Meta
Llama
Meta's open-weights model family, the foundation of much of the OSS AI world.
Our verdict
Llama is the most influential open-weights model family. Releasing the weights under a permissive license made it the foundation for thousands of fine-tunes and self-hosted deployments. Llama 4 narrowed the gap with frontier closed models on most benchmarks, and the 1M-token context window is genuinely useful for long-document tasks.
Using Llama means hosting it yourself or via providers like Together, Groq or Fireworks — the cost is mostly infrastructure rather than per-token. For teams with privacy or compliance requirements, this is often the only realistic path to a strong LLM.
Pros
- +Open weights, self-hostable
- +Massive ecosystem of fine-tunes
- +Strong long-context performance
- +Permissive Llama Community License
Cons
- −Requires infra and ML ops to deploy
- −Out-of-box quality below frontier closed models
- −License has acceptable-use restrictions
Capability scores
Pricing
- Free tier
- Free open weights (with license)
- Paid plan
- Free
- API pricing
- Free weights; pay your own infra
- Enterprise
- Free under Llama Community License
Best use cases
Best for
How we review: all scores on this page are set by our editorial team after hands-on testing. We do not accept payment for placement and do not earn affiliate commission from the vendor of Llama. See our editorial policy for our full methodology.
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