Unsloth launches desktop app to run and train LLMs locally
danielhanchen · x · 2026-08-15
Unsloth has released a desktop application, Unsloth Desktop, available for Mac, Windows, and Linux. The open-source app enables users to run and train LLMs and diffusion models locally, including Qwen2.5, Kimi, DeepSeek-V3, and FLUX. It claims to offer 2x faster training speeds and 70% less VRAM usage, while integrating local coding capabilities similar to Claude Code.
More from coding & agent
- Coding agents keep opening 3 stacked PRs per chat, and merging them is a nightmare — holdenmatt · 2026-10-16
- Google-led paper uses sequential auctions to organize decentralized LLM agent workflows — _onionesque · 2026-10-16
- Since OpenAI's math release, GitHub contributors keep driving down the integer-multiplication kappa — xennygrimmato_ · 2026-10-16
- Pattern MCP makes coding agents check existing components before writing new code — DonR954 · 2026-10-16
- Zero-keyframe procedural spider walks walls and ceilings using pure raycasts — yshan2u · 2026-10-16
- OpenCode v1.19.2 keeps 1.x installs off the 2.x update path — opencode-agent[bot] · 2026-10-16