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Llama 3.2 90B
About Llama 3.2 90B
Llama 3.2 90B is an AI model developed by Meta AI, in the multimodal category, released in 2024, made available as an open-weights model with 88.6B params.
On this page you'll find Llama 3.2 90B's full specifications, including 8 benchmark results. Review provider pricing and benchmark scores below, or compare Llama 3.2 90B head-to-head with other multimodal models.
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Run Llama 3.2 90B locally — what to buy
Share this build ↗Sized to what Llama 3.2 90B actually needs (~8k context at Q4), not to the biggest GPU: Good = cheapest that runs it, Better = best value, Best = most headroom. Speed is a hardware estimate; anything past ~120 tok/s is shown as instant.
Software support
✓ measured · · compatible · — not supported. Informational only — speed is hardware-based.
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Llama 3.2 90B benchmark scores▶
| Benchmark | Category | Score | Variant |
|---|---|---|---|
| ChartQA | multimodal | 85.5% | cited-nvlm |
| ChartQA | multimodal | 70.8% | cited-pixtral-large |
| DocVQA | multimodal | 90.100 | cited-nvlm |
| DocVQA | multimodal | 85.700 | cited-pixtral-large |
| MMMU | multimodal | 60.3% | val-cited-nvlm |
| MMMU | multimodal | 53.7% | cited-pixtral-large |
| MathVista | multimodal | 57.3% | cited-nvlm |
| MathVista | multimodal | 49.1% | cited-pixtral-large |
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Frequently asked questions
What is Llama 3.2 90B? ▶
Llama 3.2 90B is an AI model developed by Meta AI, in the multimodal category, released in 2024. It is tracked on GenAIList with its specifications, benchmark scores and provider pricing.
Who created Llama 3.2 90B? ▶
Llama 3.2 90B was developed by Meta AI and released in 2024.
Is Llama 3.2 90B open source or proprietary? ▶
Llama 3.2 90B 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 3.2 90B cost? ▶
Pricing for Llama 3.2 90B depends on the provider. See the providers table on this page for the latest API rates.
How does Llama 3.2 90B perform on benchmarks? ▶
Llama 3.2 90B is benchmarked across 8 evaluations on GenAIList, including ChartQA (85.5%). See the full benchmark table below and compare it with other models.
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