Llama 4 Maverick
Meta Llama 4 Maverick model entry for multimodal open-weight workflows, multilingual text, code generation, and local or hosted deployment evaluation.
Llama 4 Maverick is Meta’s flagship open-weight model, featuring a 400-billion parameter Mixture-of-Experts architecture with 17 billion active parameters per inference step. It supports multimodal inputs (text and images), offers a 1,000,000-token context window, and is released under a permissive open-weight license for self-hosted and commercial deployment.
As an open-weight model, Llama 4 Maverick can be deployed through multiple serving frameworks including Transformers, vLLM, SGLang, and TensorRT-LLM. It supports both local and cloud-based deployment, making it accessible to teams that need model governance, custom fine-tuning, or air-gapped operation. The model handles coding, document analysis, multilingual tasks, and cost-sensitive generation workloads.
Llama 4 Maverick’s initial benchmark results faced controversy regarding methodology, and independent evaluations suggest it performs competitively but not at the frontier level of GPT-5.5, Claude Opus 4.7, or Gemini 3.1 Pro for complex reasoning tasks. Teams should evaluate Llama 4 Maverick on their specific workloads rather than relying solely on published benchmarks, particularly for technical coding and analysis tasks where the model’s Mixture-of-Experts architecture offers efficiency advantages over dense models.
| Provider | Meta |
|---|---|
| Context Window | 1000000 |
| Pricing | Open-weight deployment cost depends on hosting, hardware, and inference provider; verify the selected provider before production use. |
| API Style | Open-weight model card and Llama tooling |
| SDK | Transformers, llama-models, Llama Stack |
| MCP | Works through local, hosted, or Llama Stack adapters that expose tool or Agent interfaces. |
| Agent | Useful for open-weight Agent workflows when serving capacity and prompt format are validated. |
| RAG | Suitable for RAG and document workflows where open-weight deployment and multimodal input support are part of the selection criteria. |
| Source Freshness | recently_verified |
| Version Status | current |
| Version Boundary | Current ContextHub entry for Llama 4 Maverick; Scout and other Llama variants should use separate model slugs. |
Key Facts
- Meta's Llama 4 Maverick model card lists a Mixture-of-Experts architecture.
- The model card lists multilingual text and image inputs with multilingual text and code outputs.
- The meta-llama GitHub tooling includes Llama 4 model entries and inference guidance.
Best For
Not Ideal For
Capability Matrix
| Capability | Status |
|---|---|
| Multimodal | Supported |
| Coding | Supported |
| Multilingual | Supported |
| Open Weight | Supported |
SEO
| SEO Title | Llama 4 Maverick API, Pricing, SDK, MCP & Agent Compatibility |
|---|---|
| Description | Llama 4 Maverick by Meta: Meta Llama 4 Maverick model entry for multimodal open-weight workflows, multilingual text, code generation, and local or hosted deployment evaluation. |
| Canonical | /model/llama-4-maverick |
| Updated | 2026-05-18 |
Related Pages
- AI Model Directory
- Compatibility Matrix
- FAQ Index
- Best AI Models for Code Review
- Best AI Models for Coding
- Best AI Models for Cost-Sensitive Generation
- Best AI Models for Document Workflows
- Best AI Models for Low-Latency Generation
- Best AI Models for Multimodal Workflows
- Best AI Models for Open-Weight Deployment
- Llama 4 Maverick vs gpt-oss-120b
- Llama 4 Maverick vs Gemini 3.1 Pro
- Llama 4 Maverick vs Qwen3.6
Compare
| Comparison | Compared With |
|---|---|
| Llama 4 Maverick vs gpt-oss-120b | gpt-oss-120b |
| Llama 4 Maverick vs Gemini 3.1 Pro | Gemini 3.1 Pro |
| Llama 4 Maverick vs Qwen3.6 | Qwen3.6 |
Compatibility Facts
| Layer | Target | Status | Evidence | Updated |
|---|---|---|---|---|
| framework | Transformers | supported | Meta's model card includes Transformers usage guidance and the meta-llama GitHub repository provides Llama 4 tooling notes. | 2026-05-18 |
FAQ
| What is Llama 4 Maverick? | Llama 4 Maverick is a Meta open-weight multimodal model with a model card context length of one million tokens. Verify license, hosting path, and inference requirements before production use. |
|---|---|
| What is Llama 4 Maverick best for? | Llama 4 Maverick is best for multimodal workflow, document workflow, coding, cost-sensitive generation. |
| How should Llama 4 Maverick be verified before production use? | Check current pricing, availability, limits, and API behavior against the listed official and GitHub sources. This entry was updated on 2026-05-18. |
| How should open-weight AI models be selected for deployment? | Open-weight model selection should compare model capability, license terms, hardware needs, serving-stack maturity, prompt format requirements, and compatibility with the Agent or RAG runtime. |
| How should open-weight models be compared with hosted API models? | Compare open-weight models by checkpoint, license, serving framework, hardware cost, context behavior, and adapter compatibility instead of treating them as direct one-to-one hosted API replacements. |
Relationship Facts
| Source | Type | Target | Confidence |
|---|---|---|---|
| llama-4-maverick | best_for | multimodal workflow | 0.8 |
| llama-4-maverick | works_with | Transformers | 0.78 |
Sources
| Name | Type | Citation | Last Verified |
|---|---|---|---|
| Meta Llama 4 Maverick model card | docs | Meta-published model card for Llama 4 Maverick architecture, modality, context, and release details. | 2026-05-18 |
| Meta Llama models GitHub repository | github | GitHub repository for Llama model metadata, tooling, license links, and inference guidance. | 2026-05-18 |
External Resources
- Meta Llama 4 Maverick model card — Meta-published model card for Llama 4 Maverick architecture, modality, context, and release details.
- Meta Llama models GitHub repository — GitHub repository for Llama model metadata, tooling, license links, and inference guidance.