Best AI Models for Fine-Tuning
Open-weight models with healthy fine-tuning ecosystems — LoRA support, training tooling, and community recipes.
Quick answer: The best options for fine-tuning in 2026 are Llama 4 Maverick (Hyland Score 90), Llama 3.3 70B (Hyland Score 87), Mistral Small 3 (Hyland Score 85) — ranked from 10 entries using Hyland's weekly-refreshed scoring. Llama 4 Maverick leads because meta’s open multimodal MoE for builders.
Llama 4 Maverick
Meta’s open multimodal MoE for builders.
Llama 3.3 70B
The self-host sweet spot: 70B, 405B-class quality.
Mistral Small 3
Low-latency chat assistants and lightweight agentic tasks
Qwen2.5 72B
The fine-tuner’s favorite open base.
Together AI
Fine-tuning and serving open models at scale
Bedrock-native multimodal for AWS shops.
Mixtral 8x22B
The open MoE that started the wave.
Frequently asked questions
What is the best option for AI Models for Fine-Tuning?
Llama 4 Maverick currently ranks first with a Hyland Score of 90/100. Meta’s open multimodal MoE for builders. It is open source and self-hostable.
How are these rankings calculated?
Entries are ranked by the Hyland Score, a 1–100 composite computed weekly from public signals: community adoption, development velocity, documentation quality, and freshness. The full formula is published on the Hyland.ai glossary page.
How often is this list updated?
Weekly. An automated pipeline re-fetches public data (GitHub activity, release info, pricing) every week and re-computes every score, so rankings reflect the current state of each tool rather than a one-time review.
Are there free or open-source options in this list?
Yes — 7 of the 10 ranked entries offer a free tier or are fully open source, including Llama 4 Maverick, Llama 3.3 70B, Mistral Small 3.