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MiniMax · Efficient

MiniMax 01

Added Jan 1, 2024

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Use in the app

MiniMax's flagship model with a 1M token context window

  • PDF input
Input
Text
Output
Text
Discovery tier
Efficient

Pricing

USD per 1M tokens
Input
$0.14
Output
$1.12

Reference prices as published by the model provider. API example

Specifications

Context window
1M
Max output
16.4K

Side by side

MiniMax 01 compared

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

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MiniMax 01MiniMaxThis modelMiniMax M3 ThinkingMiniMaxRemove
ProviderMiniMaxMiniMax
Discovery tierEfficientOpen weights
AddedJan 1, 2024Jun 1, 2026
Limits
Context window1MBest512K
Max output16.38K80KBest
Average output—1.9K tokens
Pricing, USD per 1M tokens
Input$0.14Best$0.23
Output$1.12$0.96Best
Cache read—$0.05
Performance
Throughput—185.0 tok/s
Time to first token—7.3 s
Request success (24h)—99.9%
Benchmark indexes
Intelligence Index—29.2
Coding Index—58.6
Capabilities
ReasoningNoYes
ToolsNoYes
VisionNoYes
Structured outputNoYes
PDF inputYesNo
Reasoning effort——

Public evaluations

Benchmarks

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

  • MiniMax 01
  • MiniMax M3 Thinking

Intelligence Index

  • MiniMax 01—
  • MiniMax M3 Thinking29.2
3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • MiniMax 01: —
    • MiniMax M3 Thinking: 58.6

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • MiniMax 01: —
    • MiniMax M3 Thinking: 21.3%

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • MiniMax 01: —
    • MiniMax M3 Thinking: 4.4%

  • Harvey LAB-AAv1.1

    Legal tasks passed in full, with no material hallucination

    • MiniMax 01: —
    • MiniMax M3 Thinking: 0.0%

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • MiniMax 01: —
    • MiniMax M3 Thinking: 1,089 Elo

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • MiniMax 01: —
    • MiniMax M3 Thinking: 1,243 Elo

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • MiniMax 01: —
    • MiniMax M3 Thinking: 9.8%

  • AA-LCRv1.1

    Reasoning across long documents

    • MiniMax 01: —
    • MiniMax M3 Thinking: 83.0%

  • MLCR-AA

    Long-context reasoning over medical records

    • MiniMax 01: —
    • MiniMax M3 Thinking: 4.4%

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • MiniMax 01: —
    • MiniMax M3 Thinking: 39.0%

  • GPQA Diamond

    Graduate-level science questions

    • MiniMax 01: —
    • MiniMax M3 Thinking: 92.9%

  • IFBench

    Following precise output instructions

    • MiniMax 01: —
    • MiniMax M3 Thinking: 82.9%

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • MiniMax 01: —
    • MiniMax M3 Thinking: 2.0%

  • SciCode

    Scientific computing in Python

    • MiniMax 01: —
    • MiniMax M3 Thinking: 47.1%

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • MiniMax 01: —
    • MiniMax M3 Thinking: 42.4%

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • MiniMax 01: —
    • MiniMax M3 Thinking: 88.9%

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • MiniMax 01: —
    • MiniMax M3 Thinking: 83.0%

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": "minimax/minimax-01",
    "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-01",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

MiniMax

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