AI Rate Card

MiniMax-M3 · orcarouter

MiniMax-M3 is MiniMax's flagship open-weight foundation model and the first to combine three frontier capabilities at once: frontier-level coding and agentic performance, a 1M-token context window, and native multimodality. It accepts text, image, and video inputs with text output, and is powered by the proprietary MiniMax Sparse Attention (MSA) architecture, which sustains up to 1M tokens of context (with a guaranteed minimum of 512K) - the foundation for long-range agent tasks, long-horizon coding, and long-video understanding. Multimodality is a native core capability rather than an add-on: the data pipeline was rebuilt to scale pretraining to 100T+ tokens with multimodal training from step zero, deeply aligning textual and visual semantic spaces. M3 achieves top-tier results across coding and agentic benchmarks spanning software engineering, terminal execution, and autonomous browsing (scoring 83.5 on BrowseComp), with autonomous task decomposition, tool invocation, and multi-step reasoning. It is well suited to AI coding assistants, automated workflows, and long-running asynchronous agent pipelines where coherence over extended sessions matters.

Base modelAll models on this baseAll models of the providerto the provider

Read also: MiniMax API pricing: MiniMax M3, M3.1 Flash and M2.7 at every provider

All MiniMax models at every provider

Input, $/1M $0.30

Output, $/1M $1.20

Cache read $0.06

Cache write —

Context 1 048 576

Max output 512 000

Accepts image/gif, image/jpeg, image/png, image/webp, text, video/mp4, video/quicktime, video/x-matroska, video/x-msvideo

Last checked 04.11.2026 12:26:37 UTC

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API

OpenAI-compatible API: the official OpenAI SDKs work with this base URL. Replace YOUR_API_KEY with your key from the provider.

API base URL
https://api.orcarouter.ai/v1
Endpoint
https://api.orcarouter.ai/v1/chat/completions
Model id
minimax/minimax-m3
curl
curl https://api.orcarouter.ai/v1/chat/completions \
  -H "Authorization: Bearer YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model": "minimax/minimax-m3", "messages": [{"role": "user", "content": "Hello!"}], "max_tokens": 256}'
Python
import requests

r = requests.post(
    "https://api.orcarouter.ai/v1/chat/completions",
    headers={"Authorization": "Bearer YOUR_API_KEY"},
    json={
      "model": "minimax/minimax-m3",
      "messages": [
        {
          "role": "user",
          "content": "Hello!"
        }
      ],
      "max_tokens": 256
    },
)
print(r.json())
JavaScript
const r = await fetch("https://api.orcarouter.ai/v1/chat/completions", {
  method: "POST",
  headers: {Authorization: "Bearer YOUR_API_KEY", "Content-Type": "application/json"},
  body: JSON.stringify({
    "model": "minimax/minimax-m3",
    "messages": [
      {
        "role": "user",
        "content": "Hello!"
      }
    ],
    "max_tokens": 256
  }),
});
console.log(await r.json());
Request (JSON)
{
  "model": "minimax/minimax-m3",
  "messages": [
    {
      "role": "user",
      "content": "Hello!"
    }
  ],
  "max_tokens": 256
}
Response (JSON)
{
  "id": "chatcmpl-...",
  "object": "chat.completion",
  "model": "minimax/minimax-m3",
  "choices": [
    {
      "index": 0,
      "message": {
        "role": "assistant",
        "content": "Hi! How can I help?"
      },
      "finish_reason": "stop"
    }
  ],
  "usage": {
    "prompt_tokens": 9,
    "completion_tokens": 12,
    "total_tokens": 21
  }
}

The address is taken from the provider's model list; check it against the provider's documentation.

Provider's API documentation

Source: AI Rate Card, https://airatecard.com/en/c/offer%3Aorcarouter%7Cminimax/minimax-m3, prices checked 2026-11-04; seller's page: https://orcarouter.ai/models/minimax/minimax-m3

Technical details

ID: offer:orcarouter|minimax/minimax-m3