v0.1.701-beta
📦 unslothView on GitHub →
✨ 13 features🐛 4 fixes
Summary
Unsloth Desktop is released, a new app for running and training AI models locally on various platforms and hardware. It introduces features like enhanced tool calling, support for new models, faster inference, no-code training, and remote deployment.
✨ New Features
- Introduction of Unsloth Desktop app for running and training AI models locally on Windows, macOS, and Linux.
- Up to 50% more accurate tool calling with self-healing calls and sandboxed code execution.
- Support for running models like Muse Glimmer 30B, Kimi K3, Qwen3.8, DeepSeek-V4 Flash 0731, and Gemma 4.
- Video generation with MiniMax-H3 and up to 2x faster inference for image and video diffusion models.
- Unlimited private web search, Deep Research for cited reports, and RAG capabilities.
- Export models to NVFP4, GGUF, and other formats.
- Remote access to Unsloth models via Cloudflare HTTPS.
- Support for running on CPU or multiple GPUs across NVIDIA, AMD, Intel, and Mac hardware.
- No-code model training with reduced time and VRAM usage.
- Local models served through an OpenAI-compatible API.
- Integration with OpenAI and Anthropic models as cloud providers.
- Sandboxed Python and Bash execution for models to test code and create files.
- Support for LoRAs, reference images, and ControlNet in diffusion model workflows.
🐛 Bug Fixes
- Fixed slow Windows downloading, now 200x faster due to throttling.
- Fixed Mac issue where it prompted to download command line tools (resolved uv bug).
- Fixed AMD Strix Halo not being detected.
- Other unspecified bug fixes.