Llama 4 Maverick
Multimodal
Zero-eval
#1MGSM
#1TydiQA
#2ChartQA
by Meta
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About
Llama 4 Maverick is a multimodal language model developed by Meta. It achieves strong performance with an average score of 71.8% across 13 benchmarks. It excels particularly in DocVQA (94.4%), MGSM (92.3%), ChartQA (90.0%). With a 2.0M token context window, it can handle extensive documents and complex multi-turn conversations. The model is available through 7 API providers. As a multimodal model, it can process and understand text, images, and other input formats seamlessly. Released in 2025, it represents Meta's latest advancement in AI technology.
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Pricing Range
Input (per 1M)$0.17 -$0.63
Output (per 1M)$0.60 -$1.79
Providers7
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Timeline
AnnouncedApr 5, 2025
ReleasedApr 5, 2025
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Specifications
Training Tokens22.0T
Capabilities
Multimodal
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License & Family
License
Llama 4 Community License Agreement
Performance Overview
Performance metrics and category breakdown
Overall Performance
13 benchmarks
Average Score
71.8%
Best Score
94.4%
High Performers (80%+)
5Performance Metrics
Max Context Window
2.0MAvg Throughput
193.4 tok/sAvg Latency
1ms+
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All Benchmark Results for Llama 4 Maverick
Complete list of benchmark scores with detailed information
| DocVQA | multimodal | 0.94 | 94.4% | Self-reported | |
| MGSM | text | 0.92 | 92.3% | Self-reported | |
| ChartQA | multimodal | 0.90 | 90.0% | Self-reported | |
| MMLU | text | 0.85 | 85.5% | Self-reported | |
| MMLU-Pro | text | 0.81 | 80.5% | Self-reported | |
| MBPP | text | 0.78 | 77.6% | Self-reported | |
| MathVista | multimodal | 0.74 | 73.7% | Self-reported | |
| MMMU | multimodal | 0.73 | 73.4% | Self-reported | |
| GPQA | text | 0.70 | 69.8% | Self-reported | |
| MATH | text | 0.61 | 61.2% | Self-reported |
Showing 1 to 10 of 13 benchmarks