Meta Llama
Editor Verified Open SourceOpen-weights foundation models for private inference, fine-tuning, and on-premise AI deployments.
Last Verified: February 2026 • Open Source
Free Tier Boundaries & Verification
Verified Free Allowance:
Completely free open weights under Meta Community License; free for research and commercial use up to 700M monthly active users.
Commercial Entry Price: Free weights; costs are strictly GPU compute (Ollama, vLLM, RunPod, or AWS).
Check Live Pricing Matrix Architecture & Purpose
Llama is Meta foundational open-weights model family, enabling developers and enterprises to fine-tune, quantize, and run state-of-the-art models on private infrastructure without API token limits.
Target Audience & ICP:
Machine learning engineers, enterprise security architects, and developers requiring air-gapped or private LLM inference.
Practical Use Cases
- Hosting on-premise air-gapped LLM inference for sensitive HIPAA/GDPR data.
- Domain-specific LoRA fine-tuning for specialized legal or clinical vocabulary.
- Edge device inference using quantized 8B models on Apple Silicon and workstations.
Key Capabilities & Features
- Permissive open weights for research and commercial applications under 700M MAU.
- Extensive quantization options (Ollama, vLLM, GGUF, TensorRT-LLM, EXL2).
- Strong coding, multilingual, and tool-calling benchmark performance.
Known Limitations & Operational Tradeoffs
- • Requires dedicated GPU compute hardware (NVIDIA RTX / A100 / H100) for fast inference.
- • Managing infrastructure and model scaling operations is the developer responsibility.
Side-by-Side Alternatives Comparison
Direct Market Counterparts| Specification | Meta Llama
Active
| Mistral Alternative |
|---|---|---|
| Pricing Model | Open Source | Generous Free Tier |
| Free Tier Boundaries | Completely free open weights under Meta Community License; free for research and commercial use up to 700M monthly active users. | Open weights Apache 2.0 |
| Commercial Pricing | Free weights; costs are strictly GPU compute (Ollama, vLLM, RunPod, or AWS). | API token pricing or self-host |
| Core Moat / Strength | Complete model ownership with zero API vendor lock-in or token rate limits. | European open-weights and API competitor |
| Known Limitation | Requires dedicated GPU compute hardware (NVIDIA RTX / A100 / H100) for fast inference. | Subject to provider rate limits. |
| Official Site | Visit Meta Llama | Visit Mistral |