modelparams.dev
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Providers

Alibaba Anthropic Cohere DeepSeek Google Meta MiniMax Mistral Moonshot AI Nvidia OpenAI Perplexity xAI Xiaomi Z.ai

Providers

Alibaba Anthropic Cohere DeepSeek Google Meta MiniMax Mistral Moonshot AI Nvidia OpenAI Perplexity xAI Xiaomi Z.ai
MiniMax Subscription 3 params

MiniMax MiniMax M3 (subscription) parameters

These are the parameters modelparams.dev tracks for MiniMax MiniMax M3 when you reach it through a subscription rather than an API key. 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 tokens
max_tokens 		integer (1…+∞) — Maximum number of tokens to generate in the response. —
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. —

MiniMax MiniMax M3 API parameters in brief

MiniMax MiniMax M3 via subscription documents 3 API parameters, grouped by what they control:

Frequently asked questions

How many parameters does MiniMax MiniMax M3 (subscription) accept?
MiniMax MiniMax M3 (subscription) accepts 3 API parameters: max_tokens, temperature, top_p.
What is the default temperature for MiniMax MiniMax M3 (subscription)?
The default temperature for MiniMax MiniMax M3 (subscription) is 1, within a valid range of 0.01 to 1.
What is the default top_p for MiniMax MiniMax M3 (subscription)?
The default top_p for MiniMax MiniMax M3 (subscription) is 0.95, within a valid range of 0.01 to 1.

Resources

All MiniMax models Glossary Full catalog

MiniMax M3 — JSON

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

/api/v1/models/minimax/MiniMax-M3-subscription.json 
{
  "$schema": "https://modelparams.dev/api/v1/schema.json",
  "provider": "minimax",
  "authType": "subscription",
  "model": "MiniMax-M3",
  "params": [
    {
      "path": "max_tokens",
      "label": "Max tokens",
      "description": "Maximum number of tokens to generate in the 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. 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
      }
    }
  ]
}

Other MiniMax models

MiniMax M2 4 params View 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

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