Meta Llama 4 API

Meta Llama 4 is Meta's latest generation of open-source large language models, featuring Mixture-of-Experts (MoE) architecture for efficiency, native multimodal support, and strong reasoning capabilities. Available to run self-hosted via Ollama/vLLM or via cloud providers (AWS Bedrock, Google Cloud, Together AI, Fireworks). No per-token API cost when self-hosted.

Evaluated Mar 10, 2026 (3d ago) vcurrent
Homepage ↗ Repo ↗ AI & Machine Learning meta llama llama-4 open-source self-hostable multimodal mixture-of-experts
⚙ Agent Friendliness
44
/ 100
Can an agent use this?
🔒 Security
75
/ 100
Is it safe for agents?
⚡ Reliability
N/A
Not evaluated
Does it work consistently?

Score Breakdown

⚙ Agent Friendliness

MCP Quality
0
Documentation
78
Error Messages
72
Auth Simplicity
--
Rate Limits
--

🔒 Security

TLS Enforcement
--
Auth Strength
--
Scope Granularity
--
Dep. Hygiene
--
Secret Handling
--

⚡ Reliability

Uptime/SLA
--
Version Stability
--
Breaking Changes
--
Error Recovery
--
AF Security Reliability

Best When

Privacy, cost at scale, or customization are the priority. Self-hosted inference on Llama 4 can be 10-50x cheaper than OpenAI at high volume.

Avoid When

You need highest-quality outputs on hard reasoning tasks, or don't have the infrastructure for self-hosted inference.

Use Cases

  • Self-hosted agents with no per-token costs — run inference locally or on own cloud
  • Privacy-sensitive deployments where data must not leave your infrastructure
  • High-volume agent workloads where per-token costs are prohibitive
  • Research and fine-tuning — open weights allow model customization
  • Embedding in products that need model capabilities without API dependencies

Not For

  • Teams without GPU infrastructure for self-hosting (cloud inference adds back per-token cost)
  • Applications requiring frontier reasoning (Llama 4 is competitive but not yet GPT-4o level on all tasks)
  • Quick prototyping where managed API convenience matters

Interface

REST API
Yes
GraphQL
No
gRPC
No
MCP Server
No
SDK
Yes
Webhooks
No

Authentication

Methods: api_key none
OAuth: No Scopes: No

Authentication depends on deployment: self-hosted (no auth required), via cloud providers (provider's auth model), via Meta API (coming). Access to weights requires Meta license agreement.

Pricing

Model: open_source
Free tier: Yes
Requires CC: No

Open weights model. Self-hosting is free beyond compute. Commercial use allowed with Meta's commercial license.

Agent Metadata

Pagination
none
Idempotent
No
Retry Guidance
Not documented

Known Gotchas

  • Self-hosting requires significant GPU infrastructure — minimum A100 for 70B model
  • No official API endpoint from Meta — must use self-hosted serving or third-party cloud
  • Instruction following is strong but may differ from OpenAI/Claude fine-tuning
  • Weights download is large (70B model: ~140GB) — initial setup is time-consuming
  • No formal SLA — reliability depends on your infrastructure or chosen cloud provider
  • Function calling support varies by serving layer — not all serve Llama with tool calling
  • License requires attribution and has commercial use restrictions for large companies

Alternatives

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Scores are editorial opinions as of 2026-03-10.

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