diff --git a/js/ltx_sequencer.js b/js/ltx_sequencer.js
index 27b18f5..2df62a0 100644
--- a/js/ltx_sequencer.js
+++ b/js/ltx_sequencer.js
@@ -22,28 +22,47 @@ function toggleWidget(widget, visible) {
     }
 }
 
-// --- NEW SYNC HELPER FUNCTION ---
-// Finds all other LTXSequencer nodes globally and mirrors the value to them
-function syncWidgetAcrossNodes(sourceNode, widgetName, value) {
+/**
+ * FULL STATE SYNC: 
+ * Instead of syncing one widget, we push the entire properties object 
+ * to ensure no values are ever lost during subgraph transitions or deletions.
+ */
+function syncFullStateAcrossNodes(sourceNode) {
     if (!window._LTXSequencerGlobalNodes) return;
     
     for (const targetNode of window._LTXSequencerGlobalNodes) {
-        // Target all OTHER LTXSequencer nodes by direct object reference
-        if (targetNode !== sourceNode) {
-            
-            // 1. Always update the hidden properties cache so it remembers the sync 
-            // even if the widget isn't currently visible (e.g. fewer images loaded right now)
-            targetNode.properties[widgetName] = value;
-            
-            // 2. If the widget is currently visible on the UI, update it visually
-            if (targetNode.widgets) {
-                const targetWidget = targetNode.widgets.find(w => w.name === widgetName);
-                if (targetWidget && targetWidget.value !== value) {
-                    targetWidget.value = value;
-                    targetNode.setDirtyCanvas(true, false);
+        if (targetNode === sourceNode) continue;
+
+        // 1. Mirror the properties object completely
+        // We use a shallow copy to ensure we don't accidentally share object references
+        const newState = { ...sourceNode.properties };
+        targetNode.properties = { ...targetNode.properties, ...newState };
+
+        // 2. Check if we need to rebuild the widget list (if num_images changed)
+        const targetImageCount = targetNode.properties["num_images"] || 0;
+        const currentVisibleCount = targetNode._currentImageCount;
+
+        if (targetImageCount !== currentVisibleCount) {
+            targetNode._applyWidgetCount(targetImageCount);
+        }
+
+        // 3. Update all existing widget values visually
+        if (targetNode.widgets) {
+            let modeChanged = false;
+            targetNode.widgets.forEach(w => {
+                const newValue = targetNode.properties[w.name];
+                if (newValue !== undefined && w.value !== newValue) {
+                    w.value = newValue;
+                    if (w.name === "insert_mode") modeChanged = true;
                 }
+            });
+
+            if (modeChanged && targetNode._updateVisibility) {
+                targetNode._updateVisibility();
             }
         }
+        
+        targetNode.setDirtyCanvas(true, false);
     }
 }
 
@@ -88,12 +107,76 @@ app.registerExtension({
                 node.widgets.splice(idx, 0, separator);
             }
         };
-        setTimeout(moveSeparator, 50); // Small delay to ensure num_images is present
+        setTimeout(moveSeparator, 50);
+
+        // Binds custom callbacks to python-schema generated widgets
+        node._hookStaticWidgets = function() {
+            if (!this.widgets) return;
+            const staticNames = ["num_images", "insert_mode", "frame_rate"];
+            staticNames.forEach(name => {
+                const w = this.widgets.find(w => w.name === name);
+                if (w && !w._has_custom_callback) {
+                    const orig = w.callback;
+                    w.callback = (val) => {
+                        this.properties[name] = val;
+                        
+                        if (name === "num_images") {
+                            this._applyWidgetCount(val);
+                        }
+                        
+                        // Push full state to siblings
+                        syncFullStateAcrossNodes(this);
+
+                        if (name === "insert_mode") {
+                            this._updateVisibility();
+                        }
+                        if (orig) orig.apply(w, [val]);
+                    };
+                    w._has_custom_callback = true;
+                }
+            });
+        };
+
+        // Handles show/hiding widgets based on insertion method
+        node._updateVisibility = function() {
+            const mode = this.properties["insert_mode"] || "frames";
+            if (!this.widgets) return;
+            
+            let changed = false;
+            for (const w of this.widgets) {
+                let shouldBeVisible = true;
+                
+                if (w.name.startsWith("insert_frame_")) {
+                    shouldBeVisible = (mode === "frames");
+                } else if (w.name.startsWith("insert_second_")) {
+                    shouldBeVisible = (mode === "seconds");
+                }
+                
+                const isHidden = (w.type === "hidden");
+                if (shouldBeVisible && isHidden) {
+                    toggleWidget(w, true);
+                    changed = true;
+                } else if (!shouldBeVisible && !isHidden) {
+                    toggleWidget(w, false);
+                    changed = true;
+                }
+            }
+            
+            if (changed) {
+                this.setDirtyCanvas(true, true);
+                requestAnimationFrame(() => {
+                    if (this.computeSize) {
+                        this.setSize(this.computeSize());
+                    }
+                });
+            }
+        };
 
         // Core update: synchronize widget visibility to match imageCount
         node._applyWidgetCount = function(count) {
+            this._hookStaticWidgets();
+
             const isInitialLoad = this._currentImageCount === -1;
-            
             if (this._currentImageCount === count && !isInitialLoad) return;
             this._currentImageCount = count;
 
@@ -104,20 +187,20 @@ app.registerExtension({
                 numWidget.value = Math.max(0, Math.min(count || 0, 50));
             }
 
-            // 1. Store current widget values in properties BEFORE removing them
-            // We skip reading from `this.widgets` on the initial load because it might be scrambling.
-            if (!isInitialLoad && this.widgets) {
+            // 1. Update properties from current widget values before restructuring
+            if (this.widgets) {
                 this.widgets.forEach(w => {
-                    if (w.name.startsWith("insert_frame_") || w.name.startsWith("strength_")) {
-                        this.properties[w.name] = w.value;
+                    if (w.name.startsWith("insert_") || w.name.startsWith("strength_") || ["num_images", "insert_mode", "frame_rate"].includes(w.name)) {
+                        if (w.type !== "hidden" && w.type !== "button") this.properties[w.name] = w.value;
                     }
                 });
             }
 
-            // 2. Remove all existing dynamic insert_frame/strength/header widgets
+            // 2. Clear dynamic widgets
             if (this.widgets) {
                 this.widgets = this.widgets.filter(w => 
                     !w.name.startsWith("insert_frame_") && 
+                    !w.name.startsWith("insert_second_") && 
                     !w.name.startsWith("strength_") &&
                     !w.name.startsWith("header_")
                 );
@@ -125,9 +208,9 @@ app.registerExtension({
                 this.widgets = [];
             }
 
-            // 3. Add back exactly the right amount of widgets using the cached values
+            // 3. Rebuild precisely
             for (let i = 1; i <= count; i++) {
-                // Add header/separator widget for grouping
+                // Header
                 const headerName = `header_${i}`;
                 this.addCustomWidget({
                     name: headerName,
@@ -137,279 +220,175 @@ app.registerExtension({
                         ctx.save();
                         const margin = 10;
                         const topPadding = 15;
-                        
-                        // Subtle separator line
                         ctx.strokeStyle = "#333";
                         ctx.lineWidth = 1;
                         ctx.beginPath();
                         ctx.moveTo(margin, y + 5);
                         ctx.lineTo(widget_width - margin, y + 5);
                         ctx.stroke();
-                        
-                        // Text label
-                        ctx.fillStyle = "#dddddd"; // Light gray
+                        ctx.fillStyle = "#dddddd";
                         ctx.font = "bold 12px Arial";
                         ctx.textAlign = "left";
                         ctx.fillText(`Image #${i}`, margin, y + topPadding + 10);
                         ctx.restore();
                     },
-                    computeSize(width) {
-                        return [width, 35]; // Vertical gap + label height
-                    }
+                    computeSize(width) { return [width, 35]; }
                 });
 
-                const insertFrameWidgetName = `insert_frame_${i}`;
-                const strengthWidgetName = `strength_${i}`;
+                // Helper to add widget with full sync
+                const addSyncedWidget = (type, name, def, options) => {
+                    const saved = this.properties[name];
+                    return this.addWidget(type, name, saved !== undefined ? saved : def, (val) => {
+                        this.properties[name] = val;
+                        syncFullStateAcrossNodes(this);
+                    }, options);
+                };
 
-                // Add insert_frame widget with Sync Callback
-                const savedInsertFrameValue = this.properties[insertFrameWidgetName];
-                this.addWidget("number", insertFrameWidgetName, 
-                    savedInsertFrameValue !== undefined ? savedInsertFrameValue : 0, 
-                    (value) => {
-                        const rounded = Math.round(value);
-                        this.properties[insertFrameWidgetName] = rounded;
-                        syncWidgetAcrossNodes(this, insertFrameWidgetName, rounded); // Sync out
-                    }, { min: -9999, max: 9999, step: 10, precision: 0 }
-                );
-
-                // Add strength widget with Sync Callback
-                const savedStrengthValue = this.properties[strengthWidgetName];
-                this.addWidget("number", strengthWidgetName, 
-                    savedStrengthValue !== undefined ? savedStrengthValue : 1.0, 
-                    (value) => {
-                        this.properties[strengthWidgetName] = value;
-                        syncWidgetAcrossNodes(this, strengthWidgetName, value); // Sync out
-                    }, { min: 0.0, max: 1.0, step: 0.01 }
-                );
+                addSyncedWidget("number", `insert_frame_${i}`, 0, { min: -9999, max: 9999, step: 10, precision: 0 });
+                addSyncedWidget("number", `insert_second_${i}`, 0.0, { min: 0.0, max: 9999.0, step: 0.1, precision: 2 });
+                addSyncedWidget("number", `strength_${i}`, 1.0, { min: 0.0, max: 1.0, step: 0.01 });
             }
 
+            this._updateVisibility();
             this.setDirtyCanvas(true, true);
             requestAnimationFrame(() => {
                 if (this.computeSize) {
                     this.setSize(this.computeSize());
-                    this.size[0] = initialWidth; // keep width fixed when restructuring
+                    this.size[0] = initialWidth;
                 }
             });
         };
 
-        // --- STRICT ARRAY MAPPER: FIXES ALL SHIFTING FOREVER ---
-        // This runs the exact instant the node is loaded, before any UI widgets shift indices.
-        // It locks the perfectly mapped array values directly into our properties dictionary.
         const origConfigure = node.configure;
         node.configure = function(info) {
-            if (origConfigure) {
-                origConfigure.apply(this, arguments);
-            }
+            if (origConfigure) origConfigure.apply(this, arguments);
             if (this.widgets) {
                 this.widgets.forEach(w => {
-                    if (w.name === "num_images" || w.name.startsWith("insert_frame_") || w.name.startsWith("strength_")) {
-                        this.properties[w.name] = w.value;
+                    if (w.name.startsWith("insert_") || w.name.startsWith("strength_") || ["num_images", "insert_mode", "frame_rate"].includes(w.name)) {
+                        if (w.type !== "button") this.properties[w.name] = w.value;
                     }
                 });
             }
         };
 
-        // Handle deserialization to load properties properly from JSON
-        const originalOnConfigure = node.onConfigure;
         node.onConfigure = function(info) {
-            if (originalOnConfigure) {
-                originalOnConfigure.apply(this, arguments);
-            }
             if (info.properties) {
                 this.properties = { ...this.properties, ...info.properties };
             }
+            this._hookStaticWidgets();
             setTimeout(() => {
                 const count = readSourceImageCount(this);
-                // Fallback to properties.num_images if source node disconnected
                 let targetCount = count !== null ? count : (this.properties.num_images || 0);
                 this._applyWidgetCount(targetCount);
+                this._updateVisibility();
             }, 100);
         };
 
-        // --- STRICT ARRAY GENERATOR ---
-        // Completely detach from ComfyUI's blind visual array saving.
-        // We construct an exact 101-element strict array that Python expects.
-        // This makes your node 100% immune to UI/Header index shifting.
         const originalOnSerialize = node.onSerialize;
         node.onSerialize = function(info) {
-            // Ensure properties are strictly synced with current widget values before building
             if (this.widgets) {
                 this.widgets.forEach(w => {
-                    if (w.name === "num_images" || w.name.startsWith("insert_frame_") || w.name.startsWith("strength_")) {
-                        this.properties[w.name] = w.value;
+                    if (w.name.startsWith("insert_") || w.name.startsWith("strength_") || ["num_images", "insert_mode", "frame_rate"].includes(w.name)) {
+                        if (w.type !== "hidden" && w.type !== "button") this.properties[w.name] = w.value;
                     }
                 });
             }
-
-            if (originalOnSerialize) {
-                originalOnSerialize.apply(this, arguments);
-            }
-            
+            if (originalOnSerialize) originalOnSerialize.apply(this, arguments);
             info.properties = { ...this.properties };
             
-            // Build the exact strict array that maps 1-to-1 to the Python backend
             const strictArray = [];
-            const numWidgetVal = this.properties["num_images"];
-            strictArray.push(numWidgetVal !== undefined ? numWidgetVal : 1);
+            strictArray.push(this.properties["num_images"] !== undefined ? this.properties["num_images"] : 1);
+            strictArray.push(this.properties["insert_mode"] !== undefined ? this.properties["insert_mode"] : "frames");
+            strictArray.push(this.properties["frame_rate"] !== undefined ? this.properties["frame_rate"] : 24);
             
             for (let i = 1; i <= 50; i++) {
-                const fVal = this.properties[`insert_frame_${i}`];
-                const sVal = this.properties[`strength_${i}`];
-                strictArray.push(fVal !== undefined ? fVal : 0);
-                strictArray.push(sVal !== undefined ? sVal : 1.0);
+                strictArray.push(this.properties[`insert_frame_${i}`] !== undefined ? this.properties[`insert_frame_${i}`] : 0);
+                strictArray.push(this.properties[`insert_second_${i}`] !== undefined ? this.properties[`insert_second_${i}`] : 0.0);
+                strictArray.push(this.properties[`strength_${i}`] !== undefined ? this.properties[`strength_${i}`] : 1.0);
             }
-            
             info.widgets_values = strictArray;
         };
 
-        // Set up manual num_images widget callback
-        setTimeout(() => {
-            const numWidget = node.widgets?.find(w => w.name === "num_images");
-            if (numWidget) {
-                numWidget.callback = (val) => {
-                    node.properties["num_images"] = val;
-                    node._applyWidgetCount(val);
-                };
-            }
-        }, 100);
-
-        // Exposed receiver for push-based notifications
-        node._syncImageCount = function(count) {
-            this._applyWidgetCount(count);
-        };
-
-        // Helper: read image count from a connected MultiImageLoader node
         function readSourceImageCount(self) {
             const multiInput = self.inputs?.find(inp => inp.name === "multi_input");
             if (!multiInput || !multiInput.link) return null;
-
             const nodeGraph = self.graph || app.graph;
             
-            // Helper to safely trace back through Reroutes and ComfyUI Group Nodes/Subgraphs
             function traceUpstream(graph, linkId, visited = new Set()) {
                 if (!linkId || visited.has(linkId)) return null;
                 visited.add(linkId);
-
                 const link = graph.links[linkId];
                 if (!link) return null;
-
                 const originNode = graph.getNodeById(link.origin_id);
                 if (!originNode) return null;
-
-                if (originNode.comfyClass === "MultiImageLoader") {
-                    return originNode;
-                }
-
-                // Traverse Reroute nodes
+                if (originNode.comfyClass === "MultiImageLoader") return originNode;
                 if (originNode.type === "Reroute" || originNode.comfyClass === "Reroute") {
-                    if (originNode.inputs && originNode.inputs.length > 0 && originNode.inputs[0].link) {
-                        return traceUpstream(graph, originNode.inputs[0].link, visited);
-                    }
+                    if (originNode.inputs?.[0]?.link) return traceUpstream(graph, originNode.inputs[0].link, visited);
                 }
-
-                // Traverse standard ComfyUI Group Nodes (subgraphs)
                 if (typeof originNode.getInnerNode === "function") {
                     try {
                         const innerNode = originNode.getInnerNode(link.origin_slot);
-                        if (innerNode && innerNode.comfyClass === "MultiImageLoader") {
-                            return innerNode;
-                        }
-                    } catch (e) {
-                        console.warn("Could not trace inner node", e);
-                    }
+                        if (innerNode?.comfyClass === "MultiImageLoader") return innerNode;
+                    } catch (e) {}
                 }
-
                 return null;
             }
 
             let sourceNode = traceUpstream(nodeGraph, multiInput.link);
-
-            // Helper to extract the count once we find a node
             function getCountFromNode(n) {
                 if (typeof n._imageCount === "number") return n._imageCount;
                 const pathsWidget = n.widgets?.find(w => w.name === "image_paths");
-                if (pathsWidget) {
-                    return (pathsWidget.value || "").split('\n').map(p => p.trim()).filter(p => p.length > 0).length;
-                }
-                return null;
+                return pathsWidget ? (pathsWidget.value || "").split('\n').filter(p => p.trim()).length : null;
             }
 
-            if (sourceNode) {
-                return getCountFromNode(sourceNode);
-            }
+            if (sourceNode) return getCountFromNode(sourceNode);
 
-            // Fallback Strategy: If it is connected to something, but we couldn't resolve it
-            // directly (e.g. complex nested 3rd party subgraphs), scan the entire UI.
-            // If there is EXACTLY ONE MultiImageLoader in the workspace, safely assume that's the one.
             let multiImageLoaders = [];
             function findAllLoaders(nodes) {
                 if (!nodes) return;
                 for (let n of nodes) {
-                    if (n.comfyClass === "MultiImageLoader") {
-                        multiImageLoaders.push(n);
-                    }
-                    if (n.subgraph && n.subgraph._nodes) {
-                        findAllLoaders(n.subgraph._nodes);
-                    }
+                    if (n.comfyClass === "MultiImageLoader") multiImageLoaders.push(n);
+                    if (n.subgraph?._nodes) findAllLoaders(n.subgraph._nodes);
                 }
             }
-            if (app.graph && app.graph._nodes) {
-                findAllLoaders(app.graph._nodes);
-            }
-
-            if (multiImageLoaders.length === 1) {
-                return getCountFromNode(multiImageLoaders[0]);
-            }
-
+            if (app.graph?._nodes) findAllLoaders(app.graph._nodes);
+            if (multiImageLoaders.length === 1) return getCountFromNode(multiImageLoaders[0]);
             return null;
         }
 
-        // --- Backup polling via setInterval (4 Hz) ---
         const pollInterval = setInterval(() => {
             if (!node.graph) {
                 clearInterval(pollInterval);
                 return;
             }
             const count = readSourceImageCount(node);
-            if (count !== null) {
+            if (count !== null && count !== node._currentImageCount) {
                 node._applyWidgetCount(count);
+                syncFullStateAcrossNodes(node); // Sync the new count to others
             }
-        }, 250);
+        }, 500);
 
-        // Clean up the interval when the node is deleted
         const origOnRemoved = node.onRemoved;
         node.onRemoved = function() {
-            // Unregister this node instance
             window._LTXSequencerGlobalNodes.delete(node);
-            
             clearInterval(pollInterval);
             if (origOnRemoved) origOnRemoved.apply(this, arguments);
         };
 
-        // --- Connection change handler ---
-        const onConnectionsChange = node.onConnectionsChange;
-        node.onConnectionsChange = function(type, index, connected, link_info) {
-            if (onConnectionsChange) onConnectionsChange.apply(this, arguments);
-
-            if (type === 1) { // 1 = Input
-                const input = this.inputs[index];
-                if (input && input.name === "multi_input") {
-                    if (connected) {
-                        setTimeout(() => {
-                            const count = readSourceImageCount(this);
-                            this._applyWidgetCount(count !== null ? count : (this.properties.num_images || 0));
-                        }, 100);
-                    } else {
-                        this._applyWidgetCount(0);
-                    }
+        node.onConnectionsChange = function(type, index, connected) {
+            if (type === 1 && this.inputs[index]?.name === "multi_input") {
+                if (connected) {
+                    setTimeout(() => {
+                        const count = readSourceImageCount(this);
+                        this._applyWidgetCount(count !== null ? count : (this.properties.num_images || 0));
+                    }, 100);
+                } else {
+                    this._applyWidgetCount(0);
                 }
             }
         };
 
-        // --- Initial sync when first placed on canvas ---
-        const origOnAdded = node.onAdded;
         node.onAdded = function() {
-            if (origOnAdded) origOnAdded.apply(this, arguments);
             setTimeout(() => {
                 const count = readSourceImageCount(this);
                 this._applyWidgetCount(count !== null ? count : (this.properties.num_images || 0));
diff --git a/js/multi_image_loader.js b/js/multi_image_loader.js
index 9f04d9c..f8e8b7b 100644
--- a/js/multi_image_loader.js
+++ b/js/multi_image_loader.js
@@ -77,17 +77,28 @@ app.registerExtension({
         // Permanently neutralize the DOM widget's built-in computeSize to prevent infinite LiteGraph loops
         galleryWidget.computeSize = () => [0, 0];
 
-        // Find the paths widget and hide it
+        // --- BUG FIX ---
+        // Find the paths widget and properly hide it from LiteGraph
         const pathsWidget = node.widgets.find(w => w.name === "image_paths");
         if (pathsWidget) {
-            pathsWidget.type = "hidden"; 
-            if (pathsWidget.element) pathsWidget.element.style.display = "none";
+            // Tell LiteGraph to ignore this widget for hit-testing and drawing
+            pathsWidget.hidden = true; 
+            
+            // Return -4 to absorb LiteGraph's default 4px vertical margin between widgets,
+            // entirely eliminating its invisible "ghost" hitbox.
+            pathsWidget.computeSize = () => [0, -4]; 
+            
+            // Hide the actual DOM element
+            if (pathsWidget.element) {
+                pathsWidget.element.style.display = "none";
+            }
         }
 
-        const oldCallback = pathsWidget.callback;
+        const oldCallback = pathsWidget?.callback;
 
         // Centralized helper to prevent infinite loops when updating values internally
         function setWidgetValue(newPathsArray, isRearranging = false) {
+            if (!pathsWidget) return;
             const val = newPathsArray.join("\n");
             
             // Temporarily silence the main callback
@@ -145,7 +156,7 @@ app.registerExtension({
 
         // 2D Square Packing Algorithm: Calculates the optimal grid sizes to fill empty space
         function optimizeGrid(nodeW, containerH) {
-            const paths = (pathsWidget.value || "").split(/\n|,/).map(s => s.trim()).filter(s => s);
+            const paths = (pathsWidget?.value || "").split(/\n|,/).map(s => s.trim()).filter(s => s);
             const N = paths.length;
             
             if (N === 0) {
@@ -285,7 +296,7 @@ app.registerExtension({
 
         function refreshGallery(isRearranging = false) {
             grid.innerHTML = "";
-            const paths = (pathsWidget.value || "").split(/\n|,/).map(s => s.trim()).filter(s => s);
+            const paths = (pathsWidget?.value || "").split(/\n|,/).map(s => s.trim()).filter(s => s);
             
             if (!isRearranging) {
                 syncOutputs(paths.length);
@@ -377,7 +388,7 @@ app.registerExtension({
                     
                     // The DOM visually reorders during dragover. Here we finalize it to data.
                     const newPaths = Array.from(grid.children).map(n => n.dataset.path);
-                    const currentVal = (pathsWidget.value || "").trim();
+                    const currentVal = (pathsWidget?.value || "").trim();
                     if (newPaths.join("\n") !== currentVal) {
                         setWidgetValue(newPaths, true);
                     }
@@ -492,7 +503,7 @@ app.registerExtension({
                 } catch (e) { console.error("Upload error", e); }
             }
             if (uploaded.length > 0) {
-                const current = (pathsWidget.value || "").trim();
+                const current = (pathsWidget?.value || "").trim();
                 const allPaths = current ? current.split('\n').concat(uploaded) : uploaded;
                 setWidgetValue(allPaths, false);
             }
@@ -551,10 +562,12 @@ app.registerExtension({
         };
 
         // Hooks the main callback for external state loads (e.g., undo/redo or initial graph load)
-        pathsWidget.callback = (v) => {
-            if (oldCallback) oldCallback.apply(pathsWidget, [v]);
-            refreshGallery();
-        };
+        if (pathsWidget) {
+            pathsWidget.callback = (v) => {
+                if (oldCallback) oldCallback.apply(pathsWidget, [v]);
+                refreshGallery();
+            };
+        }
 
         setTimeout(() => refreshGallery(), 100);
     }
diff --git a/ltx_sequencer.py b/ltx_sequencer.py
index 629afbc..aa49cf7 100644
--- a/ltx_sequencer.py
+++ b/ltx_sequencer.py
@@ -15,6 +15,10 @@ class LTXSequencer(LTXVAddGuide):
         ]
         
         inputs.append(io.Int.Input("num_images", default=1, min=0, max=50, step=1, display_name="images_loaded", tooltip="Select how many index/strength widgets to configure."))
+        
+        # New global settings widgets
+        inputs.append(io.Combo.Input("insert_mode", options=["frames", "seconds"], default="frames", tooltip="Select the method for determining insertion points."))
+        inputs.append(io.Int.Input("frame_rate", default=24, min=1, max=120, step=1, tooltip="Video FPS (used for calculating second insertions)."))
 
         for i in range(1, 51):  # 1 to 50 images
             inputs.extend([
@@ -24,7 +28,16 @@ class LTXSequencer(LTXVAddGuide):
                     min=-9999,
                     max=9999,
                     step=1,
-                    tooltip=f"Frame insert_frame for image {i} (in pixel space).",
+                    tooltip=f"Frame insert point for image {i} (in pixel space).",
+                    optional=True,
+                ),
+                io.Float.Input(
+                    f"insert_second_{i}",
+                    default=0.0,
+                    min=0.0,
+                    max=9999.0,
+                    step=0.1,
+                    tooltip=f"Second insert point for image {i}.",
                     optional=True,
                 ),
                 io.Float.Input(
@@ -42,7 +55,7 @@ class LTXSequencer(LTXVAddGuide):
             node_id="LTXSequencer",
             display_name="LTX Sequencer",
             category="LTXVCustom",
-            description="Add multiple guide images at specified frame indices with strengths. Number of widgets is dynamically configured.",
+            description="Add multiple guide images at specified frame indices or seconds with strengths. Number of widgets is dynamically configured.",
             inputs=inputs,
             outputs=[
                 io.Conditioning.Output(display_name="positive"),
@@ -72,6 +85,10 @@ class LTXSequencer(LTXVAddGuide):
         _, _, latent_length, latent_height, latent_width = latent_image.shape
         batch_size = multi_input.shape[0] if multi_input is not None else 0
 
+        # Retrieve selected insertion settings
+        insert_mode = kwargs.get("insert_mode", "frames")
+        frame_rate = kwargs.get("frame_rate", 24)
+
         # Process inputs up to num_images, extracting dynamic frame/strength values from kwargs
         for i in range(1, num_images + 1):
             # Skip if this image index exceeds the batch
@@ -82,9 +99,18 @@ class LTXSequencer(LTXVAddGuide):
             if img is None:
                 continue
 
-            f_idx = kwargs.get(f"insert_frame_{i}")
+            # Calculate the final frame index based on the chosen mode
+            f_idx = None
+            if insert_mode == "frames":
+                f_idx = kwargs.get(f"insert_frame_{i}")
+            elif insert_mode == "seconds":
+                sec = kwargs.get(f"insert_second_{i}")
+                if sec is not None:
+                    f_idx = int(sec * frame_rate)
+
             if f_idx is None:
                 continue
+                
             strength = kwargs.get(f"strength_{i}", 1.0)
 
             # Execution logic mirrored from LTXVAddGuideMulti
diff --git a/multi_image_loader.py b/multi_image_loader.py
index c54eb4a..89798b2 100644
--- a/multi_image_loader.py
+++ b/multi_image_loader.py
@@ -1,9 +1,11 @@
 import torch
+import torch.nn.functional as F
 import numpy as np
 from PIL import Image, ImageOps
 import os
 import folder_paths
 import io
+import comfy.utils
 
 class MultiImageLoader:
     @classmethod
@@ -13,8 +15,9 @@ class MultiImageLoader:
                 "image_paths": ("STRING", {"default": "", "multiline": True}),
                 "width": ("INT", {"default": 0, "min": 0, "max": 8192, "step": 1}),
                 "height": ("INT", {"default": 0, "min": 0, "max": 8192, "step": 1}),
-                "upscale_method": (["lanczos", "bilinear", "nearest-exact"],),
-                "divisible_by": ("INT", {"default": 32, "min": 1, "max": 512, "step": 1}),
+                "interpolation": (["lanczos", "nearest", "bilinear", "bicubic", "area", "nearest-exact"],),
+                "resize_method": (["keep proportion", "stretch", "pad", "crop"],),
+                "multiple_of": ("INT", {"default": 0, "min": 0, "max": 512, "step": 1}),
                 "img_compression": ("INT", {"default": 18, "min": 0, "max": 100, "step": 1}),
             },
         }
@@ -25,13 +28,101 @@ class MultiImageLoader:
     FUNCTION = "load_images"
     CATEGORY = "image"
 
-    def load_images(self, image_paths, width, height, upscale_method, divisible_by, img_compression):
+    def resize_image(self, image, width, height, resize_method="keep proportion", interpolation="nearest", multiple_of=0):
+        MAX_RESOLUTION = 8192
+        _, oh, ow, _ = image.shape
+        x = y = x2 = y2 = 0
+        pad_left = pad_right = pad_top = pad_bottom = 0
+
+        if multiple_of > 1:
+            width = width - (width % multiple_of)
+            height = height - (height % multiple_of)
+
+        if resize_method == 'keep proportion' or resize_method == 'pad':
+            if width == 0 and oh < height:
+                width = MAX_RESOLUTION
+            elif width == 0 and oh >= height:
+                width = ow
+
+            if height == 0 and ow < width:
+                height = MAX_RESOLUTION
+            elif height == 0 and ow >= width:
+                height = oh
+
+            ratio = min(width / ow, height / oh)
+            new_width = round(ow * ratio)
+            new_height = round(oh * ratio)
+
+            if resize_method == 'pad':
+                pad_left = (width - new_width) // 2
+                pad_right = width - new_width - pad_left
+                pad_top = (height - new_height) // 2
+                pad_bottom = height - new_height - pad_top
+
+            width = new_width
+            height = new_height
+            
+        elif resize_method == 'crop':
+            width = width if width > 0 else ow
+            height = height if height > 0 else oh
+
+            ratio = max(width / ow, height / oh)
+            new_width = round(ow * ratio)
+            new_height = round(oh * ratio)
+            x = (new_width - width) // 2
+            y = (new_height - height) // 2
+            x2 = x + width
+            y2 = y + height
+            if x2 > new_width:
+                x -= (x2 - new_width)
+            if x < 0:
+                x = 0
+            if y2 > new_height:
+                y -= (y2 - new_height)
+            if y < 0:
+                y = 0
+            width = new_width
+            height = new_height
+            
+        else:
+            width = width if width > 0 else ow
+            height = height if height > 0 else oh
+
+        # Always apply resize logic
+        outputs = image.permute(0, 3, 1, 2)
+
+        if interpolation == "lanczos":
+            outputs = comfy.utils.lanczos(outputs, width, height)
+        else:
+            outputs = F.interpolate(outputs, size=(height, width), mode=interpolation)
+
+        if resize_method == 'pad':
+            if pad_left > 0 or pad_right > 0 or pad_top > 0 or pad_bottom > 0:
+                outputs = F.pad(outputs, (pad_left, pad_right, pad_top, pad_bottom), value=0)
+
+        outputs = outputs.permute(0, 2, 3, 1)
+
+        if resize_method == 'crop':
+            if x > 0 or y > 0 or x2 > 0 or y2 > 0:
+                outputs = outputs[:, y:y2, x:x2, :]
+
+        if multiple_of > 1 and (outputs.shape[2] % multiple_of != 0 or outputs.shape[1] % multiple_of != 0):
+            width = outputs.shape[2]
+            height = outputs.shape[1]
+            x = (width % multiple_of) // 2
+            y = (height % multiple_of) // 2
+            x2 = width - ((width % multiple_of) - x)
+            y2 = height - ((height % multiple_of) - y)
+            outputs = outputs[:, y:y2, x:x2, :]
+        
+        outputs = torch.clamp(outputs, 0, 1)
+
+        return outputs
+
+    def load_images(self, image_paths, width, height, interpolation, resize_method, multiple_of, img_compression):
         results = []
         valid_paths = [p.strip() for p in image_paths.split("\n") if p.strip()]
 
-        # Track the dimensions of the first processed image
-        first_target_w, first_target_h = None, None
-
         for path in valid_paths:
             try:
                 # Resolve full path
@@ -43,49 +134,42 @@ class MultiImageLoader:
                     print(f"Warning: Image path not found: {path}")
                     continue
 
+                # Load image
                 image = Image.open(full_path)
                 image = ImageOps.exif_transpose(image)
                 image = image.convert("RGB")
 
-                orig_w, orig_h = image.size
-                target_w, target_h = width, height
-
-                if target_w == 0 and target_h == 0:
-                    target_w, target_h = orig_w, orig_h
-                elif target_w == 0:
-                    target_w = int(orig_w * (target_h / orig_h))
-                elif target_h == 0:
-                    target_h = int(orig_h * (target_w / orig_w))
-
-                # Divisible by constraint
-                target_w = (target_w // divisible_by) * divisible_by
-                target_h = (target_h // divisible_by) * divisible_by
-                
-                # To prevent torch.cat errors, ALL images in the batch must match the dimensions 
-                # of the first successfully loaded image.
-                if first_target_w is None:
-                    first_target_w, first_target_h = target_w, target_h
-                else:
-                    target_w, target_h = first_target_w, first_target_h
-
-                if target_w != orig_w or target_h != orig_h:
-                    resample = Image.LANCZOS if upscale_method == "lanczos" else Image.BILINEAR
-                    image = image.resize((target_w, target_h), resample=resample)
-
-                # Compression
-                if img_compression > 0:
-                    img_byte_arr = io.BytesIO()
-                    image.save(img_byte_arr, format="JPEG", quality=max(1, 100 - img_compression))
-                    image = Image.open(img_byte_arr)
-
+                # Convert to Torch Tensor to prepare for Advanced Resize Logic
                 image_np = np.array(image).astype(np.float32) / 255.0
-                results.append(torch.from_numpy(image_np)[None,])
+                image_tensor = torch.from_numpy(image_np)[None,]
+
+                # Apply Advanced Resize
+                image_tensor = self.resize_image(image_tensor, width, height, resize_method, interpolation, multiple_of)
+
+                # Compression (Applied after resize to accurately maintain the effect)
+                if img_compression > 0:
+                    img_np = (image_tensor[0].numpy() * 255).clip(0, 255).astype(np.uint8)
+                    img_pil = Image.fromarray(img_np)
+                    img_byte_arr = io.BytesIO()
+                    img_pil.save(img_byte_arr, format="JPEG", quality=max(1, 100 - img_compression))
+                    img_pil = Image.open(img_byte_arr)
+                    image_tensor = torch.from_numpy(np.array(img_pil).astype(np.float32) / 255.0)[None,]
+
+                results.append(image_tensor)
             except Exception as e:
                 print(f"Error loading {path}: {e}")
 
         # Combine all successfully loaded images into a single batched tensor for multi_output
         if len(results) > 0:
-            multi_output = torch.cat(results, dim=0)
+            # Safety Check: Advanced resize methods might output differently sized tensors (e.g., 'keep proportion')
+            first_shape = results[0].shape
+            all_same_shape = all(r.shape == first_shape for r in results)
+            
+            if all_same_shape:
+                multi_output = torch.cat(results, dim=0)
+            else:
+                print("MultiImageLoader Warning: Images have different dimensions due to resize settings. Cannot batch into multi_output. Outputting zero tensor for the batch, but individual output nodes will still work fine.")
+                multi_output = torch.zeros((1, 64, 64, 3))
         else:
             # Fallback empty tensor if no valid paths
             multi_output = torch.zeros((1, 64, 64, 3))
diff --git a/pyproject.toml b/pyproject.toml
index 896c9df..4213f5e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -1,7 +1,7 @@
 [project]
 name = "WhatDreamsCost-ComfyUI"
 description = "A variety of custom ComfyUI nodes and workflows for creatives."
-version = "1.0.1"
+version = "1.1.0"
 license = {file = "LICENSE"} 
 # classifiers = [
 #     # For OS-independent nodes (works on all operating systems)
diff --git a/workflows/LTX I2V First Last Frame 3 Stage Workflow v3.json b/workflows/LTX I2V First Last Frame 2 Stage Workflow v6.json
similarity index 84%
rename from workflows/LTX I2V First Last Frame 3 Stage Workflow v3.json
rename to workflows/LTX I2V First Last Frame 2 Stage Workflow v6.json
index 444a44b..4aa02ef 100644
--- a/workflows/LTX I2V First Last Frame 3 Stage Workflow v3.json	
+++ b/workflows/LTX I2V First Last Frame 2 Stage Workflow v6.json	
@@ -1,14 +1,14 @@
 {
-  "id": "1143f409-9410-46d0-a303-318c1b2d0391",
+  "id": "a41dc75e-fc80-4307-897e-f3118e4fa21b",
   "revision": 0,
-  "last_node_id": 437,
-  "last_link_id": 1070,
+  "last_node_id": 443,
+  "last_link_id": 1080,
   "nodes": [
     {
       "id": 4,
       "type": "LTXVConcatAVLatent",
       "pos": [
-        4190,
+        4180,
         6090
       ],
       "size": [
@@ -59,7 +59,7 @@
       "id": 5,
       "type": "SaveVideo",
       "pos": [
-        4950,
+        4940,
         5950
       ],
       "size": [
@@ -97,83 +97,16 @@
       "color": "#222",
       "bgcolor": "#000"
     },
-    {
-      "id": 7,
-      "type": "2979f3eb-1c4c-45ff-8387-f1f4addb72f4",
-      "pos": [
-        4190,
-        5950
-      ],
-      "size": [
-        210,
-        100
-      ],
-      "flags": {},
-      "order": 7,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "image",
-          "type": "IMAGE",
-          "link": 1048
-        },
-        {
-          "label": "length_seconds",
-          "name": "length",
-          "type": "INT",
-          "widget": {
-            "name": "length"
-          },
-          "link": 21
-        },
-        {
-          "name": "audio_vae",
-          "type": "VAE",
-          "link": 22
-        }
-      ],
-      "outputs": [
-        {
-          "name": "LATENT",
-          "type": "LATENT",
-          "links": [
-            803
-          ]
-        },
-        {
-          "name": "Latent",
-          "type": "LATENT",
-          "links": [
-            12
-          ]
-        }
-      ],
-      "properties": {
-        "proxyWidgets": [
-          [
-            "-1",
-            "length"
-          ]
-        ],
-        "cnr_id": "comfy-core",
-        "ver": "0.17.2"
-      },
-      "widgets_values": [
-        1
-      ],
-      "color": "#222",
-      "bgcolor": "#000"
-    },
     {
       "id": 14,
       "type": "Note",
       "pos": [
-        4420,
-        5810
+        4410,
+        5780
       ],
       "size": [
         210,
-        88
+        110
       ],
       "flags": {},
       "order": 0,
@@ -183,331 +116,40 @@
       "title": "3 Stage Upscale Note",
       "properties": {},
       "widgets_values": [
-        "Stage 3 will default to 1.5x on the 3rd stage if false."
+        "Stage 3 will default to 1.5x on the 3rd stage if false.\n\nIf you want to disable Stage 3, simply bypass the 3rd stage in the subraph below."
       ],
-      "color": "#322",
-      "bgcolor": "#533"
+      "color": "#223",
+      "bgcolor": "#335"
     },
     {
-      "id": 376,
-      "type": "LTXSequencer",
+      "id": 418,
+      "type": "Note",
       "pos": [
-        3890,
-        5950
+        3080,
+        5820
       ],
       "size": [
-        270,
-        152
-      ],
-      "flags": {},
-      "order": 8,
-      "mode": 0,
-      "inputs": [
-        {
-          "name": "positive",
-          "type": "CONDITIONING",
-          "link": 796
-        },
-        {
-          "name": "negative",
-          "type": "CONDITIONING",
-          "link": 797
-        },
-        {
-          "name": "vae",
-          "type": "VAE",
-          "link": 798
-        },
-        {
-          "name": "latent",
-          "type": "LATENT",
-          "link": 803
-        },
-        {
-          "name": "multi_input",
-          "type": "IMAGE",
-          "link": 1047
-        }
-      ],
-      "outputs": [
-        {
-          "name": "positive",
-          "type": "CONDITIONING",
-          "links": [
-            799
-          ]
-        },
-        {
-          "name": "negative",
-          "type": "CONDITIONING",
-          "links": [
-            800
-          ]
-        },
-        {
-          "name": "latent",
-          "type": "LATENT",
-          "links": [
-            802
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "LTXSequencer",
-        "num_images": 0,
-        "insert_frame_1": 0,
-        "strength_1": 1,
-        "insert_frame_2": 0,
-        "strength_2": 1,
-        "insert_frame_3": 0,
-        "strength_3": 1,
-        "insert_frame_4": 0,
-        "strength_4": 1,
-        "insert_frame_5": 0,
-        "strength_5": 1,
-        "insert_frame_6": 0,
-        "strength_6": 1,
-        "insert_frame_7": 0,
-        "strength_7": 1,
-        "insert_frame_8": 0,
-        "strength_8": 1,
-        "insert_frame_9": 0,
-        "strength_9": 1,
-        "insert_frame_10": 0,
-        "strength_10": 1,
-        "insert_frame_11": 0,
-        "strength_11": 1,
-        "insert_frame_12": 0,
-        "strength_12": 1,
-        "insert_frame_13": 0,
-        "strength_13": 1,
-        "insert_frame_14": 0,
-        "strength_14": 1,
-        "insert_frame_15": 0,
-        "strength_15": 1,
-        "insert_frame_16": 0,
-        "strength_16": 1,
-        "insert_frame_17": 0,
-        "strength_17": 1,
-        "insert_frame_18": 0,
-        "strength_18": 1,
-        "insert_frame_19": 0,
-        "strength_19": 1,
-        "insert_frame_20": 0,
-        "strength_20": 1,
-        "insert_frame_21": 0,
-        "strength_21": 1,
-        "insert_frame_22": 0,
-        "strength_22": 1,
-        "insert_frame_23": 0,
-        "strength_23": 1,
-        "insert_frame_24": 0,
-        "strength_24": 1,
-        "insert_frame_25": 0,
-        "strength_25": 1,
-        "insert_frame_26": 0,
-        "strength_26": 1,
-        "insert_frame_27": 0,
-        "strength_27": 1,
-        "insert_frame_28": 0,
-        "strength_28": 1,
-        "insert_frame_29": 0,
-        "strength_29": 1,
-        "insert_frame_30": 0,
-        "strength_30": 1,
-        "insert_frame_31": 0,
-        "strength_31": 1,
-        "insert_frame_32": 0,
-        "strength_32": 1,
-        "insert_frame_33": 0,
-        "strength_33": 1,
-        "insert_frame_34": 0,
-        "strength_34": 1,
-        "insert_frame_35": 0,
-        "strength_35": 1,
-        "insert_frame_36": 0,
-        "strength_36": 1,
-        "insert_frame_37": 0,
-        "strength_37": 1,
-        "insert_frame_38": 0,
-        "strength_38": 1,
-        "insert_frame_39": 0,
-        "strength_39": 1,
-        "insert_frame_40": 0,
-        "strength_40": 1,
-        "insert_frame_41": 0,
-        "strength_41": 1,
-        "insert_frame_42": 0,
-        "strength_42": 1,
-        "insert_frame_43": 0,
-        "strength_43": 1,
-        "insert_frame_44": 0,
-        "strength_44": 1,
-        "insert_frame_45": 0,
-        "strength_45": 1,
-        "insert_frame_46": 0,
-        "strength_46": 1,
-        "insert_frame_47": 0,
-        "strength_47": 1,
-        "insert_frame_48": 0,
-        "strength_48": 1,
-        "insert_frame_49": 0,
-        "strength_49": 1,
-        "insert_frame_50": 0,
-        "strength_50": 1
-      },
-      "widgets_values": [
-        0,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1,
-        0,
-        1
-      ],
-      "color": "#222",
-      "bgcolor": "#000"
-    },
-    {
-      "id": 381,
-      "type": "MultiImageLoader",
-      "pos": [
-        3550,
-        5950
-      ],
-      "size": [
-        310,
-        277
+        280,
+        88
       ],
       "flags": {},
       "order": 1,
       "mode": 0,
       "inputs": [],
-      "outputs": [
-        {
-          "name": "multi_output",
-          "type": "IMAGE",
-          "links": [
-            1046,
-            1047,
-            1048
-          ]
-        }
-      ],
-      "properties": {
-        "Node name for S&R": "MultiImageLoader"
-      },
+      "outputs": [],
+      "title": "Model Loader Note",
+      "properties": {},
       "widgets_values": [
-        "",
-        0,
-        0,
-        "lanczos",
-        32,
-        18,
-        ""
+        "↓ Select your own models in this subgraph ↓"
       ],
-      "color": "#222",
-      "bgcolor": "#000"
+      "color": "#223",
+      "bgcolor": "#335"
     },
     {
       "id": 16,
       "type": "Note",
       "pos": [
-        4680,
+        4670,
         6110
       ],
       "size": [
@@ -519,42 +161,43 @@
       "mode": 0,
       "inputs": [],
       "outputs": [],
+      "title": "Decode Note",
       "properties": {},
       "widgets_values": [
         "Enable optimized decoding to use tiled vae decoder."
       ],
-      "color": "#322",
-      "bgcolor": "#533"
+      "color": "#223",
+      "bgcolor": "#335"
     },
     {
-      "id": 418,
-      "type": "Note",
+      "id": 439,
+      "type": "MarkdownNote",
       "pos": [
-        3110,
-        5810
+        2680,
+        6180
       ],
       "size": [
-        220,
-        88
+        370,
+        320
       ],
       "flags": {},
       "order": 3,
       "mode": 0,
       "inputs": [],
       "outputs": [],
-      "title": "Model Loader Note",
+      "title": "FAQ",
       "properties": {},
       "widgets_values": [
-        "↓ Select your own models in here ↓"
+        "# FAQ\n\n**How do I set the length of the video?**\n\nYou can set the length of the video in the Model Loader Subgraph →\n\n**I keep getting errors when running this workflow!**\n\nDouble check that all of the correct models loaded. This is using the newest version of 2x upscaler (v1.1). You can change it to the older one under the Model Loader.\n\n**Where do I download these models??**\n\nThere is a good list of models and download links here: <https://github.com/wildminder/awesome-ltx2?tab=readme-ov-file>\n\nAlso the latest v1.1 spatial upscaler can be found here: <https://huggingface.co/Lightricks/LTX-2.3/tree/main>\n\nThe tiny vae (taeltx2_3.safetensors) is found here:\n<https://huggingface.co/Kijai/LTX2.3_comfy/blob/main/vae/taeltx2_3.safetensors>\n\n\n\n\n\n\n\n\n"
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-      "title": "FAQ",
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-        "# FAQ\n\n**How do I set the length of the video?**\n\nYou can set the length of the video under the Model Loader Subgraph →\n\n**I keep getting errors when running this workflow!**\n\nDouble check that all of the correct models loaded. This is using the newest version of 2x upscaler (v1.1). You can change it to the older one under the Model Loader.\n\n**When is the tutorial coming???**\n\nComing soon!\n\n"
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           "name": "LATENT_UPSCALE_MODEL",
           "type": "LATENT_UPSCALE_MODEL",
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+        },
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+          "type": "LATENT",
+          "link": 804
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+          "type": "NOISE",
+          "link": 44
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+          "name": "vae",
+          "type": "VAE",
+          "link": 45
+        },
+        {
+          "name": "image",
+          "type": "IMAGE",
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+        {
+          "label": "Upscale 2x on Stage 3",
+          "name": "value",
+          "type": "BOOLEAN",
+          "widget": {
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+          "name": "upscale_model",
+          "type": "LATENT_UPSCALE_MODEL",
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+          "name": "output",
+          "type": "LATENT",
+          "links": [
+            47
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+        }
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+      "color": "#222",
+      "bgcolor": "#000"
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@@ -1172,118 +1384,6 @@
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             "type": "LazySwitchKJ",
@@ -1446,12 +1546,124 @@
             "color": "#222",
             "bgcolor": "#000"
           },
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+            "type": "LTXVSeparateAVLatent",
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+                "localized_name": "av_latent",
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+                "name": "video_latent",
+                "type": "LATENT",
+                "links": [
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+                  1059
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@@ -5799,7 +6321,7 @@
               82
             ],
             "flags": {},
-            "order": 5,
+            "order": 4,
             "mode": 0,
             "inputs": [
               {
@@ -5846,7 +6368,7 @@
             "id": 365,
             "type": "07609e03-45f4-49c7-a233-a933ebf95094",
             "pos": [
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             "size": [
@@ -5854,7 +6376,7 @@
               58
             ],
             "flags": {},
-            "order": 9,
+            "order": 12,
             "mode": 0,
             "inputs": [
               {
@@ -5892,6 +6414,232 @@
             ],
             "color": "#222",
             "bgcolor": "#000"
+          },
+          {
+            "id": 443,
+            "type": "VAELoaderKJ",
+            "pos": [
+              2560,
+              5470
+            ],
+            "size": [
+              270,
+              110
+            ],
+            "flags": {},
+            "order": 5,
+            "mode": 0,
+            "inputs": [],
+            "outputs": [
+              {
+                "localized_name": "VAE",
+                "name": "VAE",
+                "type": "VAE",
+                "links": [
+                  1072
+                ]
+              }
+            ],
+            "title": "Tiny VAELoader KJ",
+            "properties": {
+              "cnr_id": "comfyui-kjnodes",
+              "ver": "1.2.5",
+              "Node name for S&R": "VAELoaderKJ"
+            },
+            "widgets_values": [
+              "taeltx2_3.safetensors",
+              "main_device",
+              "bf16"
+            ],
+            "color": "#222",
+            "bgcolor": "#000"
+          },
+          {
+            "id": 442,
+            "type": "LTX2SamplingPreviewOverride",
+            "pos": [
+              2850,
+              5470
+            ],
+            "size": [
+              270,
+              100
+            ],
+            "flags": {},
+            "order": 8,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "model",
+                "name": "model",
+                "type": "MODEL",
+                "link": 1073
+              },
+              {
+                "localized_name": "latent_upscale_model",
+                "name": "latent_upscale_model",
+                "shape": 7,
+                "type": "LATENT_UPSCALE_MODEL",
+                "link": null
+              },
+              {
+                "localized_name": "vae",
+                "name": "vae",
+                "shape": 7,
+                "type": "VAE",
+                "link": 1072
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "MODEL",
+                "name": "MODEL",
+                "type": "MODEL",
+                "links": [
+                  1074
+                ]
+              }
+            ],
+            "properties": {
+              "cnr_id": "comfyui-kjnodes",
+              "ver": "1.3.4",
+              "Node name for S&R": "LTX2SamplingPreviewOverride"
+            },
+            "widgets_values": [
+              16
+            ],
+            "color": "#222",
+            "bgcolor": "#000"
+          },
+          {
+            "id": 426,
+            "type": "CheckpointLoaderSimple",
+            "pos": [
+              2560,
+              5330
+            ],
+            "size": [
+              270,
+              98
+            ],
+            "flags": {},
+            "order": 6,
+            "mode": 0,
+            "inputs": [],
+            "outputs": [
+              {
+                "localized_name": "MODEL",
+                "name": "MODEL",
+                "type": "MODEL",
+                "links": [
+                  1073
+                ]
+              },
+              {
+                "localized_name": "CLIP",
+                "name": "CLIP",
+                "type": "CLIP",
+                "links": null
+              },
+              {
+                "localized_name": "VAE",
+                "name": "VAE",
+                "type": "VAE",
+                "links": null
+              }
+            ],
+            "properties": {
+              "cnr_id": "comfy-core",
+              "ver": "0.17.2",
+              "Node name for S&R": "CheckpointLoaderSimple"
+            },
+            "widgets_values": [
+              "ltx-2.3-22b-dev-fp8.safetensors"
+            ],
+            "color": "#222",
+            "bgcolor": "#000"
+          },
+          {
+            "id": 429,
+            "type": "LoraLoaderModelOnly",
+            "pos": [
+              3140,
+              5480
+            ],
+            "size": [
+              260,
+              82
+            ],
+            "flags": {},
+            "order": 9,
+            "mode": 0,
+            "inputs": [
+              {
+                "localized_name": "model",
+                "name": "model",
+                "type": "MODEL",
+                "link": 1074
+              }
+            ],
+            "outputs": [
+              {
+                "localized_name": "MODEL",
+                "name": "MODEL",
+                "type": "MODEL",
+                "links": [
+                  1067
+                ]
+              }
+            ],
+            "properties": {
+              "cnr_id": "comfy-core",
+              "ver": "0.3.75",
+              "Node name for S&R": "LoraLoaderModelOnly",
+              "enableTabs": false,
+              "tabWidth": 65,
+              "tabXOffset": 10,
+              "hasSecondTab": false,
+              "secondTabText": "Send Back",
+              "secondTabOffset": 80,
+              "secondTabWidth": 65,
+              "models": [
+                {
+                  "name": "ltx-2.3-22b-distilled-lora-384.safetensors",
+                  "url": "https://huggingface.co/Lightricks/LTX-2.3/resolve/main/ltx-2.3-22b-distilled-lora-384.safetensors",
+                  "directory": "loras"
+                }
+              ]
+            },
+            "widgets_values": [
+              "ltx2\\ltx-2.3-22b-distilled-lora-dynamic_fro09_avg_rank_105_bf16.safetensors",
+              0.5
+            ],
+            "color": "#222",
+            "bgcolor": "#000"
+          },
+          {
+            "id": 441,
+            "type": "MarkdownNote",
+            "pos": [
+              2160,
+              5500
+            ],
+            "size": [
+              370,
+              320
+            ],
+            "flags": {},
+            "order": 7,
+            "mode": 0,
+            "inputs": [],
+            "outputs": [],
+            "title": "FAQ",
+            "properties": {},
+            "widgets_values": [
+              "# FAQ\n\n**How do I set the length of the video?**\n\nYou can set the length of the video in the Model Loader Subgraph →\n\n**I keep getting errors when running this workflow!**\n\nDouble check that all of the correct models loaded. This is using the newest version of 2x upscaler (v1.1). You can change it to the older one under the Model Loader.\n\n**Where do I download these models??**\n\nThere is a good list of models and download links here: <https://github.com/wildminder/awesome-ltx2?tab=readme-ov-file>\n\nAlso the latest v1.1 spatial upscaler can be found here: <https://huggingface.co/Lightricks/LTX-2.3/tree/main>\n\nThe tiny vae (taeltx2_3.safetensors) is found here:\n<https://huggingface.co/Kijai/LTX2.3_comfy/blob/main/vae/taeltx2_3.safetensors>\n\n\n\n\n\n\n\n\n"
+            ],
+            "color": "#432",
+            "bgcolor": "#653"
           }
         ],
         "groups": [],
@@ -6009,9 +6757,25 @@
             "type": "MODEL"
           },
           {
-            "id": 1068,
+            "id": 1072,
+            "origin_id": 443,
+            "origin_slot": 0,
+            "target_id": 442,
+            "target_slot": 2,
+            "type": "VAE"
+          },
+          {
+            "id": 1073,
             "origin_id": 426,
             "origin_slot": 0,
+            "target_id": 442,
+            "target_slot": 0,
+            "type": "MODEL"
+          },
+          {
+            "id": 1074,
+            "origin_id": 442,
+            "origin_slot": 0,
             "target_id": 429,
             "target_slot": 0,
             "type": "MODEL"
@@ -6026,8 +6790,8 @@
         "version": 1,
         "state": {
           "lastGroupId": 33,
-          "lastNodeId": 437,
-          "lastLinkId": 1070,
+          "lastNodeId": 443,
+          "lastLinkId": 1080,
           "lastRerouteId": 0
         },
         "revision": 0,
@@ -6057,7 +6821,7 @@
             "name": "value",
             "type": "INT",
             "linkIds": [
-              1070
+              1071
             ],
             "label": "Seconds",
             "pos": [
@@ -6197,7 +6961,7 @@
                 "widget": {
                   "name": "value"
                 },
-                "link": 1070
+                "link": 1071
               }
             ],
             "outputs": [
@@ -6249,7 +7013,7 @@
             "type": "INT"
           },
           {
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+            "id": 1071,
             "origin_id": -10,
             "origin_slot": 0,
             "target_id": 139,
@@ -6266,8 +7030,8 @@
         "version": 1,
         "state": {
           "lastGroupId": 33,
-          "lastNodeId": 437,
-          "lastLinkId": 1070,
+          "lastNodeId": 443,
+          "lastLinkId": 1080,
           "lastRerouteId": 0
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@@ -6276,9 +7040,9 @@
         "inputNode": {
           "id": -10,
           "bounding": [
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+            4330,
             5940,
-            164.869140625,
+            187.052734375,
             240
           ]
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@@ -6302,7 +7066,7 @@
               23
             ],
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+              4497.052734375,
               5960
             ]
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@@ -6316,7 +7080,7 @@
               871
             ],
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               5980
             ]
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@@ -6330,7 +7094,7 @@
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             ],
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               6000
             ]
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@@ -6356,7 +7120,7 @@
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-              4504.869140625,
+              4497.052734375,
               6040
             ]
           },
@@ -6370,7 +7134,7 @@
             ],
             "label": "video_vae",
             "pos": [
-              4504.869140625,
+              4497.052734375,
               6060
             ]
           },
@@ -6383,7 +7147,7 @@
               30
             ],
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-              4504.869140625,
+              4497.052734375,
               6080
             ]
           },
@@ -6394,9 +7158,9 @@
             "linkIds": [
               40
             ],
-            "label": "upscale 2x on stage 3",
+            "label": "Upscale 2x on Stage 3",
             "pos": [
-              4504.869140625,
+              4497.052734375,
               6100
             ]
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@@ -6409,7 +7173,7 @@
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             ],
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               6120
             ]
           },
@@ -6421,9 +7185,9 @@
               1036,
               1039
             ],
-            "label": "2x_upscale_model",
+            "label": "2x_spatial_upscale_model",
             "pos": [
-              4504.869140625,
+              4497.052734375,
               6140
             ]
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@@ -6457,7 +7221,7 @@
               46
             ],
             "flags": {},
-            "order": 3,
+            "order": 4,
             "mode": 0,
             "inputs": [
               {
@@ -6470,7 +7234,7 @@
                 "localized_name": "audio_latent",
                 "name": "audio_latent",
                 "type": "LATENT",
-                "link": 1043
+                "link": 1080
               }
             ],
             "outputs": [
@@ -6504,7 +7268,7 @@
               70
             ],
             "flags": {},
-            "order": 4,
+            "order": 5,
             "mode": 0,
             "inputs": [
               {
@@ -6557,6 +7321,95 @@
             "color": "#222",
             "bgcolor": "#000"
           },
+          {
+            "id": 2,
+            "type": "afa29944-eb58-40a5-8e76-484f2503fa0c",
+            "pos": [
+              4540,
+              5950
+            ],
+            "size": [
+              190,
+              195.734375
+            ],
+            "flags": {},
+            "order": 1,
+            "mode": 0,
+            "inputs": [
+              {
+                "name": "model",
+                "type": "MODEL",
+                "link": 3
+              },
+              {
+                "name": "positive",
+                "type": "CONDITIONING",
+                "link": 4
+              },
+              {
+                "name": "negative",
+                "type": "CONDITIONING",
+                "link": 5
+              },
+              {
+                "name": "latent_image",
+                "type": "LATENT",
+                "link": 6
+              },
+              {
+                "name": "noise",
+                "type": "NOISE",
+                "link": 7
+              }
+            ],
+            "outputs": [
+              {
+                "name": "video_latent",
+                "type": "LATENT",
+                "links": [
+                  837
+                ]
+              },
+              {
+                "name": "audio_latent",
+                "type": "LATENT",
+                "links": [
+                  794
+                ]
+              }
+            ],
+            "properties": {
+              "proxyWidgets": [],
+              "cnr_id": "comfy-core",
+              "ver": "0.17.2"
+            },
+            "widgets_values": [],
+            "color": "#222",
+            "bgcolor": "#000"
+          },
+          {
+            "id": 440,
+            "type": "Note",
+            "pos": [
+              4970,
+              5810
+            ],
+            "size": [
+              210,
+              88
+            ],
+            "flags": {},
+            "order": 0,
+            "mode": 0,
+            "inputs": [],
+            "outputs": [],
+            "properties": {},
+            "widgets_values": [
+              "Bypass Stage #3 to skip the 2nd upscale stage."
+            ],
+            "color": "#223",
+            "bgcolor": "#335"
+          },
           {
             "id": 8,
             "type": "535e663f-da59-47c1-aab5-c78ff202cb16",
@@ -6569,8 +7422,8 @@
               330.9668884277344
             ],
             "flags": {},
-            "order": 2,
-            "mode": 0,
+            "order": 3,
+            "mode": 4,
             "inputs": [
               {
                 "name": "model",
@@ -6612,7 +7465,7 @@
               {
                 "name": "audio_latent",
                 "type": "LATENT",
-                "link": 28
+                "link": 1079
               },
               {
                 "label": "use 2x on stage 3",
@@ -6647,9 +7500,7 @@
               {
                 "name": "audio_latent",
                 "type": "LATENT",
-                "links": [
-                  1043
-                ]
+                "links": []
               }
             ],
             "properties": {
@@ -6680,7 +7531,7 @@
               299.71875
             ],
             "flags": {},
-            "order": 1,
+            "order": 2,
             "mode": 0,
             "inputs": [
               {
@@ -6748,7 +7599,8 @@
                 "name": "audio_latent",
                 "type": "LATENT",
                 "links": [
-                  28
+                  1079,
+                  1080
                 ]
               },
               {
@@ -6776,72 +7628,6 @@
             "widgets_values": [],
             "color": "#222",
             "bgcolor": "#000"
-          },
-          {
-            "id": 2,
-            "type": "afa29944-eb58-40a5-8e76-484f2503fa0c",
-            "pos": [
-              4540,
-              5950
-            ],
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-              190,
-              195.734375
-            ],
-            "flags": {},
-            "order": 0,
-            "mode": 0,
-            "inputs": [
-              {
-                "name": "model",
-                "type": "MODEL",
-                "link": 3
-              },
-              {
-                "name": "positive",
-                "type": "CONDITIONING",
-                "link": 4
-              },
-              {
-                "name": "negative",
-                "type": "CONDITIONING",
-                "link": 5
-              },
-              {
-                "name": "latent_image",
-                "type": "LATENT",
-                "link": 6
-              },
-              {
-                "name": "noise",
-                "type": "NOISE",
-                "link": 7
-              }
-            ],
-            "outputs": [
-              {
-                "name": "video_latent",
-                "type": "LATENT",
-                "links": [
-                  837
-                ]
-              },
-              {
-                "name": "audio_latent",
-                "type": "LATENT",
-                "links": [
-                  794
-                ]
-              }
-            ],
-            "properties": {
-              "proxyWidgets": [],
-              "cnr_id": "comfy-core",
-              "ver": "0.17.2"
-            },
-            "widgets_values": [],
-            "color": "#222",
-            "bgcolor": "#000"
           }
         ],
         "groups": [],
@@ -6854,14 +7640,6 @@
             "target_slot": 6,
             "type": "LATENT"
           },
-          {
-            "id": 28,
-            "origin_id": 6,
-            "origin_slot": 1,
-            "target_id": 8,
-            "target_slot": 7,
-            "type": "LATENT"
-          },
           {
             "id": 3,
             "origin_id": -10,
@@ -7095,8 +7873,16 @@
             "type": "LATENT_UPSCALE_MODEL"
           },
           {
-            "id": 1043,
-            "origin_id": 8,
+            "id": 1079,
+            "origin_id": 6,
+            "origin_slot": 1,
+            "target_id": 8,
+            "target_slot": 7,
+            "type": "LATENT"
+          },
+          {
+            "id": 1080,
+            "origin_id": 6,
             "origin_slot": 1,
             "target_id": 371,
             "target_slot": 1,
@@ -7120,8 +7906,8 @@
     "ds": {
       "scale": 1,
       "offset": [
-        -2742.877149125813,
-        -5602.752240706775
+        -3243,
+        -5621
       ]
     }
   },
diff --git a/workflows/LTX I2V First Last Frame 3 Stage Workflow v3.png b/workflows/LTX I2V First Last Frame 3 Stage Workflow v3.png
deleted file mode 100644
index dd31dd8..0000000
Binary files a/workflows/LTX I2V First Last Frame 3 Stage Workflow v3.png and /dev/null differ
diff --git a/workflows/LTX I2V First Last Frame 3 Stage Workflow v6.json b/workflows/LTX I2V First Last Frame 3 Stage Workflow v6.json
new file mode 100644
index 0000000..735c6d8
--- /dev/null
+++ b/workflows/LTX I2V First Last Frame 3 Stage Workflow v6.json	
@@ -0,0 +1,7916 @@
+{
+  "id": "a41dc75e-fc80-4307-897e-f3118e4fa21b",
+  "revision": 0,
+  "last_node_id": 443,
+  "last_link_id": 1079,
+  "nodes": [
+    {
+      "id": 4,
+      "type": "LTXVConcatAVLatent",
+      "pos": [
+        4180,
+        6090
+      ],
+      "size": [
+        210,
+        60
+      ],
+      "flags": {},
+      "order": 9,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "video_latent",
+          "type": "LATENT",
+          "link": 802
+        },
+        {
+          "name": "audio_latent",
+          "type": "LATENT",
+          "link": 12
+        }
+      ],
+      "outputs": [
+        {
+          "name": "latent",
+          "type": "LATENT",
+          "links": [
+            804
+          ]
+        }
+      ],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.7.0",
+        "Node name for S&R": "LTXVConcatAVLatent",
+        "enableTabs": false,
+        "tabWidth": 65,
+        "tabXOffset": 10,
+        "hasSecondTab": false,
+        "secondTabText": "Send Back",
+        "secondTabOffset": 80,
+        "secondTabWidth": 65
+      },
+      "widgets_values": [],
+      "color": "#222",
+      "bgcolor": "#000"
+    },
+    {
+      "id": 5,
+      "type": "SaveVideo",
+      "pos": [
+        4940,
+        5950
+      ],
+      "size": [
+        660,
+        440
+      ],
+      "flags": {},
+      "order": 12,
+      "mode": 0,
+      "inputs": [
+        {
+          "name": "video",
+          "type": "VIDEO",
+          "link": 13
+        }
+      ],
+      "outputs": [],
+      "properties": {
+        "cnr_id": "comfy-core",
+        "ver": "0.5.1",
+        "Node name for S&R": "SaveVideo",
+        "enableTabs": false,
+        "tabWidth": 65,
+        "tabXOffset": 10,
+        "hasSecondTab": false,
+        "secondTabText": "Send Back",
+        "secondTabOffset": 80,
+        "secondTabWidth": 65
+      },
+      "widgets_values": [
+        "video/LTX",
+        "auto",
+        "auto"
+      ],
+      "color": "#222",
+      "bgcolor": "#000"
+    },
+    {
+      "id": 14,
+      "type": "Note",
+      "pos": [
+        4410,
+        5780
+      ],
+      "size": [
+        210,
+        110
+      ],
+      "flags": {},
+      "order": 0,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "title": "3 Stage Upscale Note",
+      "properties": {},
+      "widgets_values": [
+        "Stage 3 will default to 1.5x on the 3rd stage if false.\n\nIf you want to disable Stage 3, simply bypass the 3rd stage in the subraph below."
+      ],
+      "color": "#223",
+      "bgcolor": "#335"
+    },
+    {
+      "id": 418,
+      "type": "Note",
+      "pos": [
+        3080,
+        5820
+      ],
+      "size": [
+        280,
+        88
+      ],
+      "flags": {},
+      "order": 1,
+      "mode": 0,
+      "inputs": [],
+      "outputs": [],
+      "title": "Model Loader Note",
+      "properties": {},
+      "widgets_values": [
+        "↓ Select your own models in this subgraph ↓"
+      ],
+      "color": "#223",
+      "bgcolor": "#335"
+    },
+    {
+      "id": 16,
+      "type": "Note",
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