modelparams.dev
xAI 5 params

xAI Grok 4.20 Multi Agent 0309 parameters

These are the parameters modelparams.dev tracks for xAI Grok 4.20 Multi Agent 0309. 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.

Length 1 param
Parameter Type Default Description Condition
Max output tokens
max_output_tokens
integer (1…+∞) Upper bound for output tokens generated in the Responses API response.
Sampling 2 params
Parameter Type Default Description Condition
Temperature
temperature
number (0…2 step 0.1) 0.7 Controls randomness. Lower values make outputs more focused; higher values make them more varied.
Top P
top_p
number (0…1 step 0.01) 0.95 Controls nucleus sampling by limiting generation to tokens within the selected cumulative probability.
Reasoning 1 param
Parameter Type Default Description Condition
Reasoning effort
reasoning.effort
enum (low | medium | high | xhigh) Controls whether the Responses API request uses the 4-agent or 16-agent multi-agent setup.
Output 1 param
Parameter Type Default Description Condition
Text format
text.format.type
enum (text | json_object | json_schema) "text" Controls whether the Responses API returns free-form text, JSON mode output, or structured JSON schema output.

xAI Grok 4.20 Multi Agent 0309 API parameters in brief

xAI Grok 4.20 Multi Agent 0309 documents 5 API parameters, grouped by what they control:

Frequently asked questions

How many parameters does xAI Grok 4.20 Multi Agent 0309 accept?
xAI Grok 4.20 Multi Agent 0309 accepts 5 API parameters: max_output_tokens, temperature, top_p, reasoning.effort, text.format.type.
What is the default temperature for xAI Grok 4.20 Multi Agent 0309?
The default temperature for xAI Grok 4.20 Multi Agent 0309 is 0.7, within a valid range of 0 to 2.
What is the default top_p for xAI Grok 4.20 Multi Agent 0309?
The default top_p for xAI Grok 4.20 Multi Agent 0309 is 0.95, within a valid range of 0 to 1.

Resources

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Grok 4.20 Multi Agent 0309 — JSON

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

{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "xai",
  "authType": "api_key",
  "model": "grok-4.20-multi-agent-0309",
  "params": [
    {
      "path": "max_output_tokens",
      "label": "Max output tokens",
      "description": "Upper bound for output tokens generated in the Responses API response.",
      "group": "generation_length",
      "type": "integer",
      "range": {
        "min": 1
      }
    },
    {
      "path": "temperature",
      "label": "Temperature",
      "description": "Controls randomness. Lower values make outputs more focused; higher values make them more varied.",
      "group": "sampling",
      "type": "number",
      "default": 0.7,
      "range": {
        "min": 0,
        "max": 2,
        "step": 0.1
      }
    },
    {
      "path": "top_p",
      "label": "Top P",
      "description": "Controls nucleus sampling by limiting generation to tokens within the selected cumulative probability.",
      "group": "sampling",
      "type": "number",
      "default": 0.95,
      "range": {
        "min": 0,
        "max": 1,
        "step": 0.01
      }
    },
    {
      "path": "reasoning.effort",
      "label": "Reasoning effort",
      "description": "Controls whether the Responses API request uses the 4-agent or 16-agent multi-agent setup.",
      "group": "reasoning",
      "type": "enum",
      "values": [
        "low",
        "medium",
        "high",
        "xhigh"
      ]
    },
    {
      "path": "text.format.type",
      "label": "Text format",
      "description": "Controls whether the Responses API returns free-form text, JSON mode output, or structured JSON schema output.",
      "group": "output_format",
      "type": "enum",
      "default": "text",
      "values": [
        "text",
        "json_object",
        "json_schema"
      ]
    }
  ]
}

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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/params/gpt-5.5.json
curl https://modelparams.dev/api/v1/params/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