MiniMax M2

Tool callingStructured outputReasoning

Hugging Face Launch post Website

Efficient open MiniMax model built for coding agents and tool-heavy workflows

Context: 205K
Released: 11mo ago
Parameters: —
Input / 1M tokens: $0.26
Output / 1M tokens: $1.02

Sources:models.devOpenRouter

Benchmarks

DeepSWE is the primary coding benchmark where an exact model evaluation exists. Other sourced evaluations appear below; missing scores are not zero.

Not evaluated in DeepSWE 1.1 as of 2026-09-22. Results are only shown for exact model versions in the official dataset. Official leaderboard.

Other published benchmarks

Evaluation	Reported score and source
Terminal Bench	30.0% https://www.tbench.ai/leaderboard/terminal-bench/2.0 · MiniMax-M2 Agent: Terminus 2 https://www.tbench.ai/leaderboard/terminal-bench/2.0 Original-source terms apply

Benchmark compilation: Epoch AI, Capabilities & benchmarking (CC BY attribution). Scores are converted to percentages and model names matched to the Vertical Tabs catalog. Individual evaluations are credited to their original sources. External results may carry separate licences and evaluation configurations; do not interpret scores from different harnesses as directly comparable.

Specifications

Developer: MiniMax
Model family: MiniMax
Type: Language model
Predecessor: —
Successor: —
Released: October 27, 2025
Model ID: minimax/minimax-m2
Openness: Open weights
License: —
Parameters: —
Input modalities: text
Output modalities: text
Modality: text->text
Tokenizer: Other
Max output tokens: 131K
Hugging Face: MiniMaxAI/MiniMax-M2
Source freshness: Metadata synced Oct 8, 2026, 10:17 PM UTC

Additional source evidence

Source model: minimax/MiniMax-M2
Source family: minimax
Last updated: 2025-10-27
Model context: 205K
Model output limit: 131K
Open weights: Yes
File attachments: No
Reasoning: Yes
Tool calling: Yes
Temperature control: Yes

Downloadable weights

Hugging Face

Published benchmarks

Benchmark	Score	Evaluation details	Evidence
SWE-Bench Verified	69.4 · resolved	—	Source

Complete source record (JSON)

{
  "id": "minimax/MiniMax-M2",
  "name": "MiniMax-M2",
  "description": "Efficient open MiniMax model built for coding agents and tool-heavy workflows",
  "family": "minimax",
  "last_updated": "2025-10-27",
  "attachment": false,
  "reasoning": true,
  "tool_call": true,
  "temperature": true,
  "modalities": {
    "input": [
      "text"
    ],
    "output": [
      "text"
    ]
  },
  "limit": {
    "context": 204800,
    "output": 131072
  },
  "benchmarks": [
    {
      "name": "SWE-Bench Verified",
      "score": 69.4,
      "source": "https://huggingface.co/MiniMaxAI/MiniMax-M2",
      "metric": "resolved"
    }
  ],
  "release_date": "2025-10-27",
  "open_weights": true,
  "weights": [
    {
      "label": "Hugging Face",
      "url": "https://huggingface.co/MiniMaxAI/MiniMax-M2"
    }
  ]
}

Infrastructure

Provider availability

All providers

Provider	Endpoint	Context	Input /M tokens	Output /M tokens	Cached input /M tokens	Cache write /M tokens	Uptime 1d	Data handling
Minimax	minimax/fp8	205K	$0.26	$1.02	—	—	100.00%	ZDR: Yes Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15
Google	google-vertex	197K	$0.30	$1.20	—	—	—	ZDR: Yes Training: Unknown Prompt logging: Unknown Retention: Unknown ZDR source Privacy policy Checked 2026-10-15

Provider data:OpenRouter

Deployment graph

Can I run this?

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