modelparams.dev
API MCP GitHub

Providers

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

MiniMax M2 API parameters

These are the API parameters modelparams.dev tracks for MiniMax M2 on Chat Completions with an API key — 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.

This model is retired.

After the parameter count instead — how many weights MiniMax M2 has? That's a different number, and we don't track it. Here's the difference.

Length 1 param
Parameter Type Default Description Condition
Max completion tokens
max_completion_tokens 		integer (1…+∞) — Maximum number of tokens to generate in the completion. —
Sampling 2 params
Parameter Type Default Description Condition
Temperature
temperature 		number (0.01…1 step 0.01) 1 Controls randomness. Lower values make outputs more focused; higher values make them more varied. Values must be greater than 0 and at most 1. —
Top P
top_p 		number (0.01…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
Split reasoning
reasoning_split 		boolean false Returns the model's reasoning in a separate reasoning_details field instead of inline with the response. —

MiniMax MiniMax M2 API parameters in brief

MiniMax MiniMax M2 on Chat Completions documents 4 API parameters, grouped by what they control:

Frequently asked questions

Which API parameters does MiniMax M2 support?
MiniMax M2 accepts 4 API parameters in the request body: max_completion_tokens, temperature, top_p, reasoning_split.
What is the default temperature for MiniMax M2?
The default temperature for MiniMax M2 is 1, within a valid range of 0.01 to 1.
What is the default top_p for MiniMax M2?
The default top_p for MiniMax M2 is 0.95, within a valid range of 0.01 to 1.

Resources

All MiniMax models Glossary Full catalog

MiniMax M2 — JSON

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

/api/v1/models/minimax/MiniMax-M2.json 
{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "minimax",
  "authType": "api_key",
  "apiSurface": "openai-chat-completions",
  "model": "MiniMax-M2",
  "status": "retired",
  "params": [
    {
      "path": "max_completion_tokens",
      "label": "Max completion tokens",
      "description": "Maximum number of tokens to generate in the 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. Values must be greater than 0 and at most 1.",
      "group": "sampling",
      "type": "number",
      "default": 1,
      "range": {
        "min": 0.01,
        "max": 1,
        "step": 0.01
      }
    },
    {
      "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": 0.01,
        "max": 1,
        "step": 0.01
      }
    },
    {
      "path": "reasoning_split",
      "label": "Split reasoning",
      "description": "Returns the model's reasoning in a separate reasoning_details field instead of inline with the response.",
      "group": "reasoning",
      "type": "boolean",
      "default": false
    }
  ]
}

Other MiniMax models

MiniMax M2 Subscription 3 params View MiniMax M2.1 4 params View MiniMax M2.1 Subscription 3 params View MiniMax M2.1 Highspeed 4 params View MiniMax M2.1 Highspeed Subscription 3 params View MiniMax M2.5 4 params View MiniMax M2.5 Subscription 3 params View MiniMax M2.5 Highspeed 4 params View MiniMax M2.5 Highspeed Subscription 3 params View MiniMax M2.7 4 params View MiniMax M2.7 Subscription 3 params View MiniMax M2.7 Highspeed 4 params View MiniMax M2.7 Highspeed Subscription 3 params View MiniMax M3 4 params View MiniMax M3 Subscription 3 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