Changelog

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User Interface Enhancements

• Recently Used Items API: New API for tracking recently used items in the interface, streamlining workflow creation by providing quick access to frequently used nodes and components
• Improved Workflow Navigation: Enhanced user experience with better organization of commonly accessed elements, reducing time spent searching for nodes

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Advanced Model Integration

• Qwen Vision Model Support: Initial support for Qwen image models with comprehensive configuration options including default shift settings and flexible latent size handling
• Optimized Image Processing: Enhanced Qwen model integration allows for more versatile image analysis and generation workflows, expanding AI capabilities for vision tasks

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Revolutionary Video Generation

• Veo3 Video Generation: Added powerful Veo3 video generation node with integrated audio support, enabling creators to produce high-quality video content with synchronized audio directly in ComfyUI workflows
• Audio-Visual Synthesis: Breakthrough capability combining video and audio generation in a single node, perfect for content creators and multimedia professionals

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Performance & Stability Improvements

• Enhanced Memory Management: Optimized conditional (cond) VRAM usage through improved casting and device transfer operations, reducing memory overhead during complex generation tasks
• Device Consistency: Comprehensive fixes ensuring all conditioning data and context remain on correct devices, preventing crashes and improving workflow reliability
• ControlNet Stability: Resolved critical ControlNet compatibility issues, restoring full functionality for precise image control workflows

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Developer & System Enhancements

• Robust Error Handling: Added intelligent warnings and crash prevention when conditioning devices don’t match, improving workflow debugging and stability
• Template Updates: Multiple template version updates (0.1.47, 0.1.48, 0.1.51) maintaining compatibility with latest development standards and ensuring smooth node integration

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Workflow Benefits

• Faster Iteration: Recently used items API enables quicker workflow assembly and modification
• Enhanced Creativity: Qwen vision models open new possibilities for image understanding and manipulation workflows
• Professional Video Production: Veo3 integration transforms ComfyUI into a comprehensive multimedia creation platform
• Improved Reliability: Memory optimizations and device management fixes ensure stable operation with complex, multi-model workflows
• Better Performance: Optimized VRAM usage allows for more ambitious projects on systems with limited resources

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ComfyAPI Core Framework

• ComfyAPI Core v0.0.2: Major update to the core API framework, providing improved stability and extensibility for custom node development and third-party integrations
• Partial Execution Support: New backend support for partial workflow execution, enabling more efficient processing of complex multi-stage workflows by allowing selective node execution

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Video Processing Improvements

• WAN Camera Memory Optimization: Enhanced memory management for WAN-based camera workflows, reducing VRAM usage during video processing operations
• WanFirstLastFrameToVideo Fix: Resolved critical issue preventing proper video generation when clip vision components are not available, improving workflow reliability

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Performance & Model Optimizations

• VAE Nonlinearity Enhancement: Replaced manual activation functions with optimized torch.silu in VAE operations, providing better performance and numerical stability for image encoding/decoding
• WAN VAE Optimizations: Additional fine-tuning optimizations for WAN VAE operations, improving processing speed and memory efficiency in video generation workflows

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Node Schema Evolution

• V3 Node Schema Definition: Initial implementation of next-generation node schema system, laying the groundwork for enhanced node type definitions and improved workflow validation
• Template Updates: Multiple template version updates (0.1.44, 0.1.45) ensuring compatibility with latest node development standards and best practices

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Workflow Development Benefits

• Enhanced Video Workflows: Improved stability and performance for video generation pipelines, particularly those using WAN-based models
• Better Memory Management: Optimized memory usage patterns enable more complex workflows on systems with limited VRAM
• Improved API Reliability: Core API enhancements provide more stable foundation for custom node development and workflow automation
• Partial Execution Flexibility: New partial execution capabilities allow for more efficient debugging and iterative workflow development

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WAN 2.2 Model Optimizations

• Reduced Memory Footprint: Eliminated unnecessary memory clones in WAN 2.2 VAE operations, significantly reducing memory usage during image encoding/decoding workflows
• 5B I2V Model Support: Major memory optimization for WAN 2.2 5B image-to-video models, making these large-scale models more accessible for creators with limited VRAM

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Enhanced VRAM Management

• Windows Large Card Support: Added extra reserved VRAM allocation for high-end graphics cards on Windows, preventing system instability during intensive generation workflows
• Better Memory Allocation: Improved memory management for users working with multiple large models simultaneously

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Workflow Performance Benefits

• Faster VAE Processing: WAN 2.2 VAE operations now run more efficiently with reduced memory overhead, enabling smoother image generation pipelines
• Stable Large Model Inference: Enhanced stability when working with billion-parameter models, crucial for professional AI art creation and research workflows
• Improved Batch Processing: Memory optimizations enable better handling of batch operations with large models

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Audio Processing Enhancements

• PyAV Audio Backend: Replaced torchaudio.load with PyAV for more reliable audio processing in video workflows, improving compatibility and performance
• Better Audio Integration: Enhanced audio handling for multimedia generation workflows, particularly beneficial for video content creators

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Expanded Hardware Support

• Iluvatar CoreX Support: Added native support for Iluvatar CoreX accelerators, expanding hardware options for AI inference
• Intel XPU Optimization: Comprehensive XPU support improvements including async offload capabilities and device-specific optimizations
• AMD ROCm Enhancements: Enabled PyTorch attention by default for gfx1201 on Torch 2.8, improving performance on AMD hardware
• CUDA Memory Management: Fixed CUDA malloc to only activate on CUDA-enabled PyTorch installations, preventing conflicts on other platforms

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Sampling Algorithm Improvements

• Euler CFG++ Enhancement: Separated denoised and noise estimation processes in Euler CFG++ sampler for improved numerical precision and quality
• WAN Model Support: Added comprehensive support for WAN (Wavelet-based Attention Network) models including ATI support and WAN 2.2 compatibility

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Advanced Training Features

• Enhanced Training Nodes: Added algorithm support, gradient accumulation, and optional gradient checkpointing to training workflows
• Improved Training Flexibility: Better memory management and performance optimization for custom model training

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Node & Workflow Enhancements

• Moonvalley V2V Node: Added Moonvalley Marey V2V node with enhanced input validation for video-to-video workflows
• Negative Prompt Updates: Improved negative prompt handling for Moonvalley nodes, providing better control over generation outputs
• History API Enhancement: Added map_function parameter to get_history API for more flexible workflow history management

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API & System Improvements

• Frontend Version Tracking: Added required_frontend_version parameter in /system_stats API response for better version compatibility
• Device Information: Enhanced XPU device name printing for better hardware identification and debugging
• Template Updates: Multiple template updates (0.1.40, 0.1.41) ensuring compatibility with latest node development standards

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Developer Experience

• Documentation Updates: Enhanced README with HiDream E1.1 examples and updated model integration guides
• Line Ending Fixes: Improved cross-platform compatibility by standardizing line endings in workflows
• Code Cleanup: Removed deprecated code and optimized various components for better maintainability

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New Sampling & Generation Features

• SA-Solver Sampler: New reconstructed SA-Solver sampling algorithm providing enhanced numerical stability and quality for complex generation workflows
• Experimental CFGNorm Node: Advanced classifier-free guidance normalization for improved control over generation quality and style consistency
• Nested Dual CFG Support: Added nested style configuration to DualCFGGuider node, offering more sophisticated guidance control patterns
• SamplingPercentToSigma Node: New utility node for precise sigma calculation from sampling percentages, improving workflow flexibility

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Enhanced Training Capabilities

• Multi Image-Caption Dataset Support: LoRA training node now handles multiple image-caption datasets simultaneously, streamlining training workflows
• Better Training Loop Implementation: Optimized training algorithms for improved convergence and stability during model fine-tuning
• Enhanced Error Detection: Added model detection error hints for LoRA operations, providing clearer feedback when issues occur

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Platform & Performance Improvements

• Async Node Support: Full support for asynchronous node functions with earlier execution optimization, improving workflow performance for I/O intensive operations
• Chroma Flexibility: Un-hardcoded patch_size parameter in Chroma, allowing better adaptation to different model configurations
• LTXV VAE Decoder: Switched to improved default padding mode for better image quality with LTXV models
• Safetensors Memory Management: Added workaround for mmap issues, improving reliability when loading large model files

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API & Integration Enhancements

• Custom Prompt IDs: API now allows specifying prompt IDs for better workflow tracking and management
• Kling API Optimization: Increased polling timeout to prevent user timeouts during video generation workflows
• History Token Cleanup: Removed sensitive tokens from history items for improved security
• Python 3.9 Compatibility: Fixed compatibility issues ensuring broader platform support

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Bug Fixes & Stability

• MaskComposite Fixes: Resolved errors when destination masks have 2 dimensions, improving mask workflow reliability
• Fresca Input/Output: Corrected input and output handling for Fresca model workflows
• Reference Bug Fixes: Resolved incorrect reference bugs in Gemini node implementations
• Line Ending Standardization: Automated detection and removal of Windows line endings for cross-platform consistency

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Developer Experience

• Warning Systems: Added torch import mistake warnings to catch common configuration issues
• Template Updates: Multiple template version updates (0.1.36, 0.1.37, 0.1.39) for improved custom node development
• Documentation: Enhanced fast_fp16_accumulation documentation in portable configurations

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New Sampling Capabilities

• TCFG Node: Enhanced classifier-free guidance control for more nuanced generation control in your workflows
• ER-SDE Sampler: Migrated from VE to VP algorithm with new sampler node, providing better numerical stability for complex generation tasks
• Skip Layer Guidance (SLG): Alternative implementation for precise layer-level control during inference, perfect for advanced model steering workflows

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Enhanced Development Tools

• Custom Node Management: New --whitelist-custom-nodes argument pairs with --disable-all-custom-nodes for precise development control
• Performance Optimizations: Dual CFG node now optimizes automatically when CFG is 1.0, reducing computational overhead
• GitHub Actions Integration: Automated release webhook notifications keep developers informed of new updates

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Image Processing Improvements

• New Transform Nodes: Added ImageRotate and ImageFlip nodes for enhanced image manipulation workflows
• ImageColorToMask Fix: Corrected mask value returns for more accurate color-based masking operations
• 3D Model Support: Upload 3D models to custom subfolders for better organization in complex projects

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Guidance & Conditioning Enhancements

• PerpNeg Guider: Updated with improved pre and post-CFG handling plus performance optimizations
• Latent Conditioning Fix: Resolved issues with conditioning at index > 0 for multi-step workflows
• Denoising Steps: Added denoising step support to several samplers for cleaner outputs

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Platform Stability

• PyTorch Compatibility: Fixed contiguous memory issues with PyTorch nightly builds
• FP8 Fallback: Automatic fallback to regular operations when FP8 operations encounter exceptions
• Audio Processing: Removed deprecated torchaudio.save function dependencies with warning fixes

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Model Integration

• Moonvalley Nodes: Added native support for Moonvalley model workflows
• Scheduler Reordering: Simple scheduler now defaults first for better user experience
• Template Updates: Multiple template version updates (0.1.31-0.1.35) for improved custom node development

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Security & Safety

• Safe Loading: Added warnings when loading files unsafely, with documentation noting that checkpoint files are loaded safely by default
• File Validation: Enhanced checkpoint loading safety measures for secure workflow execution

• Expanded Model Documentation: Added comprehensive support documentation for Flux Kontext and Omnigen 2 models, making it easier for creators to integrate these powerful models into their workflows
• VAE Encoding Improvements: Removed unnecessary random noise injection during VAE encoding, resulting in more consistent and predictable outputs across workflow runs
• Memory Management Fix: Resolved a critical memory estimation bug specifically affecting Kontext model usage, preventing out-of-memory errors and improving workflow stability

• Cosmos Predict2 Support: Full implementation for both text-to-image (2B and 14B models) and image-to-video generation workflows, expanding video creation capabilities
• Enhanced Flux Compatibility: Chroma Text Encoder now works seamlessly with regular Flux models, improving text conditioning quality
• LoRA Training Integration: New native LoRA training node using weight adapter scheme, enabling direct model fine-tuning within ComfyUI workflows

• AMD GPU Enhancements: Enabled FP8 operations and PyTorch attention on GFX1201 and other compatible AMD GPUs for faster inference
• Apple Silicon Fixes: Addressed long-standing FP16 attention issues on Apple devices, improving stability for Mac users
• Flux Model Stability: Resolved black image generation issues with certain Flux models in FP16 precision

• Rectified Flow (RF) Samplers: Added SEEDS and multistep DPM++ SDE samplers with RF support, providing more sampling options for cutting-edge models
• ModelSamplingContinuousEDM: New cosmos_rflow option for enhanced sampling control with Cosmos models
• Memory Optimization: Improved memory estimation for Cosmos models with uncapped resolution support

• SQLite Database Support: Enhanced data management capabilities for custom nodes and workflow storage
• PyProject.toml Integration: Automatic web folder registration and settings configuration from pyproject files
• Frontend Flexibility: Support for semver suffixes and prerelease frontend versions for custom deployments
• Tokenizer Enhancements: Configurable min_length settings with tokenizer_data for better text processing

• Kontext Aspect Ratio Fix: Resolved widget-only limitation, now works properly in all connection modes
• SaveLora Consistency: Standardized filename format across all save nodes for better file organization
• Python Version Warnings: Added alerts for outdated Python installations to prevent compatibility issues
• WebcamCapture Fixes: Corrected IS_CHANGED signature for reliable live input workflows

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New Workflow Tools

• ImageStitch Node: Concatenate multiple images seamlessly in your workflows - perfect for creating comparison grids or composite outputs
• GetImageSize Node: Extract image dimensions with batch processing support, essential for dynamic sizing workflows
• Regex Replace Node: Advanced text manipulation capabilities for prompt engineering and string processing workflows

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Enhanced Model Compatibility

• Improved Tensor Handling: Streamlined list processing makes complex multi-model workflows more reliable
• BFL API Optimization: Refined support for Kontext [pro] and [max] models with cleaner node interfaces
• Performance Boost: Fused multiply-add operations in chroma processing for faster generation times

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Developer Experience Improvements

• Custom Node Support: Added pyproject.toml support for better custom node dependency management
• Help Menu Integration: New help system in the Node Library sidebar for faster node discovery
• API Documentation: Enhanced API nodes documentation for workflow automation

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Frontend & UI Enhancements

• Frontend Updated to v1.21.7: Multiple stability fixes and performance improvements
• Custom API Base Support: Better subpath handling for custom deployment configurations
• Security Hardening: XSS vulnerability fixes for safer workflow sharing

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Bug Fixes & Stability

• Pillow Compatibility: Updated deprecated API calls to maintain compatibility with latest image processing libraries
• ROCm Support: Improved version detection for AMD GPU users
• Template Updates: Enhanced project templates for custom node development