What platform is best for fine-tuning LLMs?
Asked "What platform is best for fine-tuning LLMs?", ChatGPT, Copilot, Gemini, Google AI Mode and Perplexity named 36 distinct tools across 15 answers on September 7, 2026, and 23 of them in two or more answers, and all 5 engines agreed on Axolotl, the only tool every engine named.
23 of 36 names confirmed · named in 2 or more of 15 answers · asked September 7, 2026 · 5 engines
The best platform for fine-tuning LLMs depends on your technical expertise, infrastructure budget, and whether you want a managed API or full control over the hardware and code. Hugging Face ecosystem is widely regarded as the best general-purpose starting platform for fine-tuning LLMs, with strong support for PEFT, RLHF variants, and easy deployment. Other strong options include Baseten, Predibase, Axolotl, and LLaMA-Factory, depending on your needs.
- 1Together AInamed in 10 of 15 answers
- 2Hugging Facenamed in 9 of 15 answers
- 3Axolotlnamed in 9 of 15 answers
- 4Predibasenamed in 9 of 15 answers
- 5Unslothnamed in 8 of 15 answers
- 6OpenPipenamed in 6 of 15 answers
- 7OpenAInamed in 4 of 15 answers
- 8Weights & Biasesnamed in 4 of 15 answers
- 9RunPodnamed in 3 of 15 answers
- 10Amazon SageMakernamed in 3 of 15 answers
- 11Basetennamed in 3 of 15 answers
- 12Google Vertex AInamed in 3 of 15 answers
- 13LLaMA-Factorynamed in 3 of 15 answers
- 14Databricksnamed in 3 of 15 answers
- 15Google Cloud Vertex AInamed in 3 of 15 answers
- 16Torchtunenamed in 2 of 15 answers
- 17LitGPTnamed in 2 of 15 answers
- 18Hugging Face Transformersnamed in 2 of 15 answers
- 19OpenAI APInamed in 2 of 15 answers
- 20LangChainnamed in 2 of 15 answers
- 21PyTorch Lightningnamed in 2 of 15 answers
- 22TensorFlow Extendednamed in 2 of 15 answers
- 23Ertas AInamed in 2 of 15 answers
- 24AWS Bedrocknamed in 1 of 15 answersone answer
- 25AWSnamed in 1 of 15 answersone answer
The full measurement
- The position each of the 5 engines gave all 36 names.
- How many of the 15 answers named each of them.
- 168 sampled observations behind this ranking, and where the engines disagree.
- Fan-out — the query each engine actually searched.
- Every citation, and the sources nobody cited.