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MiniMax · Open weights

MiniMax M2.5

Added Feb 12, 2026Open weights

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Use in the app

MiniMax M2.5 is a productivity-focused flagship model that builds on M2.1 with stronger coding and real-world office workflow performance (Word, Excel, PowerPoint), plus better tool-use planning and token efficiency.

  • Reasoning
  • Tools
  • Structured output
Input
Text
Output
Text
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.27
Output
$1.08
Cache read
$0.027

Reference prices as published by the model provider. API example

Specifications

Context window
204.8K
Max output
131.1K
Average output (7 days)
653 tokens
Longer than 58% of 465 models

Side by side

MiniMax M2.5 compared

Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.

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MiniMax M2.5MiniMaxThis modelNvidia Nemotron 3 Ultra 550BnvidiaRemove
ProviderMiniMaxnvidia
Discovery tierOpen weightsOpen weights
AddedFeb 12, 2026Jun 4, 2026
Limits
Context window204.8K1MBest
Max output131.07KBest65.54K
Average output653 tokens56 tokens
Pricing, USD per 1M tokens
Input$0.27Best$0.50
Output$1.08Best$2.50
Cache read$0.027—
Performance
Throughput110.4 tok/sBest107.6 tok/s
Time to first token1.8 s1.2 sBest
Request success (24h)100.0%100.0%
Benchmark indexes
Intelligence Index22.822.9Best
Coding Index—49.3
Capabilities
ReasoningYesYes
ToolsYesYes
Structured outputYesNo
Parallel toolsNoYes
Reasoning effort——

Public evaluations

Benchmarks

Independent evaluation results, with how each score ranks among the models in the Noumen catalog.

  • MiniMax M2.5
  • Nvidia Nemotron 3 Ultra 550B

Intelligence Index

  • MiniMax M2.522.8
  • Nvidia Nemotron 3 Ultra 550B22.9

MiniMax M2.5: Better than 55% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • MiniMax M2.5: —
    • Nvidia Nemotron 3 Ultra 550B: 49.3

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • MiniMax M2.5: —
    • Nvidia Nemotron 3 Ultra 550B: 3.0%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • MiniMax M2.5: —
    • Nvidia Nemotron 3 Ultra 550B: 0.3%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • MiniMax M2.5: —
    • Nvidia Nemotron 3 Ultra 550B: 876 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • MiniMax M2.5: —
    • Nvidia Nemotron 3 Ultra 550B: 1,013 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • MiniMax M2.5: —
    • Nvidia Nemotron 3 Ultra 550B: 5.0%

  • AA-LCRv1.1

    Reasoning across long documents

    • MiniMax M2.5: 73.3%
    • Nvidia Nemotron 3 Ultra 550B: 79.3%Top

  • MLCR-AA

    Long-context reasoning over medical records

    • MiniMax M2.5: —
    • Nvidia Nemotron 3 Ultra 550B: 5.6%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • MiniMax M2.5: 20.5%
    • Nvidia Nemotron 3 Ultra 550B: 28.4%Top

  • GPQA Diamond

    Graduate-level science questions

    • MiniMax M2.5: 84.8%
    • Nvidia Nemotron 3 Ultra 550B: 86.7%Top

  • IFBench

    Following precise output instructions

    • MiniMax M2.5: 71.6%
    • Nvidia Nemotron 3 Ultra 550B: 81.4%Top

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • MiniMax M2.5: —
    • Nvidia Nemotron 3 Ultra 550B: 0.5%

  • SciCode

    Scientific computing in Python

    • MiniMax M2.5: —
    • Nvidia Nemotron 3 Ultra 550B: 40.3%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • MiniMax M2.5: 34.8%
    • Nvidia Nemotron 3 Ultra 550B: 36.4%Top

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • MiniMax M2.5: 95.3%Top
    • Nvidia Nemotron 3 Ultra 550B: 83.3%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • MiniMax M2.5: 73.3%
    • Nvidia Nemotron 3 Ultra 550B: 79.3%Top

Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis

Live routing data

Performance and reliability

Recent averages across requests routed for this model. Your own speed depends on prompt length, reasoning effort and load.

Throughput
110.4 tok/s
Faster than 65% of 251 models
Time to first token
1.8 s
Quicker than 80% of 251 models
Prompt cache hits
2.9%
About $0.26 per 1M input tokens with caching
Request success (24h)
100.0%
Reliable

Cache hits are the share of input tokens recently served from a prompt cache across all requests. They are not a forecast of your own hit rate.

Hourly request success · last 72 hoursLowest hour 16.6%
  • Healthy (98% or more)
  • Degraded (90–98%)
  • Down (under 90%)
  • No requests

Developers

Use it through the API

Noumen’s API is OpenAI-compatible: any Chat Completions client works with a base URL and a key.

Read the quickstart
curl https://www.noumen.xyz/api/v1/chat/completions \
  -H "Authorization: Bearer $NOUMEN_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "minimax/minimax-m2.5",
    "messages": [{ "role": "user", "content": "Explain this stack trace." }]
  }'
import os
from openai import OpenAI

client = OpenAI(base_url="https://www.noumen.xyz/api/v1", api_key=os.environ["NOUMEN_API_KEY"])
reply = client.chat.completions.create(
    model="minimax/minimax-m2.5",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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