Models / minimaxai /  / MiniMax M2.5 API

MiniMax M2.5 API

Production-scale agentic coding with full-stack development and office deliverables

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MiniMax M2.5 is SOTA in coding, agentic tool use, search, and office work, extensively trained with reinforcement learning across 200,000+ complex real-world environments. The model achieves 80.2% SWE-Bench Verified while completing tasks 37% faster than M2.1, matching Claude Opus 4.6's speed. M2.5 exhibits architect-level planning capability, actively decomposing and planning features, structure, and UI design before writing code—spanning the entire development lifecycle from 0-to-1 system design through 90-to-100 comprehensive testing. Trained on 10+ programming languages across full-stack platforms (Web, Android, iOS, Windows), M2.5 delivers truly deliverable outputs in office scenarios on Together AI's production infrastructure.

80.2%
SWE-Bench Verified
SOTA coding across 200K+ real-world environments
37%
Faster Than M2.1
Matching Opus 4.6 speed with efficient decomposition
200K+
Real-World Training Environments
RL training across coding, search, and office work

Key Capabilities:

  • ✓ Architect-Level Planning: Spec-writing with feature decomposition and UI design before coding—spanning 0-to-1 system design through 90-to-100 comprehensive testing
  • ✓ SOTA Agentic Coding: 80.2% SWE-Bench Verified across 10+ languages and full-stack platforms—37% faster than M2.1, matching Opus 4.6 speed
  • ✓ Office Deliverables: Word documents, PowerPoint presentations, Excel models trained with industry experts—59.0% win rate vs mainstream models
  • ✓ Production-Ready Infrastructure: 99.9% SLA, available on serverless and dedicated infrastructure

MiniMax M2.5 API Usage

Endpoint

curl -X POST "https://api.together.xyz/v1/chat/completions" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "MiniMax/MiniMax-M2-5",
    "messages": [
      {
        "role": "user",
        "content": "What are some fun things to do in New York?"
      }
    ]
}'
curl -X POST "https://api.together.xyz/v1/images/generations" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "MiniMax/MiniMax-M2-5",
    "prompt": "Draw an anime style version of this image.",
    "width": 1024,
    "height": 768,
    "steps": 28,
    "n": 1,
    "response_format": "url",
    "image_url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"
  }'
curl -X POST https://api.together.xyz/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "MiniMax/MiniMax-M2-5",
    "messages": [{
      "role": "user",
      "content": [
        {"type": "text", "text": "Describe what you see in this image."},
        {"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
      ]
    }],
    "max_tokens": 512
  }'
curl -X POST https://api.together.xyz/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "MiniMax/MiniMax-M2-5",
    "messages": [{
      "role": "user",
      "content": "Given two binary strings `a` and `b`, return their sum as a binary string"
    }]
  }'
curl -X POST https://api.together.xyz/v1/rerank \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "MiniMax/MiniMax-M2-5",
    "query": "What animals can I find near Peru?",
    "documents": [
      "The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
      "The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
      "The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
      "The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
    ],
    "top_n": 2
  }'
curl -X POST https://api.together.xyz/v1/embeddings \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "input": "Our solar system orbits the Milky Way galaxy at about 515,000 mph.",
    "model": "MiniMax/MiniMax-M2-5"
  }'
curl -X POST https://api.together.xyz/v1/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -d '{
    "model": "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    "prompt": "A horse is a horse",
    "max_tokens": 32,
    "temperature": 0.1,
    "safety_model": "MiniMax/MiniMax-M2-5"
  }'
curl --location 'https://api.together.ai/v1/audio/generations' \
  --header 'Content-Type: application/json' \
  --header 'Authorization: Bearer $TOGETHER_API_KEY' \
  --output speech.mp3 \
  --data '{
    "input": "Today is a wonderful day to build something people love!",
    "voice": "helpful woman",
    "response_format": "mp3",
    "sample_rate": 44100,
    "stream": false,
    "model": "MiniMax/MiniMax-M2-5"
  }'
curl -X POST "https://api.together.xyz/v1/audio/transcriptions" \
  -H "Authorization: Bearer $TOGETHER_API_KEY" \
  -F "model=MiniMax/MiniMax-M2-5" \
  -F "language=en" \
  -F "response_format=json" \
  -F "timestamp_granularities=segment"
curl --request POST \
  --url https://api.together.xyz/v2/videos \
  --header "Authorization: Bearer $TOGETHER_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "MiniMax/MiniMax-M2-5",
    "prompt": "some penguins building a snowman"
  }'
curl --request POST \
  --url https://api.together.xyz/v2/videos \
  --header "Authorization: Bearer $TOGETHER_API_KEY" \
  --header "Content-Type: application/json" \
  --data '{
    "model": "MiniMax/MiniMax-M2-5",
    "frame_images": [{"input_image": "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg"}]
  }'

from together import Together

client = Together()

response = client.chat.completions.create(
  model="MiniMax/MiniMax-M2-5",
  messages=[
    {
      "role": "user",
      "content": "What are some fun things to do in New York?"
    }
  ]
)
print(response.choices[0].message.content)
from together import Together

client = Together()

imageCompletion = client.images.generate(
    model="MiniMax/MiniMax-M2-5",
    width=1024,
    height=768,
    steps=28,
    prompt="Draw an anime style version of this image.",
    image_url="https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
)

print(imageCompletion.data[0].url)


from together import Together

client = Together()

response = client.chat.completions.create(
    model="MiniMax/MiniMax-M2-5",
    messages=[{
    	"role": "user",
      "content": [
        {"type": "text", "text": "Describe what you see in this image."},
        {"type": "image_url", "image_url": {"url": "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png"}}
      ]
    }]
)
print(response.choices[0].message.content)

from together import Together

client = Together()
response = client.chat.completions.create(
  model="MiniMax/MiniMax-M2-5",
  messages=[
  	{
	    "role": "user", 
      "content": "Given two binary strings `a` and `b`, return their sum as a binary string"
    }
 ],
)

print(response.choices[0].message.content)

from together import Together

client = Together()

query = "What animals can I find near Peru?"

documents = [
  "The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
  "The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
  "The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
  "The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations.",
]

response = client.rerank.create(
  model="MiniMax/MiniMax-M2-5",
  query=query,
  documents=documents,
  top_n=2
)

for result in response.results:
    print(f"Relevance Score: {result.relevance_score}")

from together import Together

client = Together()

response = client.embeddings.create(
  model = "MiniMax/MiniMax-M2-5",
  input = "Our solar system orbits the Milky Way galaxy at about 515,000 mph"
)

from together import Together

client = Together()

response = client.completions.create(
  model="meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
  prompt="A horse is a horse",
  max_tokens=32,
  temperature=0.1,
  safety_model="MiniMax/MiniMax-M2-5",
)

print(response.choices[0].text)

from together import Together

client = Together()

speech_file_path = "speech.mp3"

response = client.audio.speech.create(
  model="MiniMax/MiniMax-M2-5",
  input="Today is a wonderful day to build something people love!",
  voice="helpful woman",
)
    
response.stream_to_file(speech_file_path)

from together import Together

client = Together()
response = client.audio.transcribe(
    model="MiniMax/MiniMax-M2-5",
    language="en",
    response_format="json",
    timestamp_granularities="segment"
)
print(response.text)
from together import Together

client = Together()

# Create a video generation job
job = client.videos.create(
    prompt="A serene sunset over the ocean with gentle waves",
    model="MiniMax/MiniMax-M2-5"
)
from together import Together

client = Together()

job = client.videos.create(
    model="MiniMax/MiniMax-M2-5",
    frame_images=[
        {
            "input_image": "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg",
        }
    ]
)
import Together from 'together-ai';
const together = new Together();

const completion = await together.chat.completions.create({
  model: 'MiniMax/MiniMax-M2-5',
  messages: [
    {
      role: 'user',
      content: 'What are some fun things to do in New York?'
     }
  ],
});

console.log(completion.choices[0].message.content);
import Together from "together-ai";

const together = new Together();

async function main() {
  const response = await together.images.create({
    model: "MiniMax/MiniMax-M2-5",
    width: 1024,
    height: 1024,
    steps: 28,
    prompt: "Draw an anime style version of this image.",
    image_url: "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png",
  });

  console.log(response.data[0].url);
}

main();

import Together from "together-ai";

const together = new Together();
const imageUrl = "https://huggingface.co/datasets/patrickvonplaten/random_img/resolve/main/yosemite.png";

async function main() {
  const response = await together.chat.completions.create({
    model: "MiniMax/MiniMax-M2-5",
    messages: [{
      role: "user",
      content: [
        { type: "text", text: "Describe what you see in this image." },
        { type: "image_url", image_url: { url: imageUrl } }
      ]
    }]
  });
  
  console.log(response.choices[0]?.message?.content);
}

main();

import Together from "together-ai";

const together = new Together();

async function main() {
  const response = await together.chat.completions.create({
    model: "MiniMax/MiniMax-M2-5",
    messages: [{
      role: "user",
      content: "Given two binary strings `a` and `b`, return their sum as a binary string"
    }]
  });
  
  console.log(response.choices[0]?.message?.content);
}

main();

import Together from "together-ai";

const together = new Together();

const query = "What animals can I find near Peru?";
const documents = [
  "The giant panda (Ailuropoda melanoleuca), also known as the panda bear or simply panda, is a bear species endemic to China.",
  "The llama is a domesticated South American camelid, widely used as a meat and pack animal by Andean cultures since the pre-Columbian era.",
  "The wild Bactrian camel (Camelus ferus) is an endangered species of camel endemic to Northwest China and southwestern Mongolia.",
  "The guanaco is a camelid native to South America, closely related to the llama. Guanacos are one of two wild South American camelids; the other species is the vicuña, which lives at higher elevations."
];

async function main() {
  const response = await together.rerank.create({
    model: "MiniMax/MiniMax-M2-5",
    query: query,
    documents: documents,
    top_n: 2
  });
  
  for (const result of response.results) {
    console.log(`Relevance Score: ${result.relevance_score}`);
  }
}

main();


import Together from "together-ai";

const together = new Together();

const response = await client.embeddings.create({
  model: 'MiniMax/MiniMax-M2-5',
  input: 'Our solar system orbits the Milky Way galaxy at about 515,000 mph',
});

import Together from "together-ai";

const together = new Together();

async function main() {
  const response = await together.completions.create({
    model: "meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8",
    prompt: "A horse is a horse",
    max_tokens: 32,
    temperature: 0.1,
    safety_model: "MiniMax/MiniMax-M2-5"
  });
  
  console.log(response.choices[0]?.text);
}

main();

import Together from 'together-ai';

const together = new Together();

async function generateAudio() {
   const res = await together.audio.create({
    input: 'Today is a wonderful day to build something people love!',
    voice: 'helpful woman',
    response_format: 'mp3',
    sample_rate: 44100,
    stream: false,
    model: 'MiniMax/MiniMax-M2-5',
  });

  if (res.body) {
    console.log(res.body);
    const nodeStream = Readable.from(res.body as ReadableStream);
    const fileStream = createWriteStream('./speech.mp3');

    nodeStream.pipe(fileStream);
  }
}

generateAudio();

import Together from "together-ai";

const together = new Together();

const response = await together.audio.transcriptions.create(
  model: "MiniMax/MiniMax-M2-5",
  language: "en",
  response_format: "json",
  timestamp_granularities: "segment"
});
console.log(response)
import Together from "together-ai";

const together = new Together();

async function main() {
  // Create a video generation job
  const job = await together.videos.create({
    prompt: "A serene sunset over the ocean with gentle waves",
    model: "MiniMax/MiniMax-M2-5"
  });
import Together from "together-ai";

const together = new Together();

const job = await together.videos.create({
  model: "MiniMax/MiniMax-M2-5",
  frame_images: [
    {
      input_image: "https://cdn.pixabay.com/photo/2020/05/20/08/27/cat-5195431_1280.jpg",
    }
  ]
});

How to use MiniMax M2.5

Model details

Architecture Overview:
• SOTA agentic model trained with reinforcement learning across 200,000+ complex real-world environments
• Forge agent-native RL framework with 40x training speedup through asynchronous scheduling and tree-structured sample merging
• CISPO algorithm ensuring MoE model stability during large-scale RL training
• Process reward mechanism for end-to-end generation quality monitoring in long-context agent rollouts
• Optimal trade-off between intelligence and response speed through trajectory-based task completion time evaluation
• Trained on 10+ programming languages: Go, C, C++, TypeScript, Rust, Kotlin, Python, Java, JavaScript, PHP, Lua, Dart, Ruby
• Full-stack platform coverage: Web, Android, iOS, Windows, server-side APIs, business logic, databases

Training Methodology:
• Extensive RL training in hundreds of thousands of real-world coding, search, and office work environments
• Collaboration with senior professionals in finance, law, and social sciences for office deliverables training
• Industry expert-designed requirements, feedback, and standards contributing to data construction
• Architect-level planning emerged during training: spec-writing before coding with feature decomposition
• Trained for efficient reasoning and optimal task decomposition reducing token consumption by 5% vs M2.1
• Full development lifecycle training: 0-to-1 system design, 1-to-10 development, 10-to-90 iteration, 90-to-100 testing

Performance Characteristics:
• Coding Excellence: 80.2% SWE-Bench Verified, 51.3% Multi-SWE-Bench, 79.7% Droid, 76.1% OpenCode
• Agentic Leadership: 76.3% BrowseComp (with context management), 20% fewer search rounds vs M2.1
• Office Deliverables: 59.0% win rate in GDPval-MM evaluation vs mainstream models
• Speed: 37% faster than M2.1 on SWE-Bench Verified (22.8 min vs 31.3 min), matching Claude Opus 4.6
• Cost Efficiency: 10% cost of Claude Opus 4.6 per task, $1/hour continuous operation at 100 TPS
• Token Efficiency: 3.52M tokens/task vs M2.1's 3.72M, 5% reduction through better decomposition
• Additional Benchmarks: 86.3% AIME25, 85.2% GPQA-D, 70.0% IFBench, 44.4% SciCode

Prompting MiniMax M2.5

Applications & Use Cases

Full-Stack Software Development:
• Architect-level planning: Spec-writing with feature decomposition, structure design, and UI planning before coding
• Complete development lifecycle: 0-to-1 system design and environment setup through 90-to-100 comprehensive testing
• 80.2% SWE-Bench Verified, 51.3% Multi-SWE-Bench across 10+ programming languages
• Full-stack platforms: Web, Android, iOS, Windows with server-side APIs, business logic, databases
• Complex system development beyond bug-fixing: feature iteration, code review, system testing
• Multi-environment generalization: 79.7% on Droid, 76.1% on OpenCode with different scaffoldings

Agentic Search & Tool Use:
• Industry-leading performance: 76.3% BrowseComp with context management
• Expert-level search tasks: RISE benchmark evaluating real-world professional research capabilities
• Efficient decision-making: 20% fewer search rounds than M2.1 with better token efficiency
• Precise search rounds with optimal reasoning paths to results
• Stable performance across unfamiliar scaffolding environments
• Deep webpage exploration for information-dense professional tasks

Office Deliverables & Productivity:
• Word documents, PowerPoint presentations, Excel financial models as truly deliverable outputs
• Trained with senior professionals in finance, law, and social sciences
• 59.0% win rate vs mainstream models in GDPval-MM office work evaluation
• Industry-specific tacit knowledge integrated into training pipeline
• High-value workspace scenarios: financial modeling, legal documents, research reports
• Professional trajectory evaluation alongside deliverable quality assessment

Enterprise Coding Agents:
• Autonomous software development at production scale
• Multi-language, multi-platform development workflows
• Integration with Claude Code and major coding agent frameworks
• Repository-scale navigation, refactoring, and comprehensive testing
• Real-world deployment: 80% of MiniMax's newly committed code is M2.5-generated

Knowledge Work Automation:
• Automated research report generation with proper formatting
• Financial model creation following organizational standards
• Legal document preparation with industry compliance
• Presentation creation with professional design standards
• Real-world productivity: 30% of MiniMax company tasks autonomously completed by M2.5

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