MiniMax · Efficient
MiniMax M3.1 Flash
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 468 models
Side by side
MiniMax M3.1 Flash compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| MiniMax M3.1 FlashMiniMaxThis model | Claude Haiku 5.5AnthropicRemove | |
|---|---|---|
| Provider | MiniMax | Anthropic |
| Discovery tier | Efficient | Efficient |
| Added | Oct 19, 2026 | Oct 7, 2026 |
| Limits | ||
| Context window | 1.05MBest | 1M |
| Max output | 524.29KBest | 128K |
| Average output | 1.4K tokens | 1.5K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.15 | $0.10Best |
| Output | $0.60 | $0.50Best |
| Cache read | $0.015 | $0.01Best |
| Cache write | — | $0.13 |
| Performance | ||
| Throughput | 119.8 tok/s | 274.2 tok/sBest |
| Time to first token | 7.0 s | 4.2 sBest |
| Request success (24h) | 99.7% | 99.9%Best |
| Benchmark indexes | ||
| Intelligence Index | 42.7 | 43.4Best |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | Yes | Yes |
| Structured output | No | Yes |
| PDF input | No | Yes |
| Video input | Yes | No |
| Reasoning effort | low, medium, high, xhigh, max | low, medium, high, xhigh, max |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- MiniMax M3.1 Flash
- Claude Haiku 5.5
Intelligence Index
- MiniMax M3.1 Flash42.7
- Claude Haiku 5.543.4
MiniMax M3.1 Flash: Better than 88% of 326 scored models
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- MiniMax M3.1 Flash: 72.5%Top
- Claude Haiku 5.5: 35.4%
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- MiniMax M3.1 Flash: 38.1%Top
- Claude Haiku 5.5: 13.9%
Harvey LAB-AAv1.1
Legal tasks passed in full, with no material hallucination
- MiniMax M3.1 Flash: —
- Claude Haiku 5.5: 0.6%
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- MiniMax M3.1 Flash: 1,473 Elo
- Claude Haiku 5.5: 1,575 EloTop
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- MiniMax M3.1 Flash: 1,458 Elo
- Claude Haiku 5.5: 1,619 EloTop
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- MiniMax M3.1 Flash: 20.8%Top
- Claude Haiku 5.5: 20.8%Top
AA-LCRv1.1
Reasoning across long documents
- MiniMax M3.1 Flash: 79.7%
- Claude Haiku 5.5: 82.7%Top
MLCR-AA
Long-context reasoning over medical records
- MiniMax M3.1 Flash: 16.7%
- Claude Haiku 5.5: 35.0%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- MiniMax M3.1 Flash: 48.0%Top
- Claude Haiku 5.5: 44.4%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- MiniMax M3.1 Flash: 25.8%
- Claude Haiku 5.5: 32.8%Top
SciCode
Scientific computing in Python
- MiniMax M3.1 Flash: 53.4%
- Claude Haiku 5.5: 55.0%Top
Legacy evaluations
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- MiniMax M3.1 Flash: 79.7%
- Claude Haiku 5.5: 82.7%Top
Scores from Artificial Analysis, updated Oct 26, 2026. Artificial Analysis
- MiniMax M3.1 Flash
- Claude Haiku 5.5
| Leaderboard | MiniMax M3.1 Flash | Claude Haiku 5.5 |
|---|---|---|
| FrontierCode Main | Not in top 20 | #14 · 46.4% |
| FrontierCode Extended | Not in top 20 | #14 · 58.4% |
Ranks among Noumen catalog models on FrontierCode leaderboards. Only top-20 placements are listed.FrontierCode
- MiniMax M3.1 Flash
- Claude Haiku 5.5
| Leaderboard | MiniMax M3.1 Flash | Claude Haiku 5.5 |
|---|---|---|
| Epoch Capabilities Index | Not in top 20 | #15 · 159.3 |
Ranks among Noumen catalog models on Epoch AI leaderboards. Only top-20 placements are listed.Epoch AI
- MiniMax M3.1 Flash
- Claude Haiku 5.5
| Leaderboard | MiniMax M3.1 Flash | Claude Haiku 5.5 |
|---|---|---|
| ARC-AGI-3 (Default harness) | Not in top 20 | #13 · 0.5% |
Ranks among Noumen catalog models on ARC Prize leaderboards. Only top-20 placements are listed.ARC Prize
- MiniMax M3.1 Flash
- Claude Haiku 5.5
| Leaderboard | MiniMax M3.1 Flash | Claude Haiku 5.5 |
|---|---|---|
| Game Development | Not in top 20 | #15 · 1325 |
| Data Visualization | Not in top 20 | #15 · 1294 |
| 3D | Not in top 20 | #14 · 1344 |
Ranks among Noumen catalog models on Design Arena leaderboards. Only top-20 placements are listed.Design Arena
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
- 119.8 tok/s
- Faster than 68% of 254 models
- Time to first token
- 7.0 s
- Quicker than 22% of 254 models
- Prompt cache hits
- 78.4%
- About $0.0441 per 1M input tokens with caching
- Request success (24h)
- 99.7%
- 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.
- 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.
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
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