Data as of October 20, 2026 · How the score is built
Released Apr 22, 20261M context
MiMo-V2.5-Pro
Decision readingMiMo-V2.5-Pro scores 53 out of 100 and ranks #87 of 227. This profile shows 14 source-displayable benchmark rows; its strongest eligible category is Coding at #58. No comparable first-party API price is published in the catalog.
Released Apr 22, 2026 — see all recent releases
Decision snapshot
Each value carries a field reference instead of floating alone. Markers compare this model with the current ranked and priced catalog; they are not absolute quality thresholds.
Capability
53/100
field median 49.8#87 of 227 ranked models
Public
#87of 227
Verified #51 of 87
Price
API rate not published
input median $0.72No comparable first-party hosted token rate
Speed
Not measured
field median 93.5 tok/sTime to first token not measured
Context
1Mtokens
field median 256,000Reported for this model; direct source link not stored
Strongest published evidence
Coding ranks #58. Particularly well-suited for software development and code generation tasks.
Validate before choosing
14 published rows leave some tracked benchmark slots empty. No comparable first-party API token rate is published.
Source-linked · 14 displayable benchmark rows
Category score record
Scores and ranks appear only where published evidence can be displayed. The table keeps the score, weight, cohort, and evidence state together.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #74 of 131Percentile 44thWeight 22%6 benchmarksVerified | 37.8 | 6 benchmarks | Verified | |||
| CodingRank #58 of 152Percentile 62ndWeight 20%4 benchmarksVerified | 43.2 | 4 benchmarks | Verified | |||
| ReasoningWeight 17%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MultimodalWeight 12%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| KnowledgeRank #73 of 187Percentile 61stWeight 12%4 benchmarksVerified | 52.4 | 4 benchmarks | Verified | |||
| MultilingualWeight 7%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| Inst. FollowingWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured | |||
| MathWeight 5%0 benchmarksNot measured | Not measured | 0 benchmarks | Not measured |
14 of 726 tracked benchmark slots have displayable evidence · bars run 0–100
Coverage detailsHow much of this is verified
Coverage is split by category so a strong number never hides a thin evidence base. Verified means the row is tied to a published source; provisional rows remain visible but separate.
- Agentic6/6 verified
- Coding4/4 verified
- ReasoningNot measured
- MultimodalNot measured
- Knowledge4/4 verified
- MultilingualNot measured
- Inst. FollowingNot measured
- MathNot measured
Capability shape
Each axis shows percentile within that category’s eligible cohort. The comparison outline is the median of the six nearest public-score peers; a collapsed vertex means the category is not rank-eligible.
MiMo-V2.5-Pro category percentile values
- Agentic44th percentile
- Coding62nd percentile
- ReasoningNot eligible
- MultimodalNot eligible
- Knowledge61st percentile
- MultilingualNot eligible
- Instruction followingNot eligible
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#74/131
- Coding#58/152
- ReasoningNot ranked
- MultimodalNot ranked
- Knowledge#73/187
- MultilingualNot ranked
- Inst. FollowingNot ranked
- MathNot ranked
Benchmark ledger
Coding opens by default. The marker compares each value with the best source-verified result in the catalog; provisional leaders do not set the reference. Expand the remaining categories for every published row.
Coding4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench Pro | Score57.2% | Versus best verified row Best verified: Claude Opus 5.5 · 89.9% | Gap32.7 behind | Weight26% ref. weight | Provider exact |
| LiveCodeBench (Vals)LiveCodeBench, Vals AI run | Score81.4% | Versus best verified row Best verified: Claude Fable 5.1 · 90.5% | Gap9.1 behind | Weight8% ref. weight | |
| Terminal-Bench 2.0 | Score68.4% | Versus best verified row Best verified: GPT-5.5 · 82.0% | Gap13.6 behind | WeightScored in Agentic | Provider exact |
| SWE-bench (Vals)SWE-bench, Vals AI run | Score74.0% | Versus best verified row Best verified: Claude Opus 5 · 97.0% | Gap23 behind | WeightDisplay only | Verified |
Agentic6 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.0 | Score68.4% | Versus best verified row Best verified: GPT-5.5 · 82% | Gap13.6 behind | Weight7% ref. weight | Provider exact |
| Terminal-Bench 2.1 (Vals)Terminal-Bench 2.1, Vals AI run | Score57.3% | Versus best verified row Best verified: GPT-6 Astra · 87.3% | Gap30 behind | Weight4% ref. weight | |
| τ³-bench resultsτ³-Bench Tool-Agent-User Evaluation | Score72.9% | Versus best verified row Best verified: Mercury 2.5 · 96.0% | Gap23.1 behind | Weight2% ref. weight | Provider exact |
| Claw-Eval | Score63.8% | Versus best verified row Best verified: Ornith-1.5-397B · 81.4% | Gap17.6 behind | WeightDisplay only | Benchmark exact |
| Gert LabsGert Labs Composite Game Benchmark | Score62.70% | Versus best verified row Best verified: Claude Opus 4.8 · 72.97% | Gap10.3 behind | WeightDisplay only | Benchmark exact |
| MazeBenchMazeBench: visual spatial reasoning in a 3D open world | Score0% | Versus best verified row Best verified: GPT-6 Astra · 23% | Gap23 behind | WeightDisplay only | Benchmark exact |
Knowledge4 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLEHumanity's Last Exam | Score48% | Versus best verified row Best verified: Claude Fable 5.1 · 65% | Gap17 behind | Weight44% ref. weight | Provider exact |
| HLE w/o toolsHumanity's Last Exam without tools | Score34% | Versus best verified row Best verified: Claude Opus 5.5 · 64.4% | Gap30.4 behind | Weight7% ref. weight | Provider exact |
| MMLU-Pro (Vals)MMLU-Pro, Vals AI run | Score84.6% | Versus best verified row Best verified: Claude Fable 5.1 · 92.4% | Gap7.8 behind | Weight6% ref. weight | Verified |
| GPQA Diamond (Vals)GPQA Diamond, Vals AI run | Score82.6% | Versus best verified row Best verified: Gemini 3.1 Pro · 95.5% | Gap12.9 behind | Weight2% ref. weight |
Bars run 0–100; the dark tick marks the best source-verified value
All 14 rowsLineage
The sequence follows explicit supersedes links. Each score is estimated for that model; a relative can inform a sparse estimate but never sets a floor, so a newer release can score below an earlier one. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Spec sheet
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
- API model ID
- Not published
- Context window
- 1M
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not disclosed by the provider
- Availability
- Not sourced yet
- Cloud regions
- Not tracked yet
- Lifecycle
- Superseded
- API capabilities
- Tool calling, structured outputs, and batch support are not tracked yet
- Prompt caching
- Not documented in the pricing record
- Self-host
- Weights are not published
- Rate limits
- Not tracked yet
How to read this profile
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
MiMo-V2.5-Pro ranks #87 of 227 on the public leaderboard with a score of 53.02/100. Its source-verified position is #51 of 87.
MiMo-V2.5-Pro is a proprietary model with a 1M context window. It uses an explicit reasoning mode, which can improve complex problem solving while adding latency and token use.
Official exact-value snapshot from Xiaomi's April 22, 2026 MiMo-V2.5-Pro launch page. BenchLM maps only directly comparable rows from Xiaomi's published benchmark charts and keeps the row non-ranked because weighted public benchmark coverage remains sparse.
MiMo-V2.5-Pro sits in the MiMo-V2.5 family with MiMo-V2.5. Its explicit predecessor is MiMo-V2-Pro. 14 of 726 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Coding at #58, while its lowest eligible position is Agentic at #74. particularly well-suited for software development and code generation tasks.
Last updated October 20, 2026. Runtime fields remain blank until a sourced snapshot exists.
Deployment options
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Where to run MiMo-V2.5-Pro by API
2 hosts publish a per-token price for it. OpenRouter has the lowest output rate, $0.87 per million tokens. Prices read from each host’s own pages on October 20, 2026.
| Host | Input /1M | Output /1M | Cached /1M | Context |
|---|---|---|---|---|
| OpenRouter | $0.43 | $0.87 | $0.004 | 1.05M |
| Novita AI | $0.52 | $1.04 | $0.004 | 1.05M |
Questions
How does MiMo-V2.5-Pro perform overall in AI benchmarks?
MiMo-V2.5-Pro ranks #87 out of 227 models on the public BenchAlign leaderboard, with a score of 53.02/100. Its evidence status is Supported, and this profile shows 14 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is MiMo-V2.5-Pro good for knowledge and understanding?
MiMo-V2.5-Pro ranks #73 out of 187 eligible models for knowledge and understanding, with a public category score of 52.4/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is MiMo-V2.5-Pro good for coding and programming?
MiMo-V2.5-Pro ranks #58 out of 152 eligible models for coding and programming, with a public category score of 43.2/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Is MiMo-V2.5-Pro good for agentic tool use and computer tasks?
MiMo-V2.5-Pro ranks #74 out of 131 eligible models for agentic tool use and computer tasks, with a public category score of 37.8/100. Higher-ranked alternatives are available for workloads where this category decides the choice. Check the underlying rows before treating the aggregate as a workload guarantee.
Which sibling models are related to MiMo-V2.5-Pro?
MiMo-V2.5-Pro belongs to the MiMo-V2.5 family. Related tracked variants include MiMo-V2.5. A sibling link indicates shared lineage or a documented configuration relationship; it does not mean the variants have identical pricing, context limits, benchmark evidence, or deployment behavior. Compare before switching.
Does MiMo-V2.5-Pro have full benchmark coverage on BenchLM?
No. MiMo-V2.5-Pro currently has 31 source-displayable rows. The profile exposes published, non-generated evidence and leaves missing categories blank until an exact evaluation is available. Coverage describes how much was measured; it is not a penalty added to an individual benchmark result.
What is the context window size of MiMo-V2.5-Pro?
MiMo-V2.5-Pro has a reported context window of 1M in the exact-model catalog record. The value stays visible, but the profile marks its source link as unavailable instead of presenting it as directly documented. Maximum output length remains separate because providers often publish a different limit.