Axolotl
Top pickFine-tune most open models from one YAML file. The community default.
93
sovereigntyAxolotl wraps the messy parts of fine-tuning — dataset formatting, tokenization, LoRA and QLoRA configuration, multi-GPU sharding, gradient checkpointing — behind a single YAML config. It supports most mainstream open model families and both adapter and full fine-tunes, and it has become the de facto shared vocabulary of the open fine-tuning community, which means the config you need has usually already been written by someone else. The output is adapter weights on your disk, which you own outright.
OPEN SOURCEApache-2.0SELF-HOSTLOCAL-FIRST
LicenseApache-2.0
PricingFree. You rent or own the GPU; a small LoRA can cost a few dollars of rented time.
Open sourceYes
Self-hostableYes
Local-first dataYes
What it does well
- +One YAML file covers dataset, method and hardware configuration
- +Broad model-family support, LoRA/QLoRA and full fine-tuning
- +Large community — working configs are usually already published
- +Produces weights you own and can run anywhere
Where it falls short
- −You supply the GPU and the environment
- −The config surface is wide enough to be its own learning curve
- −Fast-moving project; pinning versions matters for reproducibility
Axolotl as an alternative to
Where Axolotl shows up in our comparisons, and how it ranked.
Axolotl head-to-head
Straight comparisons against the tools people weigh it against.