Enhanced UI Experience & Advanced Model SupportThis release brings significant user experience improvements and cutting-edge model support that enhance workflow creation and performance across diverse AI applications:
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
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
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
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
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
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
Core API Enhancement & Performance OptimizationsThis release introduces significant backend improvements and performance optimizations that enhance workflow execution and node development capabilities:
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
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
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
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
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
Memory Optimization & Large Model PerformanceThis release focuses on critical memory optimizations for large model workflows, particularly improving performance with WAN 2.2 models and enhancing VRAM management for high-end systems:
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
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
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
Hardware Acceleration & Audio Processing ImprovementsThis release focuses on expanding hardware support and enhancing audio processing capabilities for workflow creators:
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
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
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
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
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
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
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
Advanced Sampling & Training Infrastructure ImprovementsThis release introduces significant enhancements to sampling algorithms, training capabilities, and node functionality for AI researchers and workflow creators:
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
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
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
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
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
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
Advanced Sampling & Model Control EnhancementsThis release delivers significant improvements to sampling algorithms and model control systems, particularly benefiting advanced AI researchers and workflow creators:
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
Enhanced Development Tools
- Custom Node Management: New
--whitelist-custom-nodesargument pairs with--disable-all-custom-nodesfor 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
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
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
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
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
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
Enhanced Model Support & Workflow ReliabilityThis release brings significant improvements to model compatibility and workflow stability:
- 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
Major Model Support Additions
- 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
This release brings powerful new workflow utilities and performance optimizations for ComfyUI creators:
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
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
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
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
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