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MiniMax · Efficient

MiniMax M3.1 Flash

Added Oct 19, 2026

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Use in the app

MiniMax M3.1 Flash is a multimodal model for coding, tool use, and long-context work. It accepts text, images, and video and produces text, with a 1,000,000-token context window and up to 524,288 output tokens within the remaining context. Thinking is always enabled, with low, medium, high, xhigh, and max effort levels; max is the default. Thinking tokens count toward the output limit. Temperature is fixed at 1 and top-p at 0.95; custom values have no effect.

  • Reasoning
  • Tools
  • Vision
  • Video input
Input
Text, Images, Video
Output
Text
Reasoning effort
low · medium · high · xhigh · max
Discovery tier
Efficient

Pricing

USD per 1M tokens
Input
$0.15
Output
$0.60
Cache read
$0.015

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
524.3K
Average output (7 days)
1.4K tokens
Longer than 82% of 465 models

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TryGPT 5.6 TerraClaude Haiku 5.5Kimi K3 TEEAll 3

Public evaluations

Benchmarks

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

Intelligence Index

42.7

Better than 88% of 326 scored models

3.8Catalog models by score55.1

Agentic work

  • AutomationBench-AA

    72.5%

    Workflow automation, penalized for guardrail violations

    Better than 97% of 173 scored models

  • AutomationBench-AA tasks completed

    38.1%

    Workflows finished end to end without a guardrail violation

    Better than 97% of 173 scored models

  • AA-Briefcasev1.1

    1,473 Elo

    Agentic knowledge work, rated head to head

    Better than 80% of 166 scored models

  • GDPval-AAv2.1

    1,458 Elo

    Economically valuable occupational tasks, rated head to head

    Better than 74% of 187 scored models

Document reasoning

  • GDP.pdf

    20.8%

    Professional reasoning over PDF documents, all-pass rate

    Better than 77% of 171 scored models

  • AA-LCRv1.1

    79.7%

    Reasoning across long documents

    Better than 75% of 309 scored models

  • MLCR-AA

    16.7%

    Long-context reasoning over medical records

    Better than 69% of 121 scored models

Reasoning and knowledge

  • Humanity’s Last Exam

    48.0%

    Expert-level questions across academic fields

    Better than 92% of 323 scored models

Coding

  • Terminal-Benchv4.0

    25.8%

    Practical software engineering in a terminal

    Better than 77% of 171 scored models

  • SciCode

    53.4%

    Scientific computing in Python

    Better than 63% of 174 scored models

Legacy evaluations

  • AA-LCR (unversioned)

    79.7%

    Long-context reasoning, earlier grading

    Better than 75% of 309 scored models

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
113.1 tok/s
Faster than 66% of 251 models
Time to first token
2.0 s
Quicker than 78% of 251 models
Prompt cache hits
74.3%
About $0.0496 per 1M input tokens with caching
Request success (24h)
99.5%
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 0.0%
  • 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-m3.1-flash",
    "reasoning_effort": "medium",
    "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-m3.1-flash",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

MiniMax

Other MiniMax models, starting with the same family.