Llama 3.2 90B Vision Instruct

Chat

Built by Meta · United States · llama.com

Meta chat model.

How to use

model: "meta-llama/llama-3.2-90b-vision-instruct"

Cap quality here and save

Hard questions go to this model, easy ones drop to something cheaper. Set a savings target (0–0.8) and the router tunes itself until realized savings converge on it.

{
  "model": "celon/auto",
  "celon": {
    "anchor": "meta-llama/llama-3.2-90b-vision-instruct",
    "savings_target": 0.4
  }
}

Naming a model directly gets you that model — savings controls don't apply.

Context

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Max output

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Input $/1M

$0.35

Output $/1M

$0.40

Features

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Serving providers

DeepInfra

Providers

Price, latency, and uptime per provider serving this model. Celon routes each request to the fastest and cheapest of them. Click a row for regions and data policies.

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Performance

Benchmark quality scores, and measured speed per provider.

Quality

Epoch Capabilities IndexComposite over 50+ benchmarks

125.7

GPQA DiamondPhD-level science questions

41.0%

AIMECompetition mathematics

2.6%

At each model's best reasoning effort. Benchmarks it wasn't run on are omitted.

Speed

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