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
xAI 6 params

xAI Grok 4.6 API parameters

These are the API parameters modelparams.dev tracks for xAI Grok 4.6 — 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 Grok 4.6 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 completion tokens
max_completion_tokens 		integer (1…+∞) — Upper bound for visible output tokens generated in the chat completion. —
Stop sequence
stop 		string — Stops generation when this sequence is produced. xAI accepts up to four stop sequences. —
Sampling 3 params
Parameter Type Default Description Condition
Temperature
temperature 		number (0…2 step 0.1) 1 Controls randomness. Lower values make outputs more focused; higher values make them more varied. —
Top P
top_p 		number (0…1 step 0.01) 1 Controls nucleus sampling by limiting generation to tokens within the selected cumulative probability. —
Seed
seed 		integer — Optional seed used for decoding when reproducible sampling is desired. —
Output 1 param
Parameter Type Default Description Condition
Response format
response_format.type 		enum (text | json_object | json_schema) "text" Controls whether the model returns text, JSON mode output, or structured JSON schema output. —

xAI Grok 4.6 API parameters in brief

xAI Grok 4.6 documents 6 API parameters, grouped by what they control:

Frequently asked questions

Which API parameters does xAI Grok 4.6 support?
xAI Grok 4.6 accepts 6 API parameters in the request body: max_completion_tokens, temperature, top_p, seed, stop, response_format.type.
What is the default temperature for xAI Grok 4.6?
The default temperature for xAI Grok 4.6 is 1, within a valid range of 0 to 2.
What is the default top_p for xAI Grok 4.6?
The default top_p for xAI Grok 4.6 is 1, within a valid range of 0 to 1.

Resources

All xAI models Glossary Full catalog

Grok 4.6 — JSON

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

/api/v1/models/xai/grok-4.6.json 
{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "xai",
  "authType": "api_key",
  "model": "grok-4.6",
  "params": [
    {
      "path": "max_completion_tokens",
      "label": "Max completion tokens",
      "description": "Upper bound for visible output tokens generated in the chat completion.",
      "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": 1,
      "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": 1,
      "range": {
        "min": 0,
        "max": 1,
        "step": 0.01
      }
    },
    {
      "path": "seed",
      "label": "Seed",
      "description": "Optional seed used for decoding when reproducible sampling is desired.",
      "group": "sampling",
      "type": "integer"
    },
    {
      "path": "stop",
      "label": "Stop sequence",
      "description": "Stops generation when this sequence is produced. xAI accepts up to four stop sequences.",
      "group": "generation_length",
      "type": "string"
    },
    {
      "path": "response_format.type",
      "label": "Response format",
      "description": "Controls whether the model returns text, JSON mode output, or structured JSON schema output.",
      "group": "output_format",
      "type": "enum",
      "default": "text",
      "values": [
        "text",
        "json_object",
        "json_schema"
      ]
    }
  ]
}

Other xAI models

Grok 4.20 0309 Non Reasoning 6 params View Grok 4.20 0309 Non Reasoning Subscription 6 params View Grok 4.20 0309 Reasoning 5 params View Grok 4.20 0309 Reasoning Subscription 5 params View Grok 4.20 Multi Agent 0309 5 params View Grok 4.3 6 params View Grok 4.3 Subscription 6 params View Grok 4.5 6 params View Grok 4.5 Subscription 6 params View Grok Build 0.1 5 params View Grok Build 0.1 Subscription 5 params View

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