Change8

v0.1.702-beta

📦 unslothView on GitHub →
20 features🐛 6 fixes

Summary

Unsloth Desktop is a new open-source application for running and training AI models locally on Windows, macOS, and Linux. This release introduces features like tunable VRAM usage, faster inference, improved hardware support, and enhanced tool calling capabilities.

✨ New Features

  • Added tool calling / web search & more for all external providers.
  • UI and UX fixes - VRAM usage is now tunable.
  • 10% faster inference + reduced VRAM usage and other perf fixes.
  • Much better AMD RDNA3,4 + Strix Halo, Mac support.
  • Image diffusion, video generation fixes.
  • Can login with Codex subscription.
  • Added self-healing tool calling that repairs malformed calls.
  • Models can run Python and Bash inside sandboxed environments.
  • Added unlimited private web search, Deep Research, RAG and MCP.
  • Local models can be served through Unsloth's OpenAI-compatible API.
  • Added support for running Muse Glimmer 30B, Kimi K3, Qwen3.8, DeepSeek-V4 Flash 0731, Gemma 4.
  • Added video generation with MiniMax-H3.
  • Added ability to create images and videos with diffusion models at up to 2x faster inference.
  • Added no-code training for LLMs, diffusion models, TTS models and embedding models.
  • Training is up to 2x faster and uses up to 70% less VRAM on supported LLM workloads.
  • Added ability to export models to NVFP4, GGUF and other formats.
  • Added ability to securely deploy and access models remotely via Cloudflare HTTPS.
  • Added support for Windows, macOS, and Linux.
  • Added support for CPU and multi-GPU systems, NVIDIA and AMD GPUs, Intel hardware, and Mac.
  • Added CPU support for Chat and Data Recipes.

🐛 Bug Fixes

  • Fixed bypass permissions not working for sandboxing.
  • Many bug fixes.
  • Fixed slow Windows downloading (200x faster due to throttling).
  • Fixed Mac asking to download command line tools (uv bug).
  • Fixed AMD Strix Halo not being detected.
  • Other bug fixes.