v3.1.0

• General:
  • Migrated NNCFGraph from nx.DiGraph to nx.MultiDiGraph to support models with parallel/multi-edges, enabling correct quantization of models with complex graph structures such as YOLO26 and models like a = conv(x); return a * a (#3843).
• Features:
  • (OpenVINO) Added NVFP4 (f4e2m1) compression data type in Weight Compression. NVFP4 uses a constant group size of 16 with scales compressed to f8e4m3 using a second-degree scale (#3967).
  • (OpenVINO) Added backup_mode parameter for FP compression formats (MXFP4, MXFP8, FP4, FP8), allowing first/last layers to be compressed with a backup FP format instead of INT8 (#3886).
  • (OpenVINO) RoPe ignored pattern is updated to handle operations without a preceding transpose like in the Phi-3.5-MoE-instruct model (#3989).
  • (PyTorch) Added TopKMetatype support for TorchFX backend, enabling correct graph building for models with TopK operations such as YOLO26 (#3944).
  • (PyTorch) Migrated to use torchao instead of deprecated torch.ao (#3854).
• Fixes:
  • (OpenVINO) Fixed scale estimation for Adaptive Codebook weight compression (#3888).
  • (ONNX) Fixed nncf.errors.ValidationError: There is no tensor with the name error (#3988).
• Improvements:
  • (PyTorch) Added lazy import for nncf.torch module to reduce startup import time (#3862).
• Tutorials:
  • Post-Training Optimization of Gemma 4 Model
  • Post-Training Optimization of Code-specialized LLMs
  • Post-Training Optimization of Vision-Language Models (VLMs)
  • Post-Training Optimization of MiniCPM-o 4.5 Multimodal Model
  • Post-Training Optimization of PaddleOCR-VL/PaddleOCR-VL-1.5 Models
  • Post-Training Optimization of RAG pipeline
• Requirements:
  • Updated to openvino 2026.1.0 (#4005).
  • Updated to torch 2.10.0 (#3852).
  • Updated to onnx 1.20.1 (#3966).
  • Updated to onnxruntime 1.24.3 (#3977).
  • Moved pandas to optional dependency (#3970).
  • Removed unused pillow dependency (#3929).