Model profile
Xiaomi
New in 2026

Xiaomi: MiMo-V2.5

Xiaomi: MiMo-V2.5 is a budget-priced multimodal generalist from Xiaomi with heavy runtime profile, large context posture, and the clearest fit around long-context research / multimodal.

Best for: Long-context research / MultimodalHeavy latencyLarge contextBudget pricing
Intelligence
38.0

Benchmark blend

Coding
56.8

Dev workflow signal

Context
1050K Tokens

Large

Input Price
$0.14

Budget tier

Decision snapshot
57

Xiaomi: MiMo-V2.5 currently reads as a budget multimodal option with large context and a heavy runtime profile.

Overall profile
Selective fit
Best for
Long-context research / Multimodal
Latency tier
Heavy
Price tier
Budget
Source coverage
OpenRouterArtificial AnalysisVision signal

Decision Strip

Decision rail before the raw tables

Core buy-side signals stay in one pass. The rest of the page expands only after intelligence, speed, context, and price are clear.

Intelligence
38.0
38

General reasoning and benchmark headroom.

Limited
Speed
61 tok/s
27

TTFT 3.60s

Limited
Context
1050K Tokens
100

How much prompt and task state can stay in view.

Above average
Price
$0.14
86

$0.28 output / 1M

Efficient

Editorial Profile

Xiaomi: MiMo-V2.5 in one narrative

Positioning, tradeoffs, and fit are consolidated into one read instead of repeating the same story across separate cards.

Selective fitCoding score 57Math score N/AVision enabled

MiMo-V2.5 is a native omnimodal model by Xiaomi. It delivers Pro-level agentic performance at roughly half the inference cost, while surpassing MiMo-V2-Omni in multimodal perception across image and video understanding...

Identity

Xiaomi multimodal profile

Positioning

Long-context research / Multimodal with large context and heavy runtime.

Cost posture

Efficient spend profile. More comfortable for sustained prompt volume if the capability fit is right.

Strengths
  • Large context headroom supports repo-wide prompts and long research sessions.

  • Vision-capable routing opens up multimodal review and extraction workflows.

Tradeoffs
  • Budget-friendly input pricing is a strength, but raw capability may vary by workload.

  • Latency profile is better for deliberate runs than rapid back-and-forth chat.

Best fit
  • Image-grounded review, multimodal extraction, and UI audit workflows.

  • Long-context summarization, repo analysis, and policy or document review.

Explore Next

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Xiaomi: MiMo-V2.5-Pro

Intelligence
42.9
Context
1050K Tokens
Input Price
$0.43
Xiaomi

MiMo-V2-Pro

Intelligence
41.4
Context
N/A
Input Price
$0.00
Xiaomi

MiMo-V2-Omni-0327

Intelligence
37.3
Context
N/A
Input Price
$0.00

Benchmarks

Grouped by job-to-be-done

Only benchmark categories with actual signal are shown. Secondary values stay as simple definitions instead of nested micro-cards.

General intelligence

Broad reasoning, knowledge depth, and flagship benchmark posture.

Intelligence Index
38.0
GPQA
84.9%
HLE
27.2%
Coding

Software implementation, debugging quality, and coding benchmark signal.

Coding Index
56.8
SciCode
43.1%
Agent / tool use

Long-horizon execution quality and interactive benchmark evidence.

IFBench
67.1%
TAU2
90.6%
TerminalBench Hard
41.7%
LCR
68.3%

Specs & Pricing

Technical snapshot and cost posture

Specs stay neutral, pricing gets emphasis through values rather than extra containers. Raw provider internals remain in metadata at the end.

Technical snapshot
Context Window
1050K Tokens
Vision
Enabled
Modalities
audio, image, text, video
Tokenizer
Other
Max Completion
131072
Moderation
No
Supported Parameters
frequency_penaltyinclude_reasoninglogit_biasmax_tokensmin_ppresence_penaltyreasoningrepetition_penaltyresponse_formatseedstopstructured_outputstemperaturetool_choicetoolstop_ktop_p
Input Modalities
audioimagetextvideo
Output Modalities
text
Price architecture
Input
per 1M input tokens
$0.14
Output
per 1M output tokens
$0.28
Blended
AA 3:1 mix
$0.17

This model is relatively efficient on price. It is the easier fit when sustained prompt volume matters.

OR Cache Read
$0.00

Metadata

Raw source tables at the end

Verification details remain available, but the page no longer forces them ahead of the editorial read.