MiniMax-M2.1 API

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MiniMax-M2.1 is an updated Minimax model with a 200K context window optimized for conversational and reasoning tasks.

Modalities: TextText
In / Out price: $0.3/$1.2per 1M
Context window: 204K tokens
Released: Dec 23, 2025

MiniMax-M2.1 overview

MiniMax-M2.1 by MiniMax

Engineered for speed and precision, it delivers top-tier multilingual code generation with clean, actionable outputs.

MiniMax-M2.1 specs

Model ID: minimax/m2-1
Developer: MiniMax
Context window: 204,000 tokens
Max output: 204,000 tokens
Input: Text
Output: Text
API: OpenAI-compatible, base URL https://api.aimlapi.com/v1

Multilingual Code Generation & Refactoring AI Model

MiniMax-M2.1 is a cutting-edge large language model built for high-performance code generation, refactoring, and cross-language reasoning. Optimized for real-world developer workflows, it supports languages such as Rust, Java, Go, C++, TypeScript, and JavaScript, offering fast, clean, and reliable outputs.

Technical Specifications

Model type: Multilingual Transformer-based LLM
Architecture: Hybrid dense-attention model with optimized code tokenization
Context window: 204,800 tokens (input + output)
Supported languages: Rust, Go, Java, C++, TypeScript, JavaScript, Python, SQL

Performance Benchmarks

Evaluated using rigorous internal frameworks (e.g., OctoCodingbench, SWE Review), with results averaged over 4 runs.

Key Features

Multilingual Coding Mastery: Excels across 6+ major programming languages with syntax-aware generation and refactoring
Agentic Reasoning: Maintains coherent reasoning between turns, critical for tool use, IDE integration, and long-horizon tasks
Concise & Clean Outputs: Minimizes verbosity while preserving functional correctness and style consistency
Real-Time Developer Workflows: Optimized for low latency and high throughput in coding assistants and CI/CD pipelines
Open & Deployable: Fully open-source weights enable on-prem, edge, or custom deployment scenarios

Core Use Cases

Cross-Language Code Migration: Seamlessly rewrite applications between Rust, Go, and JavaScript without losing logic integrity.
Code Review & Refactoring: Automate code readability enhancements, style consistency, and optimization opportunities.
Automated Documentation: Generate aligned docstrings, inline comments, and technical documentation for complex repositories.
Intelligent Debugging: Detect potential bugs and suggest fixes within a single inference cycle.
Developer Tool Integration: Connect via SDKs or APIs to augment IDEs such as VSCode, JetBrains, or Neovim with real-time AI assistance.

Model Comparison

vs. Claude Sonnet 4.5: M2.1 matches or exceeds Sonnet 4.5 in coding-specific benchmarks while using far fewer activated parameters. Offers significantly lower inference cost and latency, making it ideal for high-throughput coding agents.

vs. DeepSeek-Coder: M2.1 demonstrates stronger instruction following in complex, multi-step coding scenarios (e.g., full-stack feature implementation). Excels in real-world tool integration and stateful reasoning, critical for IDE plugins and autonomous agents.

Use cases

Cross-Language Code Migration: Seamlessly rewrite applications between Rust, Go, and JavaScript without losing logic integrity.
Code Review & Refactoring: Automate code readability enhancements, style consistency, and optimization opportunities.
Automated Documentation: Generate aligned docstrings, inline comments, and technical documentation for complex repositories.
Intelligent Debugging: Detect potential bugs and suggest fixes within a single inference cycle.
Developer Tool Integration: Connect via SDKs or APIs to augment IDEs such as VSCode, JetBrains, or Neovim with real-time AI assistance.

Capabilities

Function calling
Streaming
Structured outputs
Reasoning

MiniMax-M2.1 benchmarks by Artificial Analysis

See how MiniMax-M2.1 compares in generation speed and latency. Data retrieved Nov 3, 2026.

Speed#164 / 21957.5Output tokens / second Latency#122 / 2161.70Seconds to first token Humanity's Last Exam#125 / 45823.2%Score GPQA Diamond#114 / 43983%Score

Speed

Output tokens / second

Benchmark results

Compare 12 models available on AI/ML API across 5 independent benchmarks.

Humanity's Last Exam

Expert-written questions across academic subjects.

MiniMax-M2.1 API pricing

MiniMax-M2.1 pricing in US dollars
Usage	Price	Unit
Input	$0.3	1M tokens
Output	$1.2	1M tokens
Cached input	$0.3	1M tokens

Prices from the AI/ML API price list, checked on Nov 4, 2026.

MiniMax-M2.1 vs other models: token prices

AI/ML API input and output rates for 5 models, per million tokens.

AI/ML API model prices in USD per million tokens
Model	Input	Output
MiniMax-M2.1	$0.3	$1.2
MiniMax M3.1 Flash	$0.15	$0.6
MiniMax M3	$0.3	$1.2
MiniMax M2.1 Highspeed	$0.6	$2.4
MiniMax M2.7 Highspeed	$0.6	$2.4

How to use the MiniMax-M2.1 API

View docs

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key

export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/chat/completions' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "minimax/m2-1",
  "messages": [
    {
      "role": "user",
      "content": "Write a haiku about the ocean."
    }
  ]
}'

import os
import requests

headers = {
    "Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
    "Content-Type": "application/json",
}
payload = {
    "model": "minimax/m2-1",
    "messages": [
        {
            "role": "user",
            "content": "Write a haiku about the ocean."
        }
    ]
}

response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())

const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "minimax/m2-1",
    "messages": [
      {
        "role": "user",
        "content": "Write a haiku about the ocean."
      }
    ]
  }),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());

All posts

MiniMax-M2.1 FAQ

What is the context window of MiniMax-M2.1?

MiniMax-M2.1 has a 204,000 tokens context window and can return up to 204,000 tokens.

What inputs and outputs does MiniMax-M2.1 support?

MiniMax-M2.1 takes image, text as input and returns text.

What is the model ID for MiniMax-M2.1?

Use minimax/m2-1 as the model id. Requests go to https://api.aimlapi.com/v1/chat/completions.

How much does MiniMax-M2.1 cost?

MiniMax-M2.1 costs $0.3 input and $1.2 output per 1M tokens on AI/ML API, billed as you go with no subscription.

Does MiniMax-M2.1 support streaming?

Yes, MiniMax-M2.1 can stream responses as they are generated.

Can MiniMax-M2.1 read images?

Yes, MiniMax-M2.1 accepts image input alongside text.

Who created MiniMax-M2.1?

MiniMax-M2.1 was built by MiniMax.

Start building with MiniMax-M2.1

Get API key

MiniMax-M2.1 API

minimax/m2-1

Build with your agent

Give your agent the model details, code and documentation.

1Get your API key

Create API key

export AIMLAPI_KEY="8f2b4c7d9a1e6b3f…"

2Make your first request

curl 'https://api.aimlapi.com/v1/chat/completions' \
  -H "Authorization: Bearer $AIMLAPI_KEY" \
  -H 'Content-Type: application/json' \
  -d '{
  "model": "minimax/m2-1",
  "messages": [
    {
      "role": "user",
      "content": "Write a haiku about the ocean."
    }
  ]
}'

import os
import requests

headers = {
    "Authorization": f"Bearer {os.environ['AIMLAPI_KEY']}",
    "Content-Type": "application/json",
}
payload = {
    "model": "minimax/m2-1",
    "messages": [
        {
            "role": "user",
            "content": "Write a haiku about the ocean."
        }
    ]
}

response = requests.post("https://api.aimlapi.com/v1/chat/completions", headers=headers, json=payload, timeout=120)
response.raise_for_status()
print(response.json())

const response = await fetch("https://api.aimlapi.com/v1/chat/completions", {
  method: "POST",
  headers: {
    Authorization: `Bearer ${process.env.AIMLAPI_KEY}`,
    "Content-Type": "application/json",
  },
  body: JSON.stringify({
    "model": "minimax/m2-1",
    "messages": [
      {
        "role": "user",
        "content": "Write a haiku about the ocean."
      }
    ]
  }),
});

if (!response.ok) throw new Error(`HTTP ${response.status}`);
console.log(await response.json());

Docs for AI agents Plain-text index · llms.txt API documentation API reference and examples

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MiniMax-M2.1 API

MiniMax-M2.1 overview

MiniMax-M2.1 by MiniMax

MiniMax-M2.1 specs

Multilingual Code Generation & Refactoring AI Model

Technical Specifications

Performance Benchmarks

Key Features

Core Use Cases

Model Comparison

Use cases

Capabilities

MiniMax-M2.1 benchmarks by Artificial Analysis

Speed

Benchmark results

Humanity's Last Exam

GPQA Diamond

AA-LCR

IFBench

τ²-Bench Telecom

MiniMax-M2.1 API pricing

MiniMax-M2.1 vs other models: token prices

How to use the MiniMax-M2.1 API

Build with your agent

1Get your API key

2Make your first request

Related articles

MiniMax-M2.1 FAQ

Start building with MiniMax-M2.1

MiniMax-M2.1 API

Build with your agent

1Get your API key

2Make your first request

MiniMax-M2.1 API

MiniMax-M2.1 overview

MiniMax-M2.1 by MiniMax

MiniMax-M2.1 specs

Multilingual Code Generation & Refactoring AI Model

Technical Specifications

Performance Benchmarks

Key Features

Core Use Cases

Model Comparison

Use cases

Capabilities

Speed

Benchmark results

Humanity's Last Exam

GPQA Diamond

AA-LCR

IFBench

τ²-Bench Telecom

MiniMax-M2.1 API pricing

MiniMax-M2.1 vs other models: token prices

How to use the MiniMax-M2.1 API

Build with your agent

1Get your API key

2Make your first request

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