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Changelog
Track ComfyUI’s latest features, improvements, and bug fixes
Enhanced Model Support & Qwen Image ControlNet IntegrationThis release significantly expands ControlNet capabilities and improves model compatibility, making ComfyUI workflows more versatile and reliable:Qwen ControlNet Ecosystem
- Diffsynth ControlNet Support: Added support for Qwen Diffsynth ControlNets with Canny and depth conditioning, enabling precise edge and depth-based image control
- InstantX Qwen ControlNet: Integrated InstantX Qwen ControlNet for expanded creative control options
- Inpaint ControlNet/Model Patches: Enhanced inpainting capabilities with dedicated Diffsynth inpaint ControlNet support
- V3 Architecture Migration: String nodes, Google Veo API, and Ideogram API nodes upgraded to V3 architecture for better performance and consistency
- Enhanced API Nodes: OpenAI Chat node renamed to “OpenAI ChatGPT” for clarity, Gemini Chat node now includes copy button functionality
- Improved Usability: API nodes now provide better user experience with clearer labeling and enhanced interaction features
- LTXV Noise Mask Fix: Resolved key frame noise mask dimension issues when real noise masks exist, ensuring stable video workflow execution
- 3D Latent Conditioning Control: Fixed conditioning masks on 3D latents, enabling proper depth-aware conditioning control in advanced workflows
- Invalid Filename Handling: Improved workflow save functionality with proper handling of invalid filenames, preventing save failures
- EasyCache & LazyCache: Implemented advanced caching systems for improved workflow execution performance
- Python 3.13 Support: Full compatibility with Python 3.13, keeping ComfyUI current with latest Python developments
- Frontend Update: Updated to v1.25.10 with improved navigation and user interface enhancements
- Elementwise Fusions: Added performance optimizations through elementwise operations fusion
- Navigation Mode Rollback: Rolled back navigation default to traditional legacy mode, avoiding user experience issues caused by default enabled standard navigation mode. Users can still enable standard navigation mode in settings
Model Support
- Qwen-Image-Edit Model: Native support for Qwen-Image-Edit
- FluxKontextMultiReferenceLatentMethod Node: Multi-reference input node for Flux workflows
- WAN 2.2 Fun Camera Model Support: Support for video generation through camera control
- Template Updates: Upgraded to version 0.1.62, added Wan2.2 Fun Camera and Qwen Image Edit templates
- Context Windows Support: Enhanced sampling code to support longer sequence generation tasks
- SDPA Backend Optimization: Improved Scaled Dot Product Attention backend settings for better performance
- Audio Recording Node: New native audio recording node, now you can record audio directly in ComfyUI
- Audio Video Integration: Complete audio-video dependency integration
- GPT-5 Series Models: Support for the latest GPT-5 models
- Kling V2-1 and V2-1-Master: Updated video generation model functionality
- Minimax Hailuo Video Node: New video generation node
- Vidu Video Node: Vidu API node support
- Google Model Updates: Added new Google Gemini models
- OpenAI API Fix: Fixed MIME type errors in OpenAI API node input images
- Intel GPU Compatibility: Fixed Intel integrated GPU compatibility issues
- PyTorch Compatibility: Enhanced compatibility with older PyTorch versions
- Torch Compile Optimization: Improved torch compile behavior
- Memory Management: Optimized installation size and memory efficiency
- Subgraph Support: Subgraph functionality support
- Shortcut Panel: Added bottom shortcut panel
- UI Layout Modifications: Modified terminal entry layout, added template, log panel and other entries
- Standard Canvas Mode: Added standard canvas mode, can be switched in
Lite Graph>Canvas>Canvas Navigation Mode - Mini Map: Added workflow mini map
- Tab Preview: Added workflow tab preview
- Top Tab Menu Layout Adjustments
Model Integration & Performance EnhancementsThis release expands ComfyUI’s model ecosystem with enhanced Qwen support, async API capabilities, and stability improvements for complex workflows:Qwen Model Ecosystem
- Qwen Image Model Support: Improved integration including proper LoRA loading and model merging capabilities for sophisticated vision workflows
- Qwen Model Merging Node: New dedicated node for merging Qwen image models, allowing creators to combine different model strengths
- SimpleTuner Lycoris LoRA Support: Extended compatibility with SimpleTuner-trained Lycoris LoRAs for Qwen-Image models
- Async API Nodes: Introduction of asynchronous API nodes, enabling non-blocking workflow execution for better performance
- Memory Handling: Enhanced RepeatLatentBatch node now properly handles multi-dimensional latents, fixing workflow interruptions
- WAN 2.2 Fun Control Support: Added support for WAN 2.2 fun control features, expanding creative control for video workflows
- AMD GPU Improvements: Enhanced AMD Radeon support with improved FP16 accuracy handling and performance optimization
- RDNA3 Architecture Fixes: Resolved issues with gfx1201 GPUs when using Flux models with PyTorch attention
- Updated PyTorch Support: Bumped CUDA and ROCM PyTorch versions with testing on Python 3.13 and CUDA 12.9
- Cleaner Logging: Feature flags now only display in verbose mode, reducing console noise
- Audio Processing Safety: Enhanced torchaudio import safety checks prevent crashes when audio dependencies are unavailable
- Kling API Improvements: Fixed image type parameter handling in Kling Image API nodes
- Async Workflow Execution: New async API capabilities enable more responsive workflows when integrating external services
- Model Flexibility: Expanded Qwen support allows for more diverse vision-language workflows with improved LoRA compatibility
- Hardware Utilization: AMD GPU optimizations and updated PyTorch support improve performance across hardware configurations
- Batch Processing: Fixed RepeatLatentBatch ensures reliable operation with complex multi-dimensional data structures
- Video Control: WAN 2.2 fun control features provide advanced creative control for video generation workflows
UI Experience & Model SupportThis release brings user experience improvements and model support that enhance workflow creation and performance:User Interface Enhancements
- Recently Used Items API: New API for tracking recently used items in the interface, streamlining workflow creation
- Workflow Navigation: Enhanced user experience with better organization of commonly accessed elements
- Qwen Vision Model Support: Initial support for Qwen image models with configuration options
- Image Processing: Enhanced Qwen model integration allows for more versatile image analysis and generation workflows
- Veo3 Video Generation: Added Veo3 video generation node with integrated audio support
- Audio-Visual Synthesis: Capability combining video and audio generation in a single node
- Memory Management: Optimized conditional VRAM usage through improved casting and device transfer operations
- Device Consistency: Fixes ensuring all conditioning data and context remain on correct devices
- ControlNet Stability: Resolved ControlNet compatibility issues, restoring functionality for image control workflows
- Error Handling: Added warnings and crash prevention when conditioning devices don’t match
- Template Updates: Multiple template version updates (0.1.47, 0.1.48, 0.1.51) maintaining compatibility
- 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
- Video Production: Veo3 integration transforms ComfyUI into a comprehensive multimedia creation platform
- Reliability: Memory optimizations and device management fixes ensure stable operation with complex workflows
- Performance: Optimized VRAM usage allows for more ambitious projects on systems with limited resources
API Enhancement & Performance OptimizationsThis release introduces backend improvements and performance optimizations that enhance workflow execution and node development:ComfyAPI Core Framework
- ComfyAPI Core v0.0.2: Update to the core API framework, providing improved stability and extensibility
- Partial Execution Support: New backend support for partial workflow execution, enabling efficient processing of multi-stage workflows
- WAN Camera Memory Optimization: Enhanced memory management for WAN-based camera workflows, reducing VRAM usage
- WanFirstLastFrameToVideo Fix: Resolved issue preventing proper video generation when clip vision components are not available
- VAE Nonlinearity Enhancement: Replaced manual activation functions with optimized torch.silu in VAE operations
- WAN VAE Optimizations: Fine-tuning optimizations for WAN VAE operations, improving processing speed and memory efficiency
- V3 Node Schema Definition: Implementation of next-generation node schema system
- Template Updates: Multiple template version updates (0.1.44, 0.1.45) ensuring compatibility
- Video Workflows: Improved stability and performance for video generation pipelines
- Memory Management: Optimized memory usage patterns enable more complex workflows on systems with limited VRAM
- API Reliability: Core API enhancements provide more stable foundation for custom node development
- Execution Flexibility: New partial execution capabilities allow for more efficient debugging and development
Memory Optimization & Large Model PerformanceThis release focuses on memory optimizations for large model workflows, improving performance with WAN 2.2 models and VRAM management:WAN 2.2 Model Optimizations
- Reduced Memory Footprint: Eliminated unnecessary memory clones in WAN 2.2 VAE operations, reducing memory usage
- 5B I2V Model Support: Memory optimization for WAN 2.2 5B image-to-video models, making these models more accessible
- Windows Large Card Support: Added reserved VRAM allocation for high-end graphics cards on Windows
- Memory Allocation: Improved memory management for users working with multiple large models simultaneously
- VAE Processing: WAN 2.2 VAE operations now run more efficiently with reduced memory overhead
- Large Model Inference: Enhanced stability when working with billion-parameter models
- Batch Processing: Memory optimizations enable better handling of batch operations with large models
Hardware Acceleration & Audio ProcessingThis release expands hardware support and enhances audio processing capabilities:Audio Processing Enhancements
- PyAV Audio Backend: Replaced torchaudio.load with PyAV for more reliable audio processing in video workflows
- Audio Integration: Enhanced audio handling for multimedia generation workflows
- Iluvatar CoreX Support: Added native support for Iluvatar CoreX accelerators
- Intel XPU Optimization: XPU support improvements including async offload capabilities
- AMD ROCm Enhancements: Enabled PyTorch attention by default for gfx1201 on Torch 2.8
- CUDA Memory Management: Fixed CUDA malloc to only activate on CUDA-enabled PyTorch installations
- Euler CFG++ Enhancement: Separated denoised and noise estimation processes in Euler CFG++ sampler
- WAN Model Support: Added support for WAN (Wavelet-based Attention Network) models
- Training Nodes: Added algorithm support, gradient accumulation, and optional gradient checkpointing
- Training Flexibility: Better memory management and performance optimization for custom model training
- Moonvalley V2V Node: Added Moonvalley Marey V2V node with enhanced input validation
- Negative Prompt Updates: Improved negative prompt handling for Moonvalley nodes
- History API Enhancement: Added map_function parameter to get_history API
- Frontend Version Tracking: Added required_frontend_version parameter in /system_stats API response
- Device Information: Enhanced XPU device name printing for better hardware identification
- Template Updates: Multiple template updates (0.1.40, 0.1.41) ensuring compatibility
- Documentation Updates: Enhanced README with examples and updated model integration guides
- Line Ending Fixes: Improved cross-platform compatibility by standardizing line endings
- Code Cleanup: Removed deprecated code and optimized components
Sampling & Training ImprovementsThis release introduces enhancements to sampling algorithms, training capabilities, and node functionality:Sampling & Generation Features
- SA-Solver Sampler: New reconstructed SA-Solver sampling algorithm providing enhanced numerical stability
- Experimental CFGNorm Node: Classifier-free guidance normalization for improved control over generation quality
- Nested Dual CFG Support: Added nested style configuration to DualCFGGuider node
- SamplingPercentToSigma Node: New utility node for precise sigma calculation from sampling percentages
- Multi Image-Caption Dataset Support: LoRA training node now handles multiple image-caption datasets simultaneously
- Training Loop Implementation: Optimized training algorithms for improved convergence and stability
- Error Detection: Added model detection error hints for LoRA operations
- Async Node Support: Full support for asynchronous node functions with earlier execution optimization
- Chroma Flexibility: Un-hardcoded patch_size parameter in Chroma
- LTXV VAE Decoder: Switched to improved default padding mode for better image quality
- Safetensors Memory Management: Added workaround for mmap issues
- Custom Prompt IDs: API now allows specifying prompt IDs for better workflow tracking
- Kling API Optimization: Increased polling timeout to prevent user timeouts
- History Token Cleanup: Removed sensitive tokens from history items
- Python 3.9 Compatibility: Fixed compatibility issues ensuring broader platform support
- MaskComposite Fixes: Resolved errors when destination masks have 2 dimensions
- 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
- 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
Sampling & Model Control EnhancementsThis release delivers improvements to sampling algorithms and model control systems:Sampling Capabilities
- TCFG Node: Enhanced classifier-free guidance control for more nuanced generation control
- ER-SDE Sampler: Migrated from VE to VP algorithm with new sampler node
- Skip Layer Guidance (SLG): Implementation for precise layer-level control during inference
- Custom Node Management: New
--whitelist-custom-nodesargument pairs with--disable-all-custom-nodes - Performance Optimizations: Dual CFG node now optimizes automatically when CFG is 1.0
- GitHub Actions Integration: Automated release webhook notifications
- Transform Nodes: Added ImageRotate and ImageFlip nodes for enhanced image manipulation
- ImageColorToMask Fix: Corrected mask value returns for more accurate color-based masking
- 3D Model Support: Upload 3D models to custom subfolders for better organization
- PerpNeg Guider: Updated with improved pre and post-CFG handling
- Latent Conditioning Fix: Resolved issues with conditioning at index > 0 for multi-step workflows
- Denoising Steps: Added denoising step support to several samplers
- 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
- Moonvalley Nodes: Added native support for Moonvalley model workflows
- Scheduler Reordering: Simple scheduler now defaults first
- Template Updates: Multiple template version updates (0.1.31-0.1.35)
- Safe Loading: Added warnings when loading files unsafely
- File Validation: Enhanced checkpoint loading safety measures
Model Support & Workflow ReliabilityThis release brings improvements to model compatibility and workflow stability:Expanded Model Documentation: Added support documentation for Flux Kontext and Omnigen 2 models
VAE Encoding Improvements: Removed unnecessary random noise injection during VAE encoding
Memory Management Fix: Resolved a memory estimation bug affecting Kontext model usage
Model Support Additions
- Cosmos Predict2 Support: Implementation for text-to-image (2B and 14B models) and image-to-video generation workflows
- Flux Compatibility: Chroma Text Encoder now works with regular Flux models
- LoRA Training Integration: New native LoRA training node using weight adapter scheme
- AMD GPU Enhancements: Enabled FP8 operations and PyTorch attention on AMD GPUs
- Apple Silicon Fixes: Addressed FP16 attention issues on Apple devices
- Flux Model Stability: Resolved black image generation issues with certain Flux models
- Rectified Flow Samplers: Added SEEDS and multistep DPM++ SDE samplers with RF support
- ModelSamplingContinuousEDM: New cosmos_rflow option for enhanced sampling control
- Memory Optimization: Improved memory estimation for Cosmos models
- SQLite Database Support: Enhanced data management capabilities for custom nodes
- PyProject.toml Integration: Automatic web folder registration from pyproject files
- Frontend Flexibility: Support for semver suffixes and prerelease frontend versions
- Tokenizer Enhancements: Configurable min_length settings with tokenizer_data
- Kontext Aspect Ratio Fix: Resolved widget-only limitation
- SaveLora Consistency: Standardized filename format across all save nodes
- Python Version Warnings: Added alerts for outdated Python installations
- WebcamCapture Fixes: Corrected IS_CHANGED signature
Workflow Tools & Performance OptimizationsThis release brings new workflow utilities and performance optimizations:Workflow Tools
- ImageStitch Node: Concatenate multiple images seamlessly in your workflows
- GetImageSize Node: Extract image dimensions with batch processing support
- Regex Replace Node: Advanced text manipulation capabilities for workflows
- Tensor Handling: Streamlined list processing makes multi-model workflows more reliable
- BFL API Optimization: Refined support for Kontext models with cleaner node interfaces
- Performance Boost: Fused multiply-add operations in chroma processing for faster generation
- Custom Node Support: Added pyproject.toml support for better dependency management
- Help Menu Integration: New help system in the Node Library sidebar
- API Documentation: Enhanced API nodes documentation
- Frontend Updated to v1.21.7: Stability fixes and performance improvements
- Custom API Base Support: Better subpath handling for custom deployment configurations
- Security Hardening: XSS vulnerability fixes
- Pillow Compatibility: Updated deprecated API calls
- ROCm Support: Improved version detection for AMD GPU users
- Template Updates: Enhanced project templates for custom node development