Llama

Meta's open-weight LLM family

Open Model Free (open weights)
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What It Is

Llama is Meta's open-weight LLM family and the most widely deployed open AI model in the world. The Llama 4 generation (released 2025) introduced mixture-of-experts architecture with 17B and 109B active parameter variants. Permissive commercial license (with the acceptable use policy exclusion for 700M+ monthly active users) makes it the default choice for almost every open-weight deployment.

How It Works

Meta releases base model weights on Hugging Face and llama.meta.com. You download them and run locally via Ollama, LM Studio, vLLM, llama.cpp, or hosted services like Together and Groq. For fine-tuning, Unsloth and Axolotl are the most popular frameworks. For serving at scale, vLLM or TGI are the production options.

Pricing Breakdown

Free to download and self-host. Hosted costs via Together ($0.18-$0.88/M), Groq ($0.05-$0.79/M), and Fireworks ($0.90/M). Self-hosting costs depend on your GPU — a single A100 can serve Llama 3.1 70B at reasonable throughput for under $1/hour on spot instances.

Who Uses It

Essentially every AI company that self-hosts an open model. Goldman Sachs, Dell, IBM, Zoom, AT&T, Shopify, and thousands of others deploy Llama in production.

Strengths & Weaknesses

✓ Strengths

  • Most widely deployed open model
  • Strong community and tooling ecosystem
  • Permissive license
  • Llama 4 MoE architecture is efficient

× Weaknesses

  • Lags closed frontier models on hardest benchmarks
  • 700M+ MAU clause in license
  • Requires significant GPU for large variants

Best Use Cases

Self-hosted LLMFine-tuningResearchCost-sensitive production

Alternatives

Mistral API
European frontier models with open weights
Gemma 4
Google's Apache 2.0 open model family
Qwen
Alibaba's most-downloaded open model family
DeepSeek
Reasoning-specialized open models
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