How does MiMo-V2.5-Pro rank among AI models?
MiMo-V2.5-Pro is a superseded version and is not on the current board as of 6 November 2026. Its archive position, where one exists, is shown on the page; the newer version carries the current rank.
Xiaomi·#53 of 504 in the all-versions archive
MiMo-V2.5-Pro is a language model from Xiaomi. It ranks #53 of 504 in ModelCap's all-versions archive, with an Index score of 75.9, measured on 3 public benchmarks. Its score range of 71.2–80.6 spans positions #20–#83. It is listed at $0.48 per million input tokens and $1.80 per million output tokens across 3 providers. It reads up to 1M tokens of context, and its weights are openly downloadable.
Figures as of 6 Nov 2026, 13:52 UTC · download the public dataset · methodology
ModelCap Index · All-versions archive
75.9#53
Measured on 3 public benchmarks · range 71.2–80.6
Evidence as of 4 Nov 2026, 00:00 UTC
Superseded by MiMo-V2.6-Pro. It no longer holds a current-board position; its all-versions archive rank is #53.
Input
$0.48
per 1M tokens
Output
$1.80
per 1M tokens
Context
1M
tokens
Providers
3
endpoints
Providers
Uptime measured over the last 30 minutesHugging Face Inference Providers
Exact repository identityProvider economics and telemetry published by the Hugging Face Router. These are operational signals, not benchmark results.
Reasoning efforts
Best supported result can inform ModelCapPublished Max, X-High, High and other configurations for this model. These are sourced scores, not head-to-head essays.
Reported evaluation leads (13)
Not independent measurementStructured rows reported in this exact model repository at the pinned revision below. They are the publisher talking about itself: never measured evidence, never a score input on their own. They remain quarantined until dataset revision, harness, configuration and identity pass ModelCap’s independent admission review.
Other versions (1)
ModelCap Index · All-versions archive
Methodology75.9
Measured on 3 public benchmarks
All-versions archive
#53 of 504
- Score range
- 71.2–80.6
- Rank range
- #20–#83
- Evidence as of
- 4 Nov 2026, 00:00 UTC
- Benchmarks used
- Arena Coding, Arena Overall, LMArena Agent
Technical details
- Public rank basis
- Measured (measured)
- Evidence label
- Measured · 3 public benchmark observations across 3 boards
- Index support
- 66.1% · strong
- Identity binding
- Exact catalogue product · xiaomi/xiaomi/mimo-v2.5-pro/fp8 · aggregates disclosed benchmark configurations · endpoint configuration not claimed · artifact metadata XiaomiMiMo/MiMo-V2.5-Pro@98e90df48208087a2eb974866a736a20f8122d2a (not the evaluation revision)
- Index observations used
- 3
- Qualified Index evidence point
- 75.9
Bayesian Evidence Score · measured evidence input only
BES normalizes admitted public benchmark evidence for measured Index rows. Its legacy score and observables prior do not define the public language rank.
- Observed capability
- 75.9
- Evidence status
- confirmed · 88% mass
- General preference
- 77.0
- Coding
- 78.3
- Agents & tools
- 22.2
- Reasoning
- —
- Evidence breadth
- 97%
- Evidence coverage
- 66%
Market and catalogue signals · secondary, never the language Index rank
- Usage (OpenRouter popularity)
- 13.8
- Liquidity (providers × uptime)
- 85.9
- Open reach (HF downloads)
- 73.8
- Surface (context / tools / modalities)
- 85.0
- Freshness
- 47.1
- · OpenRouter popularity #152
- · 3 live providers
- · HF 30d downloads 9858
- · Catalogue: context 1050000, reasoning, tools
- · First seen 2026-04-22
These adoption and deployment observations remain context only. They do not change this model's ModelCap Index score or rank.
BES evidence selected · measured input only
- Arena Overall77.0
- Arena Coding78.3
- LMArena Agent22.2
The bounded 0–100 capability score blends each source’s competitive placement with its published achievement, then combines capability families. Evidence breadth adds a modest uncertainty adjustment; price and popularity are not part of benchmark-led rank.
Deployment readiness
Metadata index88.9
strong · 94% metadata coverage
- Artifact reproducibility
- 85.0
- Access & legal clarity
- 100.0
- Deployability
- 93.3
- Evaluation provenance
- 77.1
Not yet published: the base model it derives from, pinned evaluation dataset versions.
A metadata completeness and deployability index—not a safety certification, quality grade, or production-readiness claim.
Market activity
Venue coverage- Market Gravity
- 42.5
- OpenRouter weekly popularity
- #152 of 339
Market Gravity uses OpenRouter’s full-catalogue popularity order. Sparse Vercel top-ten observations appear only when published and do not affect the score.
Arena preference
- Status
- Ranked
- Source
- LMArena
- Official rank
- #52 of 419
- Rating
- 1466.6
- 95% confidence interval
- 1463–1470
- Votes
- 78K
- Source published at
- 28 Oct 2026, 00:00 UTC
- Category
- overall
- Identity match confidence
- 100%
Market Gravity breakdown
- Usage55%
- 13.8
- Liquidity25%
- 85.9
- Open reach15%
- 73.8
- Freshness5%
- 47.1
OpenRouter weekly popularity across the full model catalogue.
Independent providers versus the model's open or closed cohort, weighted by uptime.
Hugging Face 30-day downloads for open models; neutral for closed models.
Time since first public availability, on a six-month half-life.
Specification
- Model ID
xiaomi/mimo-v2.5-pro- Context window
- 1M tokens
- Declared output cap
- 236K tokens
OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. OpenRouter metadata
- Inputs
- Text
- Outputs
- Text
- Tokenizer
- Other
- Cached input tokens
- $0.096 / 1M
- First seen on OpenRouter
- 22 Apr 2026
Capabilities
- Supported: Reasoning
- Supported: Tool use
- Supported: Structured output
- Supported: Response format
- Not supported: Moderated
Weights & access
Open weights. Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI.
- Access
- Open weights
- Licence
- mit
- Pinned revision
- 98e90df48208
- Parameters
- 1023.2B
- Architecture
- MiMoV2ForCausalLM
- Model type
- mimo_v2
- Hugging Face downloads (30d)
- 10K
- Downloads (all time)
- 355K
- Likes
- 771
- Repository
- XiaomiMiMo/MiMo-V2.5-Pro
- Repository updated
- 28 Oct 2026, 14:14 UTC
Benchmark leaderboards featuring MiMo-V2.5-Pro
All leaderboardsMiMo-V2.5-Pro: common questions
How much does MiMo-V2.5-Pro cost per 1M tokens?
MiMo-V2.5-Pro is listed at $0.48 per 1M input tokens and $1.80 per 1M output tokens as of 6 November 2026; the lowest output price among 3 providers is $0.609 on GMICloud. Prices come from the OpenRouter catalogue and re-observe on every refresh. For 1,000 requests using 2,000 input and 500 output tokens each, the listed rates imply $1.86 total (2M input + 0.5M output). This excludes caching, batch discounts, prompt-length tiers, tool charges and retries; verify the chosen endpoint's rate and limits before budgeting.
What is the context window of MiMo-V2.5-Pro?
MiMo-V2.5-Pro has a published context window of 1M tokens (1,050,000). The snapshot lists a 235,929 token catalogue-declared route output cap. OpenRouter catalogue or provider-endpoint declaration. Limits can vary by provider and prompt length; a model-wide maximum has not been independently verified. The providers table lists each endpoint's context limit.
Is MiMo-V2.5-Pro open-weight?
Open weights (mit). Downloadable weights are published under an OSI or free-culture license in the current repository metadata. This describes weight availability, not whether the full training stack qualifies as Open Source AI. The repository is XiaomiMiMo/MiMo-V2.5-Pro on Hugging Face.
Which API providers serve MiMo-V2.5-Pro?
3 providers serve MiMo-V2.5-Pro through OpenRouter as of 6 November 2026: GMICloud, AtlasCloud and DigitalOcean. Each provider's price, context limit, quantization and measured uptime are in the providers table above.
Which benchmarks has MiMo-V2.5-Pro been evaluated on?
MiMo-V2.5-Pro has published results on 4 public boards tracked by ModelCap as of 6 November 2026: Arena text 1467 (#52 of 419), Arena coding 1521 (#34 of 414), LMArena Agent -9.0% (#50 of 58) and WildClawBench OpenClaw 43.0 (#21 of 34). Each board page ranks every tracked model on that benchmark. The ModelCap Index scores the results its methodology admits, with published uncertainty, and shows reference boards without scoring them.
When was MiMo-V2.5-Pro released?
MiMo-V2.5-Pro first appeared in the catalogue on 22 Apr 2026. It has since been superseded by MiMo-V2.6-Pro. Rank and price movements since then are recorded on the site's changes feed.