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MiniMax-M2.7

Input:$0.24/M
Output:$0.96/M
Released:Mar 18, 2026

MiniMax-M2.7 offers the same top-tier intelligence as the standard versionโ€”including recursive self-evolution and expert-level office productivityโ€”but is designed for applications requiring sub-second latency and high-speed token generation. Leveraging an enhanced inference backbone architecture, its output speed is 66% faster than the standard model (reaching 100 tps). It is the preferred choice for interactive programming assistants, real-time agent loop execution, and high-throughput enterprise pipelines with stringent completion time requirements.

New
Commercial Use

Playground for MiniMax-M2.7

Explore MiniMax-M2.7's Playground โ€” an interactive environment to test models, run queries in real time. Try prompts, adjust parameters, and iterate instantly to accelerate development and validate use cases.

Technical specifications of MiniMax-M2.7 API

ItemDetails
Model nameMiniMax-M2.7
Model IDminimax-m2.7
ProviderMiniMax
Model familyMiniMax text models
Input typeText
Output typeText
Context window204,800 tokens
Official speed note~60 tps for MiniMax-M2.7; ~100 tps for MiniMax-M2.7-highspeed
Primary strengthsProgramming, tool calling, search, office productivity, agent workflows
AvailabilityMiniMax API / text generation endpoints
Public multimodal spec on reviewed pagesNot published on the text-model pages reviewed

What is MiniMax-M2.7?

MiniMax-M2.7 is MiniMaxโ€™s current flagship text model for demanding coding, agent, and productivity workflows. The official docs position it as a model for multilingual programming, tool calling, search, and complex task execution, while the MiniMax model page highlights gains in real-world software engineering, office editing, and complex environment interaction.

Main features of MiniMax-M2.7

  • Strong software engineering performance for end-to-end delivery, log analysis, bug troubleshooting, code security, and machine learning tasks.
  • Large 204,800-token context window for long prompts, multi-file work, and extended agent sessions.
  • Strong office workflow support, including complex edits in Excel, PowerPoint, and Word.
  • Tool-calling and search-oriented behavior for agentic API workflows.
  • Broad integration support in popular coding tools such as Claude Code, OpenCode, Kilo Code, Cline, Roo Code, Grok CLI, and Codex CLI.

Benchmark performance of MiniMax-M2.7

The official MiniMax materials published the following benchmark claims for M2.7:

BenchmarkReported resultWhat it suggests
SWE-Pro56.22%Strong real-world software engineering performance
VIBE-Pro55.6%Full-project delivery capability
Terminal Bench 257.0%Strong understanding of complex engineering systems
GDPval-AAELO 1495Strong office-task performance and high-fidelity editing
Complex skills (>2,000 tokens)97% skill adherenceGood reliability in long, structured workflows

How MiniMax-M2.7 compares with nearby MiniMax models

ModelPositioningContext windowSpeed noteBest fit
MiniMax-M2.7Current flagship text model204,800~60 tpsHighest-end coding, tool use, search, and office tasks
MiniMax-M2.7-highspeed(coming soon in CometAPI)Faster variant of M2.7204,800~100 tpsSame capability profile when latency matters more
MiniMax-M2.5Prior high-end text model204,800~60 tpsStrong coding/productivity when M2.7 is not required
MiniMax-M2Efficient coding and agent workflows204,800Official docs list the model, but not the same M2.7 positioningCost-conscious agentic coding and general workflow automation

Best use cases for MiniMax-M2.7 API

  1. Large codebase refactoring and multi-file implementation work.
  2. Agentic debugging loops that require planning, search, and tool use.
  3. Office document generation and revision workflows in Word, Excel, and PowerPoint.
  4. Terminal-heavy automation where the model needs to reason across logs and build outputs.
  5. Search-assisted tasks that benefit from long context and multi-step reasoning.

If you are choosing between MiniMax models, use M2.7 when you want the strongest public text-model positioning for engineering, tool use, search, and office editing. Use M2.5 or M2 when you want a nearby family member with a different performance or workflow tradeoff.

How to access MiniMax-2.7 API

Step 1: Sign Up for API Key

Log in to cometapi.com. If you are not our user yet, please register first. Sign into your CometAPI console. Get the access credential API key of the interface. Click โ€œAdd Tokenโ€ at the API token in the personal center, get the token key: sk-xxxxx and submit.

cometapi-key

Step 2: Send Requests to MiniMax-2.7 API

Select the โ€œminimax-2.7โ€ endpoint to send the API request and set the request body. The request method and request body are obtained from our website API doc. Our website also provides Apifox test for your convenience. Replace <YOUR_API_KEY> with your actual CometAPI key from your account. base url is Chat Completions .

Insert your question or request into the content fieldโ€”this is what the model will respond to . Process the API response to get the generated answer.

Step 3: Retrieve and Verify Results

Process the API response to get the generated answer. After processing, the API responds with the task status and output data.

FAQ

Pricing for MiniMax-M2.7

Explore competitive pricing for MiniMax-M2.7, designed to fit various budgets and usage needs. Our flexible plans ensure you only pay for what you use, making it easy to scale as your requirements grow. Discover how MiniMax-M2.7 can enhance your projects while keeping costs manageable.

Comet Price (USD / M Tokens)Official Price (USD / M Tokens)Discount
Input:$0.24/M
Output:$0.96/M
Input:$0.3/M
Output:$1.2/M
-20%

Sample code and API for MiniMax-M2.7

Access comprehensive sample code and API resources for MiniMax-M2.7 to streamline your integration process. Our detailed documentation provides step-by-step guidance, helping you leverage the full potential of MiniMax-M2.7 in your projects.

# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"
curl https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "minimax-m2.7",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }'

cURL Code Example

# Get your CometAPI key from https://api.cometapi.com/console/token
# Export it as: export COMETAPI_KEY="your-key-here"
curl https://api.cometapi.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $COMETAPI_KEY" \
  -d '{
    "model": "minimax-m2.7",
    "messages": [
      {
        "role": "system",
        "content": "You are a helpful assistant."
      },
      {
        "role": "user",
        "content": "Hello!"
      }
    ]
  }'

Python Code Example

from openai import OpenAI
import os

# Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
COMETAPI_KEY = os.environ.get("COMETAPI_KEY") or "<YOUR_COMETAPI_KEY>"
BASE_URL = "https://api.cometapi.com/v1"

client = OpenAI(base_url=BASE_URL, api_key=COMETAPI_KEY)

completion = client.chat.completions.create(
    model="minimax-m2.7",
    messages=[
        {"role": "system", "content": "You are a helpful assistant."},
        {"role": "user", "content": "Hello!"},
    ],
)

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

JavaScript Code Example

import OpenAI from "openai";

// Get your CometAPI key from https://api.cometapi.com/console/token, and paste it here
const api_key = process.env.COMETAPI_KEY || "<YOUR_COMETAPI_KEY>";
const base_url = "https://api.cometapi.com/v1";

const openai = new OpenAI({
  apiKey: api_key,
  baseURL: base_url,
});

const completion = await openai.chat.completions.create({
  model: "minimax-m2.7",
  messages: [
    { role: "system", content: "You are a helpful assistant." },
    { role: "user", content: "Hello!" },
  ],
});

console.log(completion.choices[0].message.content);

Uptime

Request success rate over the last 30 days, reflecting the reliability of each model provider. CometAPI monitors all connected providers in real time, 24/7.

RespondLIVE
728msAvg. Response
UptimeLIVE
100.0%Avg. Uptime