Llama 4 Maverick
Llama 4 Maverick is a natively multimodal model capable of processing both text and images. It features a 17 billion active parameter mixture-of-experts (MoE) architecture with 128 experts, supporting a wide range of multimodal tasks such as conversational interaction, image analysis, and code generation. The model includes a 1 million token context window.
Benchmark results
| Benchmark | Score | Tags | Source |
|---|---|---|---|
| ChartQA | 90.0% | self-reported llm-stats | link → |
| DocVQA | 94.4% | self-reported llm-stats | link → |
| GPQA | 69.8% | self-reported llm-stats | link → |
| LiveCodeBench | 43.4% | self-reported llm-stats | link → |
| MATH | 61.2% | self-reported llm-stats | link → |
| MathVista | 73.7% | self-reported llm-stats | link → |
| MBPP | 77.6% | self-reported llm-stats | link → |
| MGSM | 92.3% | self-reported llm-stats | link → |
| MMLU | 85.5% | self-reported llm-stats | link → |
| MMLU-Pro | 80.5% | self-reported llm-stats | link → |
| MMMU | 73.4% | self-reported llm-stats | link → |
| MMMU-Pro | 59.6% | self-reported llm-stats | link → |
| TydiQA | 31.7% | self-reported llm-stats | link → |