Axolotl

Fine-tune open LLMs 2x faster with far less VRAM. Open source.

An open-source (Apache-2.0) framework for fine-tuning and running open-weight models with custom CUDA kernels — roughly 2x faster training and large VRAM savings, so 7B–13B models fit on a single consumer GPU. Free tier runs on Colab/Kaggle or locally; Pro and Enterprise tiers add multi-GPU and multi-node speedups. Exports to GGUF/Safetensors for llama.cpp, vLLM, and Ollama.

Replace frontier-model spend with a fine-tuned small model.

Captures your production OpenAI / Anthropic calls, builds a dataset, fine-tunes a small open-weights model on your traffic, then serves the swap behind your existing SDK. The pitch: 10x cost reduction at parity.