modelparams.dev
API MCP GitHub

Providers

Alibaba Anthropic Bedrock Cerebras Cohere DeepSeek Fireworks Google Groq Meta MiniMax Mistral Moonshot AI NVIDIA OpenAI Perplexity Thinking Machines Vertex xAI Xiaomi Z.ai

Providers

Alibaba Anthropic Bedrock Cerebras Cohere DeepSeek Fireworks Google Groq Meta MiniMax Mistral Moonshot AI NVIDIA OpenAI Perplexity Thinking Machines Vertex xAI Xiaomi Z.ai
Bedrock 4 params

Bedrock Pixtral Large 2502 API parameters

These are the API parameters modelparams.dev tracks for Bedrock Pixtral Large 2502 — the settings you send in a request. Each row gives the type, default, valid range or values, and the conditions that gate it. It's the same data the JSON API serves.

After the parameter count instead — how many weights Pixtral Large 2502 has? That's a different number, and we don't track it. Here's the difference.

Length 2 params
Parameter Type Default Description Condition
Max tokens
inferenceConfig.maxTokens 		integer (1…+∞) — Maximum number of output tokens the model may generate. —
Stop sequences
inferenceConfig.stopSequences 		string — A list of strings where the model stops generating further tokens. —
Sampling 2 params
Parameter Type Default Description Condition
Temperature
inferenceConfig.temperature 		number (0…1 step 0.1) — Controls randomness. Lower values make outputs more focused; higher values make them more varied. Bedrock rejects values above 1 for this model. —
Top P
inferenceConfig.topP 		number (0…1 step 0.01) — Controls nucleus sampling by limiting generation to tokens whose cumulative probability reaches this value. —

Bedrock Pixtral Large 2502 API parameters in brief

Bedrock Pixtral Large 2502 documents 4 API parameters, grouped by what they control:

Frequently asked questions

Which API parameters does Bedrock Pixtral Large 2502 support?
Bedrock Pixtral Large 2502 accepts 4 API parameters in the request body: inferenceConfig.maxTokens, inferenceConfig.temperature, inferenceConfig.topP, inferenceConfig.stopSequences.

Resources

All Bedrock models Glossary Full catalog

Pixtral Large 2502 — JSON

The full model definition as served by the API. Copy it or open the endpoint directly.

/api/v1/models/bedrock/pixtral-large-2502.json 
{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "bedrock",
  "authType": "api_key",
  "model": "pixtral-large-2502",
  "wireId": "{scope}.mistral.pixtral-large-2502-v1:0",
  "params": [
    {
      "path": "inferenceConfig.maxTokens",
      "label": "Max tokens",
      "description": "Maximum number of output tokens the model may generate.",
      "group": "generation_length",
      "type": "integer",
      "range": {
        "min": 1
      }
    },
    {
      "path": "inferenceConfig.temperature",
      "label": "Temperature",
      "description": "Controls randomness. Lower values make outputs more focused; higher values make them more varied. Bedrock rejects values above 1 for this model.",
      "group": "sampling",
      "type": "number",
      "range": {
        "min": 0,
        "max": 1,
        "step": 0.1
      }
    },
    {
      "path": "inferenceConfig.topP",
      "label": "Top P",
      "description": "Controls nucleus sampling by limiting generation to tokens whose cumulative probability reaches this value.",
      "group": "sampling",
      "type": "number",
      "range": {
        "min": 0,
        "max": 1,
        "step": 0.01
      }
    },
    {
      "path": "inferenceConfig.stopSequences",
      "label": "Stop sequences",
      "description": "A list of strings where the model stops generating further tokens.",
      "group": "generation_length",
      "type": "string"
    }
  ]
}

Other Bedrock models

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How to use

Building with an AI agent? Hit Copy to grab this whole guide as Markdown and paste it in — or point your agent straight at /llms.txt.

modelparams.dev is an open, community-maintained catalog of model parameters. Each entry shows the knobs you can turn — type, default, range, and the conditions that gate it.

The same model accessed via an API key and via a subscription usually exposes a different set of parameters. We list both as separate entries so the data stays honest.

Catalog API

The full catalog is static JSON, CORS-enabled, served from the edge.

curl https://modelparams.dev/api/v1/models.json

Each entry is keyed by provider/model for API-key variants; subscription variants append -subscription.

If you only need the params for one model contract, use the providerless endpoint. Subscription contracts are model slugs with -subscription. 

curl https://modelparams.dev/api/v1/models/openai/gpt-5.5.json
curl https://modelparams.dev/api/v1/models/openai/gpt-5.5-subscription.json

Single model

curl https://modelparams.dev/api/v1/models/anthropic/claude-opus-4-7.json
curl https://modelparams.dev/api/v1/models/anthropic/claude-opus-4-7-subscription.json

JSON Schema

Every entry validates against a JSON Schema you can use in your editor or pipeline. 

curl https://modelparams.dev/api/v1/schema.json

Add this header to any YAML you author for autocomplete in VS Code: 

# yaml-language-server: $schema=https://modelparams.dev/api/v1/schema.json

Logos

Provider logos are available at /assets/logos/{provider}.svg where {provider} is the provider slug. They use currentColor so they inherit your text color. 

curl https://modelparams.dev/assets/logos/anthropic.svg

Logos are sourced from the models.dev repo (MIT) and used under nominative fair use.

Contribute

The data lives in YAML under models/{provider}/{model}-{auth}.yaml in the GitHub repo. Open a PR; CI validates against the schema and rebuilds.

Edit on GitHub MIT licensed