LLaMA 4 Maverick is a cutting-edge multimodal model featuring 17 billion active parameters within a Mixture-of-Experts architecture of 128 experts, totaling 400 billion parameters. It leads its class by outperforming models like GPT-4o and Gemini 2.0 Flash across a wide range of benchmarks, and it matches DeepSeek V3 in reasoning and coding tasks—using less than half the active parameters. Designed for efficiency and scalability, Maverick delivers a best-in-class performance-to-cost ratio, with an experimental chat variant achieving an ELO score of 1417 on LMArena. Despite its scale, it runs on a single NVIDIA H100 host, ensuring simple and practical deployment.
Web Site AI Model Web Page | |
Provider The entity that provides this model. | |
Chat Input a message to start chatting | - |
Release Date When the model was first released. | 1 year ago Apr 05, 2025 |
Modalities Types of data this model can process | text images video |
API Providers The providers that offer this model. (This is not an exhaustive list.) | Meta AI, Hugging Face, Fireworks, Together, DeepInfra |
Knowledge Cut-off Date When the model's knowledge was last updated. | 2024-08 |
Open Source Whether the model's code is available for public use. | Yes (Source) |
Pricing Input Cost for processing tokens in your prompts | Not available |
Pricing Output Cost for tokens generated by the model | Not available |
MMLU Massive Multitask Language Understanding - Tests knowledge across 57 subjects including mathematics, history, law, and more | Not available |
MMLU-Pro A more robust MMLU benchmark with harder, reasoning-focused questions, a larger choice set, and reduced prompt sensitivity | 80.5% Source |
MMMU Massive Multitask Multimodal Understanding - Tests understanding across text, images, audio, and video | 73.4% Source |
HellaSwag A challenging sentence completion benchmark | Not available |
HumanEval Evaluates code generation and problem-solving capabilities | Not available |
MATH Tests mathematical problem-solving abilities across various difficulty levels | Not available |
GPQA Tests PhD-level knowledge in chemistry, biology, and physics through multiple choice questions that require deep domain expertise | 69.8% Diamond Source |
IFEval Tests model's ability to accurately follow explicit formatting instructions, generate appropriate outputs, and maintain consistent instruction adherence across different tasks | Not available |
SimpleQA Assessing the accuracy of simple questions | - |
AIME 2024 | - |
AIME 2025 | - |
Aider Polyglot Multilingual programming benchmark. | - |
LiveCodeBench v5 Benchmark for real-time programming | - |
Global MMLU (Lite) A simplified version of the benchmark for assessing the universality of models at the global level. | - |
MathVista Evaluates the mathematical reasoning abilities of AI models within visual contexts | - |
Mobile Application | - |
VideoGameBench | |
| Total score | 0% |
| Doom II | 0% |
| Dream DX | 0% |
| Awakening DX | 0% |
| Civilization I | 0% |
| Pokemon Crystal | 0% |
| The Need for Speed | 0% |
| The Incredible Machine | 0% |
| Secret Game 1 | %0 |
| Secret Game 2 | 0% |
| Secret Game 3 | 0% |
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