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MiniMax · Balanced

MiniMax M1 80K

Added Jan 8, 2025

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Use in the app

MiniMax-M1 with 80K thinking budget. Enhanced version of the hybrid MoE reasoning model with double the thinking capacity. Ideal for extremely complex software engineering, tool use, and long context tasks.

Input
Text
Output
Text
Discovery tier
Balanced

Pricing

USD per 1M tokens
Input
$0.61
Output
$2.42

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
131.1K

Side by side

MiniMax M1 80K compared

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

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MiniMax M1 80KMiniMaxThis modelGPT 5.4 NanoOpenAIRemove
ProviderMiniMaxOpenAI
Discovery tierBalancedEfficient
AddedJan 8, 2025Mar 17, 2026
Limits
Context window1MBest400K
Max output131.07KBest128K
Average output—515 tokens
Pricing, USD per 1M tokens
Input$0.61$0.20Best
Output$2.42$1.25Best
Cache read—$0.02
Performance
Request success (24h)—100.0%
Benchmark indexes
Intelligence Index11.711.7
Math Index61.0—
Capabilities
ReasoningNoYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
PDF inputNoYes
Reasoning effort—none, low, medium, high, xhigh

Public evaluations

Benchmarks

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

  • MiniMax M1 80K
  • GPT 5.4 Nano

Intelligence Index

  • MiniMax M1 80K11.7
  • GPT 5.4 Nano11.7

MiniMax M1 80K: Better than 26% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Math Index

    Composite of the math evaluations

    • MiniMax M1 80K: 61.0
    • GPT 5.4 Nano: —

Document reasoning

  • AA-LCRv1.1

    Reasoning across long documents

    • MiniMax M1 80K: 57.7%Top
    • GPT 5.4 Nano: 29.7%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • MiniMax M1 80K: 8.9%Top
    • GPT 5.4 Nano: 4.1%
  • GPQA Diamond

    Graduate-level science questions

    • MiniMax M1 80K: 69.7%Top
    • GPT 5.4 Nano: 55.8%
  • MMLU-Pro

    Multi-subject knowledge and reasoning

    • MiniMax M1 80K: 81.6%
    • GPT 5.4 Nano: —
  • IFBench

    Following precise output instructions

    • MiniMax M1 80K: 41.8%Top
    • GPT 5.4 Nano: 32.7%

Coding

  • LiveCodeBench

    Recent competitive programming problems

    • MiniMax M1 80K: 71.1%
    • GPT 5.4 Nano: —

Math

  • AIME 2025

    Competition mathematics, 2025 problems

    • MiniMax M1 80K: 61.0%
    • GPT 5.4 Nano: —
  • AIME

    Competition mathematics

    • MiniMax M1 80K: 84.7%
    • GPT 5.4 Nano: —
  • MATH-500

    Competition math problems

    • MiniMax M1 80K: 98.0%
    • GPT 5.4 Nano: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • MiniMax M1 80K: 3.0%
    • GPT 5.4 Nano: 24.2%Top
  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • MiniMax M1 80K: 34.2%
    • GPT 5.4 Nano: 34.8%Top
  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • MiniMax M1 80K: 57.7%Top
    • GPT 5.4 Nano: 29.7%

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

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": "MiniMaxAI/MiniMax-M1-80k",
    "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="MiniMaxAI/MiniMax-M1-80k",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

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