xiaomi · Open weights
MiMo V2.5 Pro Thinking
MiMo V2.5 Pro with Xiaomi thinking enabled for coding, long-context reasoning, and agentic orchestration.
- Reasoning
- Tools
- Structured output
- Input
- Text
- Output
- Text
- Reasoning effort
- none · high
- Discovery tier
- Open weights
Pricing
USD per 1M tokens- Input
- $0.44
- Output
- $0.87
- Cache read
- $0.0036
- Cache write
- $0.00
Reference prices as published by the model provider. API example
Specifications
- Context window
- 1M
- Max output
- 131.1K
- Average output (7 days)
- 1.4K tokens
- Longer than 84% of 465 models
Side by side
MiMo V2.5 Pro Thinking compared
Specifications, prices, speed and benchmark scores next to each other. Benchmarks below show every compared model too.
| MiMo V2.5 Pro ThinkingxiaomiThis model | Kimi K2.7 Code TEEMoonshotRemove | |
|---|---|---|
| Provider | xiaomi | Moonshot |
| Discovery tier | Open weights | Open weights |
| Added | Jun 3, 2026 | Aug 15, 2026 |
| Limits | ||
| Context window | 1.05MBest | 262.14K |
| Max output | 131.07KBest | 65.54K |
| Average output | 1.4K tokens | 1.1K tokens |
| Pricing, USD per 1M tokens | ||
| Input | $0.44Best | $0.95 |
| Output | $0.87Best | $4.00 |
| Cache read | $0.0036Best | $0.19 |
| Cache write | $0.00 | — |
| Performance | ||
| Throughput | 25.9 tok/s | — |
| Time to first token | 5.5 s | — |
| Request success (24h) | 99.9% | — |
| Benchmark indexes | ||
| Intelligence Index | 26.0Best | 25.8 |
| Coding Index | 60.2 | 60.8Best |
| Capabilities | ||
| Reasoning | Yes | Yes |
| Tools | Yes | Yes |
| Vision | No | Yes |
| Structured output | Yes | No |
| Parallel tools | No | Yes |
| Reasoning effort | none, high | — |
Public evaluations
Benchmarks
Independent evaluation results, with how each score ranks among the models in the Noumen catalog.
- MiMo V2.5 Pro Thinking
- Kimi K2.7 Code TEE
Intelligence Index
- MiMo V2.5 Pro Thinking26.0
- Kimi K2.7 Code TEE25.8
MiMo V2.5 Pro Thinking: Better than 64% of 326 scored models
Indexes
Coding Index
Composite of the coding evaluations
- MiMo V2.5 Pro Thinking: 60.2
- Kimi K2.7 Code TEE: 60.8Top
Agentic work
AutomationBench-AA
Workflow automation, penalized for guardrail violations
- MiMo V2.5 Pro Thinking: 13.7%
- Kimi K2.7 Code TEE: 24.5%Top
AutomationBench-AA tasks completed
Workflows finished end to end without a guardrail violation
- MiMo V2.5 Pro Thinking: 2.0%
- Kimi K2.7 Code TEE: 4.7%Top
AA-Briefcasev1.1
Agentic knowledge work, rated head to head
- MiMo V2.5 Pro Thinking: 883 EloTop
- Kimi K2.7 Code TEE: 858 Elo
GDPval-AAv2.1
Economically valuable occupational tasks, rated head to head
- MiMo V2.5 Pro Thinking: 1,121 EloTop
- Kimi K2.7 Code TEE: 1,038 Elo
Document reasoning
GDP.pdf
Professional reasoning over PDF documents, all-pass rate
- MiMo V2.5 Pro Thinking: 4.0%
- Kimi K2.7 Code TEE: 11.2%Top
AA-LCRv1.1
Reasoning across long documents
- MiMo V2.5 Pro Thinking: 79.7%Top
- Kimi K2.7 Code TEE: 79.3%
MLCR-AA
Long-context reasoning over medical records
- MiMo V2.5 Pro Thinking: 5.6%
- Kimi K2.7 Code TEE: 12.2%Top
Reasoning and knowledge
Humanity’s Last Exam
Expert-level questions across academic fields
- MiMo V2.5 Pro Thinking: 35.7%Top
- Kimi K2.7 Code TEE: 35.0%
GPQA Diamond
Graduate-level science questions
- MiMo V2.5 Pro Thinking: 86.6%
- Kimi K2.7 Code TEE: 89.6%Top
IFBench
Following precise output instructions
- MiMo V2.5 Pro Thinking: 79.9%Top
- Kimi K2.7 Code TEE: 63.1%
Coding
Terminal-Benchv4.0
Practical software engineering in a terminal
- MiMo V2.5 Pro Thinking: 0.0%
- Kimi K2.7 Code TEE: 1.0%Top
SciCode
Scientific computing in Python
- MiMo V2.5 Pro Thinking: 50.6%Top
- Kimi K2.7 Code TEE: 47.8%
Legacy evaluations
Terminal-Bench Hard
Earlier terminal task suite
- MiMo V2.5 Pro Thinking: 43.2%
- Kimi K2.7 Code TEE: 44.7%Top
τ²-Bench Telecom
Tool use in a customer-support simulation
- MiMo V2.5 Pro Thinking: 94.2%Top
- Kimi K2.7 Code TEE: 90.1%
AA-LCR (unversioned)
Long-context reasoning, earlier grading
- MiMo V2.5 Pro Thinking: 79.7%Top
- Kimi K2.7 Code TEE: 79.3%
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
- 25.9 tok/s
- Faster than 16% of 250 models
- Time to first token
- 5.5 s
- Quicker than 30% of 250 models
- Prompt cache hits
- 57.1%
- About $0.19 per 1M input tokens with caching
- Request success (24h)
- 99.9%
- 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": "xiaomi/mimo-v2.5-pro:thinking",
"reasoning_effort": "none",
"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="xiaomi/mimo-v2.5-pro:thinking",
messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)xiaomi
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