This is a large performance and reliability + bug fix release for Unsloth
Highlights
- 1.2-1.7x faster diffusion. AMD 20% perf boost vs ROCM via Vulkan
- 2x faster updating, remove SAC + AV false positives for Windows
- Blender MCP, detect Hermes, AMD gibberish fixed (reported to AMD)
- Over 250+ bug fixes, 60% smaller binaries and performance improvements
- Strix iGPU BIOS popup - 3x faster inference if more VRAM for iGPU
- Updated PyTorch to 2.11 from 2.10 - 2.14 will be soon. MLX improvements
- Default to gpt-6-astra for Codex logins and improve OpenAI API processing
- MLX fixed when self healing / updating, causing slowdowns for inf + training
- Fix AppImage being very laggy. Fixed RAG upload issues stuck at 28% and API issues
- New Docker image published at https://hub.docker.com/r/unsloth/unsloth for Studio and notebooks
Performance Boosts
- Diffusion is 1.2x to 1.7x faster for INT8 / FP8 pathways - all models accelerated.
- 23% faster prompt processing and 8% faster generation on Strix Halo.
- Gated-delta models now train up to 25% faster on Apple Silicon.
- Quantized MLX KV caches use up to 74% less prompt memory than before.
AMD + Windows
- Strix Halo and Strix Point now default to Vulkan for faster inference.
- AMD iGPUs without ROCm now use Vulkan instead of CPU on Linux.
- Windows llama.cpp binaries are now signed to reduce Smart App Control blocks.
- Windows now clearly explains when code integrity blocks model loading.
- Reinstalling Unsloth on Windows keeps your supported PyTorch version.
MLX + Apple Silicon
- Fresh Mac installs keep MLX training and exports working.
- Fine-tune with DoRA and more DPO loss types on Apple Silicon.
- Batched MLX generation now streams and samples each chat independently.
- More multimodal models can be fine-tuned using text-only datasets.
Studio + API
- RAG and document uploads are faster, show clearer progress and no longer appear stuck.
- Studio menus, Find and Settings now open more smoothly.
- GPT-6 Astra is available for Codex logins with Low through Max reasoning controls.
- Improved OpenAI-compatible API streaming, audio input and model loading.
- AppImage builds are more reliable with a pinned release toolchain.
Installs + Docker
- PyTorch 2.11 is now the default across supported installers.
- New NVIDIA Docker images for training and Studio, from Turing to Blackwell.
- Native AMD64 and ARM64 images are available from Docker Hub.
- The Unsloth Python package is now >60% smaller.
Docker: https://hub.docker.com/r/unsloth/unsloth
