MiniMax · Balanced
MiniMax M2-her
Dialogue-focused MiniMax model optimized for role-playing and multi-turn conversations with rich role settings.
- Input
- Text
- Output
- Text
- Discovery tier
- Balanced
Pricing
USD per 1M tokens- Input
- $0.30
- Output
- $1.21
Reference prices as published by the model provider. API example
Specifications
- Context window
- 65.5K
- Max output
- 2K
- Average output (7 days)
- 186 tokens
- Longer than 20% of 468 models
Side by side
MiniMax M2-her compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| MiniMax M2-herMiniMaxThis model | MiniMax LatestMiniMaxRemove | |
|---|---|---|
| Provider | MiniMax | MiniMax |
| Discovery tier | Balanced | Open weights |
| Added | Jan 12, 2025 | May 3, 2026 |
| Limits | ||
| Context window | 65.53K | 512KBest |
| Max output | 2.05K | 80KBest |
| Average output | 186 tokens | — |
| Pricing, USD per 1M tokens | ||
| Input | $0.30 | $0.23Best |
| Output | $1.21 | $0.96Best |
| Cache read | — | $0.05 |
| Performance | ||
| Throughput | — | 127.0 tok/s |
| Time to first token | — | 1.1 s |
| Request success (24h) | — | 99.9% |
| Benchmark indexes | ||
| Intelligence Index | — | 29.2 |
| Coding Index | — | 58.6 |
| Capabilities | ||
| Reasoning | No | Yes |
| Tools | No | Yes |
| Vision | No | Yes |
| Structured output | No | Yes |
| Reasoning effort | — | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- MiniMax M2-her
- MiniMax Latest
Intelligence Index
- MiniMax M2-her—
- MiniMax Latest29.2
Indexes
Coding Index
Composite of the coding evaluations
- MiniMax M2-her: —
- MiniMax Latest: 58.6
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- MiniMax M2-her: —
- MiniMax Latest: 21.3%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- MiniMax M2-her: —
- MiniMax Latest: 4.4%
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- MiniMax M2-her: —
- MiniMax Latest: 0.0%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- MiniMax M2-her: —
- MiniMax Latest: 1,089 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- MiniMax M2-her: —
- MiniMax Latest: 1,243 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- MiniMax M2-her: —
- MiniMax Latest: 9.8%
AA-LCRv1.1
Reasoning across long documents
- MiniMax M2-her: —
- MiniMax Latest: 83.0%
MLCR-AA
Long-context reasoning over medical records
- MiniMax M2-her: —
- MiniMax Latest: 4.4%
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- MiniMax M2-her: —
- MiniMax Latest: 39.0%
GPQA Diamond
Graduate-level science questions
- MiniMax M2-her: —
- MiniMax Latest: 92.9%
IFBench
Following precise output instructions
- MiniMax M2-her: —
- MiniMax Latest: 82.9%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- MiniMax M2-her: —
- MiniMax Latest: 2.0%
SciCode
Scientific computing in Python
- MiniMax M2-her: —
- MiniMax Latest: 47.1%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- MiniMax M2-her: —
- MiniMax Latest: 42.4%
τ²-Bench Telecom
Tool use in a customer-support simulation
- MiniMax M2-her: —
- MiniMax Latest: 88.9%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- MiniMax M2-her: —
- MiniMax Latest: 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.
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-her",
"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-her",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)MiniMax
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