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Llama 4 Maverick
About Llama 4 Maverick
Llama 4 Maverick is an AI model developed by Meta AI, in the multimodal category, released in 2025, made available as an open-weights model with 400B params.
On this page you'll find Llama 4 Maverick's full specifications, including 8 benchmark results. Review provider pricing and benchmark scores below, or compare Llama 4 Maverick head-to-head with other multimodal models.
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Run Llama 4 Maverick locally — what it takes
Llama 4 Maverick (400B) is too large to run on a single consumer or Apple machine. At Q4 its weights alone are about 224 GB — it needs a multi-GPU / datacenter setup:
- ≈ 1× AMD Instinct MI325X
- ≈ 2× NVIDIA B200
Lower quantization (Q3/Q2) or CPU + system-RAM offload (e.g. ktransformers) reduces the requirement at the cost of speed.
Software support
✓ measured · · compatible · — not supported. Informational only — speed is hardware-based.
Community
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Llama 4 Maverick benchmark scores▶
| Benchmark | Category | Score | Variant |
|---|---|---|---|
| LiveCodeBench v5 | code | 43.4% | |
| LiveCodeBench v6 | code | 32.7% | |
| IFEval | general | 85.4% | |
| MMLU-Pro | general | 80.5% | |
| MMLU-Redux | general | 92.3% | |
| AIME 2025 | math | 18% | |
| GPQA Diamond | reasoning | 69.8% | |
| BFCL v3 | tool-use | 52.9% |
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Frequently asked questions
What is Llama 4 Maverick? ▶
Llama 4 Maverick is an AI model developed by Meta AI, in the multimodal category, released in 2025. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.
Who created Llama 4 Maverick? ▶
Llama 4 Maverick was developed by Meta AI and released in 2025.
Is Llama 4 Maverick open source or proprietary? ▶
Llama 4 Maverick ships as an open-weights model: you can download and self-host the weights, though the licence may place some restrictions on use.
How much does Llama 4 Maverick cost? ▶
Pricing for Llama 4 Maverick depends on the provider. See the providers table on this page for the latest API rates.
How does Llama 4 Maverick perform on benchmarks? ▶
Llama 4 Maverick is benchmarked across 8 evaluations on GenAIList, including LiveCodeBench v5 (43.4%). See the full benchmark table below and compare it with other models.
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