MiniMax · Open weights
MiniMax M2.1
MiniMax M2.1 builds on M2 with enhanced context understanding and improved complex tool use. 230B parameter MoE model (10B active) optimized for agentic workflows and long-horizon tasks.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.30
- Output
- $1.20
- Cache read
- $0.03
Reference prices as published by the model provider. API example
Specifications
- Context window
- 200K
- Max output
- 131.1K
- Average output (7 days)
- 359 tokens
- Longer than 37% of 465 models
Side by side
MiniMax M2.1 compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| MiniMax M2.1MiniMaxThis model | GPT 5.1 Codex MiniOpenAIRemove | |
|---|---|---|
| Provider | MiniMax | OpenAI |
| Discovery tier | Open weights | Efficient |
| Added | Jan 20, 2025 | Nov 13, 2025 |
| Limits | ||
| Context window | 200K | 400KBest |
| Max output | 131.07KBest | 128K |
| Average output | 359 tokens | 136 tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.30 | $0.25Best |
| Output | $1.20Best | $2.00 |
| Cache read | $0.03 | $0.025Best |
| Benchmark indexes | ||
| Intelligence Index | 20.9Best | 20.4 |
| Math Index | 82.7 | 91.7Best |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | No |
| Vision | No | Yes |
| Structured output | Yes | No |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- MiniMax M2.1
- GPT 5.1 Codex Mini
Intelligence Index
- MiniMax M2.120.9
- GPT 5.1 Codex Mini20.4
MiniMax M2.1: Better than 51% of 326 scored models
Indexes
Math Index
Composite of the math evaluations
- MiniMax M2.1: 82.7
- GPT 5.1 Codex Mini: 91.7Top
Document reasoning
AA-LCRv1.1
Reasoning across long documents
- MiniMax M2.1: 67.7%Top
- GPT 5.1 Codex Mini: 66.7%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- MiniMax M2.1: 23.2%Top
- GPT 5.1 Codex Mini: 18.5%
GPQA Diamond
Graduate-level science questions
- MiniMax M2.1: 83.0%Top
- GPT 5.1 Codex Mini: 81.3%
MMLU-Pro
Multi-subject knowledge and reasoning
- MiniMax M2.1: 87.5%Top
- GPT 5.1 Codex Mini: 82.0%
IFBench
Following precise output instructions
- MiniMax M2.1: 69.9%Top
- GPT 5.1 Codex Mini: 67.9%
Coding
LiveCodeBench
Recent competitive programming problems
- MiniMax M2.1: 81.0%
- GPT 5.1 Codex Mini: 83.6%Top
Math
AIME 2025
Competition mathematics, 2025 problems
- MiniMax M2.1: 82.7%
- GPT 5.1 Codex Mini: 91.7%Top
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- MiniMax M2.1: 28.8%
- GPT 5.1 Codex Mini: 33.3%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- MiniMax M2.1: 85.4%Top
- GPT 5.1 Codex Mini: 62.9%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- MiniMax M2.1: 67.7%Top
- GPT 5.1 Codex Mini: 66.7%
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.
curl https://www.noumen.xyz/api/v1/chat/completions \
-H "Authorization: Bearer $NOUMEN_API_KEY" \
-H "Content-Type: application/json" \
-d '{
"model": "minimax/minimax-m2.1",
"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-m2.1",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)MiniMax
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