Meta · AI model
Llama 4 Maverick
Open-weight natively multimodal mixture-of-experts model (17B active / 400B total parameters, 128 experts) released April 2025 under the Llama 4 Community License. Text and image input, text and code output, 1M-token context.
Last verified Available 5 sources
Key specs
- Provider
- Meta
- Family
- Llama 4
- Availability
- Available
- Release date
- 2025-04-05
- License
- Open weights (Llama 4 Community License)
- Context window
- 1,000,000 tokens
- Knowledge cutoff
- August 2024
- API access
- Unknown
- Consumer app
- Unknown
Capabilities
Inputs
- Text input Yes
- Image input Yes Text plus up to 5 images; image understanding is English-only
- Audio input No Input modalities listed as multilingual text and image
- Video input No Input modalities listed as multilingual text and image
- File input Unknown
Outputs
- Text output Yes
- Image output No Output modalities listed as multilingual text and code
- Audio output Unknown
Features
- Reasoning Unknown
- Tool calling Yes Zero-shot function calling in Python-style and JSON formats; tool output uses the ipython role
- Web search Unknown
"Unknown" means we have not verified this capability yet; it does not mean the model lacks it.
Pricing
No current prices listed.
Benchmarks
| Benchmark | Setting | Score | Reported by | Measured | Verified | Source |
|---|---|---|---|---|---|---|
| GDPval-AA v2.1 Elo, higher is better | v2.1; no effort setting; Artificial Analysis Stirrup harness | -276 Elo | Third party | 2026-10-25 | 2026-10-25 | GDPval-AA v2.1 Leaderboard (Artificial Analysis) |
| Humanity's Last Exam accuracy %, higher is better | full set; tools not stated; Scale Labs harness, o3-mini judge | 5.68 % | Third party | — | 2026-10-25 | Humanity's Last Exam leaderboard (Scale Labs) |
| Text Arena Arena score, higher is better | Overall, style control on (default) | 1,327 | Third party | 2026-10-23 | 2026-10-25 | Text Arena leaderboard (Arena) |
Elo is a relative rating: values change as models are added and the scale is re-anchored, so always store the date a rating was read. For example, Anthropic's launch page gives 1846 for Claude Opus 5.5, while the leaderboard on 2026-10-12 shows 1866 (Max, Default Fallback). Earlier versions (Google cites "GDPVal-AA v2") are not comparable. Judging is done by an LLM, not by human experts. Anthropic models are listed with "Default Fallback", meaning refused steps are routed to a fallback model. AA-Briefcase and GDP.pdf are separate evaluations.
Results differ a lot by setting: with tools versus without tools (Anthropic reports 45.9% without tools and 57.4% with tools for Claude Haiku 5.5), and the full set versus the text-only subset. Providers use different judge models and harnesses (Scale uses o3-mini; Alibaba states GPT-4o). Derived sets such as HLE-Verified (a third-party revision with 1,811 scored items), HLE-Rolling and HLE-Diamond are different item sets and are not comparable. The questions are public, so contamination is possible, and community reviews have reported flawed items.
Scores measure voter preference, which can be influenced by answer style and length. The leaderboard offers a style-control adjustment, so record which view was used. Scores shift with every update, so a value is only meaningful together with its leaderboard date. Entries marked "Preliminary" or with few votes have wide confidence intervals. The same model can appear several times with different reasoning-effort suffixes (for example -high or -max). Category views (Coding, Math, Creative Writing and others) are different rankings from Overall.
One row per result, without rank numbers: each result was measured under its own setting (effort level, harness, tools, test version), as stated by the source, and scores compare only within the same setting. Self-reported results come from the provider and have not been reproduced independently.
Rankings
- #37 of 42 in Best AI API as of 2026-10-26
Derived from our published ranking snapshots; each ranking explains its criteria and weights.
Compare Llama 4 Maverick
Guides
About Llama 4 Maverick
Llama 4 Maverick is a natively multimodal mixture-of-experts model with 17B active and 400B total parameters across 128 experts, released on 5 April 2025. It accepts multilingual text and image input and outputs text and code, with a 1M-token context window and a knowledge cutoff of August 2024. Meta's Llama 4 page labels Llama 4 as the latest Llama generation, and the weights are distributed under the Llama 4 Community License.
Strengths and weaknesses
Strengths
- Open weights under the Llama 4 Community License
- Native text and image input (early fusion), with 12 officially supported languages
- 1M-token context window
- Documented zero-shot function calling (Python-style and JSON formats)
Weaknesses
- Knowledge cutoff of August 2024
- Image understanding is English-only and tested up to 5 input images
- Smaller context window than Llama 4 Scout (1M vs 10M tokens); no Meta first-party API price listed
Sources
Last verified Page updated 2026-10-26