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xiaomi · Open weights

MiMo V2.5

Added Apr 22, 2026Open weights

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Use in the app

MiMo V2.5 is Xiaomi's full-modal understanding model for agent workflows. It supports tool calling, structured outputs, and web search with up to 1M context.

  • Reasoning
  • Tools
  • Vision
  • Structured output
  • Audio input
  • Video input
Input
Text, Images, Video, Audio
Output
Text
Reasoning effort
none · high
Discovery tier
Open weights

Pricing

USD per 1M tokens
Input
$0.14
Output
$0.28
Cache read
$0.0028
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)
458 tokens
Longer than 45% of 468 models

Side by side

MiMo V2.5 compared

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

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MiMo V2.5xiaomiThis modelMiMo V2.6 Flash AbliteratedxiaomiRemove
Providerxiaomixiaomi
Discovery tierOpen weightsOpen weights
AddedApr 22, 2026Sep 25, 2026
Limits
Context window1.05M1.05M
Max output131.07KBest65.54K
Average output458 tokens1.3K tokens
Pricing, USD per 1M tokens
Input$0.14Best$0.50
Output$0.28Best$1.50
Cache read$0.0028Best$0.28
Cache write$0.00—
Performance
Throughput31.4 tok/s164.5 tok/sBest
Time to first token5.7 s1.5 sBest
Request success (24h)100.0%Best98.4%
Benchmark indexes
Intelligence Index21.8—
Coding Index56.8—
Capabilities
ReasoningYesYes
ToolsYesYes
VisionYesYes
Structured outputYesNo
Audio inputYesNo
Video inputYesNo
Reasoning effortnone, highnone, high

Public evaluations

Benchmarks

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

  • MiMo V2.5
  • MiMo V2.6 Flash Abliterated

Intelligence Index

  • MiMo V2.521.8
  • MiMo V2.6 Flash Abliterated—

MiMo V2.5: Better than 52% of 326 scored models

3.8Catalog models by score55.1

Indexes

  • Coding Index

    Composite of the coding evaluations

    • MiMo V2.5: 56.8
    • MiMo V2.6 Flash Abliterated: —

Agentic work

  • AutomationBench-AA

    Workflow automation, penalized for guardrail violations

    • MiMo V2.5: 18.4%
    • MiMo V2.6 Flash Abliterated: —

  • AutomationBench-AA tasks completed

    Workflows finished end to end without a guardrail violation

    • MiMo V2.5: 3.3%
    • MiMo V2.6 Flash Abliterated: —

  • AA-Briefcasev1.1

    Agentic knowledge work, rated head to head

    • MiMo V2.5: 754 Elo
    • MiMo V2.6 Flash Abliterated: —

  • GDPval-AAv2.1

    Economically valuable occupational tasks, rated head to head

    • MiMo V2.5: 996 Elo
    • MiMo V2.6 Flash Abliterated: —

Document reasoning

  • GDP.pdf

    Professional reasoning over PDF documents, all-pass rate

    • MiMo V2.5: 4.0%
    • MiMo V2.6 Flash Abliterated: —

  • AA-LCRv1.1

    Reasoning across long documents

    • MiMo V2.5: 73.0%
    • MiMo V2.6 Flash Abliterated: —

Reasoning and knowledge

  • Humanity’s Last Exam

    Expert-level questions across academic fields

    • MiMo V2.5: 27.2%
    • MiMo V2.6 Flash Abliterated: —

  • GPQA Diamond

    Graduate-level science questions

    • MiMo V2.5: 84.9%
    • MiMo V2.6 Flash Abliterated: —

  • IFBench

    Following precise output instructions

    • MiMo V2.5: 67.1%
    • MiMo V2.6 Flash Abliterated: —

Coding

  • Terminal-Benchv4.0

    Practical software engineering in a terminal

    • MiMo V2.5: 0.0%
    • MiMo V2.6 Flash Abliterated: —

  • SciCode

    Scientific computing in Python

    • MiMo V2.5: 43.9%
    • MiMo V2.6 Flash Abliterated: —

Legacy evaluations

  • Terminal-Bench Hard

    Earlier terminal task suite

    • MiMo V2.5: 41.7%
    • MiMo V2.6 Flash Abliterated: —

  • τ²-Bench Telecom

    Tool use in a customer-support simulation

    • MiMo V2.5: 90.6%
    • MiMo V2.6 Flash Abliterated: —

  • AA-LCR (unversioned)

    Long-context reasoning, earlier grading

    • MiMo V2.5: 73.0%
    • MiMo V2.6 Flash Abliterated: —

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
31.4 tok/s
Faster than 22% of 254 models
Time to first token
5.7 s
Quicker than 31% of 254 models
Prompt cache hits
74.0%
About $0.0384 per 1M input tokens with caching
Request success (24h)
100.0%
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.

Hourly request success · last 72 hoursLowest hour 95.3%
  • 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.

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": "xiaomi/mimo-v2.5",
    "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",
    messages=[{"role": "user", "content": "Explain this stack trace."}],
)
print(reply.choices[0].message.content)

xiaomi

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