Back to directory

Unsloth

Unsloth is a desktop application and toolkit for running and fine-tuning large language and diffusion models locally, supporting formats such as GGUF and MLX across NVIDIA, AMD and Intel GPUs as well as CPUs.

Unsloth

It runs and trains language, image and audio models, connects local models to coding agents such as Claude Code and Codex with tool calling over MCP, and adds private web search, deep research and a rolling-context RAG mode. Fine-tuning is reported to run twice as fast with about 70 percent less VRAM than standard methods, with support for LoRA, QLoRA, full fine-tuning, pretraining and reinforcement-learning methods including GRPO and DPO, plus export to formats such as GGUF and NVFP4.

A one-command "Unsloth Start" connects Claude Code, Codex and other agents to a chosen local model, and a served OpenAI-compatible API lets a locally hosted model be reached remotely over HTTPS or from another application.

Available as a desktop app, a web UI called Unsloth Studio, or a code-based core library.

More in Models

See all 405
  • mini-AGI

    github.com

    A continual learning language model that trains from scratch on a single 8 GB VRAM GPU, assembling its own architecture and adapting its size to the hardware and data available rather than shipping as a fixed pretrained model.

  • An open-source contrastive-embedding pipeline that maps technical CVE vulnerability descriptions to formal cybersecurity compliance controls in NIST SP 800-53 and CMMC, published with its model generation, fine-tuning and evaluation code.

  • peekaboolean

    github.com

    A small vision-language model, fine-tuned with LoRA on a 500-million-parameter backbone, that answers typed multiple-choice, ordinal-score and yes/no questions about an image with calibrated probabilities, in about 400 milliseconds on a laptop.