What is Llama 4?

Llama 4 is Meta's latest open-source large language model family, featuring a Mixture of Experts (MoE) architecture that achieves frontier-level performance while remaining open-weights. It's the most capable open model available for self-hosting.

Our Review

Llama 4 closes much of the gap between open and closed models. For teams with GPU infrastructure willing to manage self-hosting, the economics are compelling: no per-token cost and no data leaving your infrastructure. The MoE architecture makes it more accessible to run than same-parameter dense models.

Key Use Cases

Self-hosted LLM for privacy-sensitive applications
Fine-tuning for domain-specific tasks
Cost-effective high-volume inference
Research and experimentation

Pros & Cons

✅ Pros

•Open weights — fully self-hostable
•MoE architecture: frontier quality at lower compute
•No API cost if self-hosted
•Strong multilingual performance
•Large community of fine-tunes and integrations

❌ Cons

•Self-hosting requires significant GPU resources
•Commercial use restrictions in license
•Slightly behind GPT-4o/Claude on edge cases

Pricing

Free (open weights); hosted APIs from ~$0.10-0.40/M tokens

Who Should Use Llama 4?

Llama 4 is best for self-hosted llm for privacy-sensitive applications, fine-tuning for domain-specific tasks.

Llama 4