Capability
58.9/100
field median 59.1
#87 of 230 ranked models
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Data as of September 2, 2026 · How the score is built
Mathematics ranks #5. Particularly strong for mathematical reasoning, scientific computing, and quantitative analysis.
45 published rows leave some tracked benchmark slots empty. Agentic is its lowest eligible category at #118.
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
58.9/100
field median 59.1
#87 of 230 ranked models
Price
$0.60input / $3 output
input median $1
blended $1.80
Speed
82tok/s
field median 90 tok/s
First token 38.77 s
Context
256Ktokens
field median 256,000
Reported for this model; direct source link not stored
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.
Kimi K2.5 category percentile values
The dashed outline is median of 6 nearest peers.
Published API price against the public score. The x-axis uses a log scale; the dashed path marks models that are not beaten by a cheaper, higher-scoring option. Price uses average of published input and output rates.
The chart opens on the current model. Scroll horizontally to inspect the full price axis.
Horizontal: blended price per million tokens, log scale · Vertical: public score
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.
Each documented value carries its source. Missing fields stay visible as not sourced or not published, rather than disappearing from the page.
Self-host and provider-specific paths stay separate from benchmark evidence so operating constraints are visible before a score becomes the whole decision.
Estimates at 50,000 req/day · 1000 tokens/req average.
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 #118 of 143Percentile 18thWeight 22%14 benchmarksMixed sources | 39.6 | #118 of 143 | 18th | 22% | 14 benchmarks | Mixed sources |
| CodingRank #45 of 148Percentile 70thWeight 20%8 benchmarksMixed sources | 57.0 | #45 of 148 | 70th | 20% | 8 benchmarks | Mixed sources |
| ReasoningRank Not rankedWeight 17%1 benchmarkVerified | 44.9 | Not ranked | Not available | 17% | 1 benchmark | Verified |
| KnowledgeRank #49 of 57Percentile 14thWeight 12%6 benchmarksMixed sources | 54.6 | #49 of 57 | 14th | 12% | 6 benchmarks | Mixed sources |
| MathRank #5 of 7Percentile 33rdWeight 5%9 benchmarksMixed sources | 62.5 | #5 of 7 | 33rd | 5% | 9 benchmarks | Mixed sources |
| MultilingualRank #8 of 12Percentile 36thWeight 7%2 benchmarksReported | 38.2 | #8 of 12 | 36th | 7% | 2 benchmarks | Reported |
| MultimodalRank Not rankedWeight 12%4 benchmarksMixed sources | 61.2 | Not ranked | Not available | 12% | 4 benchmarks | Mixed sources |
| Inst. FollowingRank #9 of 43Percentile 81stWeight 5%1 benchmarkReported | 91.2 | #9 of 43 | 81st | 5% | 1 benchmark | Reported |
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.
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-Rebench | Score58.5% | Versus best verified row Best verified: Claude Opus 4.6 · 65.3% | Gap6.8 behind | WeightWeighted 20% | Benchmark exact |
| SWE-bench VerifiedSoftware Engineering Benchmark Verified | Score76.8% | Versus best verified row Best verified: Claude Opus 5 · 96% | Gap19.2 behind | WeightWeighted 16% | Provider exact |
| SciCodeScientific Code Benchmark | Score48.7% | Versus best verified row Best verified: Sakana Fugu · 60.1% | Gap11.4 behind | WeightWeighted 16% | Provider exact |
| SWE-bench Pro | Score50.7% | Versus best verified row Best verified: Claude Fable 5.1 · 81.2% | Gap30.5 behind | WeightWeighted 10% | Provider exact |
| SWE-bench Verified*SWE-bench Verified (mini-swe-agent-v2) | Score70.8% | Versus best verified row | GapNo verified comparator | WeightDisplay only | Secondary exact |
| LiveCodeBench v6 | Score85.0% | Versus best verified row Best verified: Sakana Fugu-Ultra · 93.2% | Gap8.2 behind | WeightDisplay only | Provider exact |
| SWE Multilingual | Score73% | Versus best verified row Best verified: Claude Opus 5 · 89.5% | Gap16.5 behind | WeightDisplay only | Provider exact |
| React Native Evals | Score77.2% | Versus best verified row Best verified: Composer 2 · 96.1% | Gap18.9 behind | WeightDisplay only | Benchmark exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| Terminal-Bench 2.0 | Score50.8% | Versus best verified row Best verified: GPT-5.6 Sol · 91.9% | Gap41.1 behind | WeightWeighted 38% | Provider exact |
| BrowseComp | Score60.6% | Versus best verified row Best verified: GPT-5.6 Sol · 92.2% | Gap31.6 behind | WeightWeighted 28% | Provider exact |
| Claw-Eval | Score52.3% | Versus best verified row Best verified: Ornith-1.5-397B · 81.4% | Gap29.1 behind | WeightDisplay only | Benchmark exact |
| QwenClawBench | Score54.3% | Versus best verified row Best verified: Qwen3.7 Max · 64.3% | Gap10 behind | WeightDisplay only | Secondary exact |
| τ³-bench resultsτ³-Bench Tool-Agent-User Evaluation | Score65.7% | Versus best verified row Best verified: Mistral Medium 3.5 128B · 91.4% | Gap25.7 behind | WeightDisplay only | Secondary exact |
| DeepSearchQA | Score77.1% | Versus best verified row Best verified: Claude Opus 5 · 95.0% | Gap17.9 behind | WeightDisplay only | Provider exact |
| DeepPlanning | Score14.4% | Versus best verified row Best verified: Qwen3.7 Plus · 62.3% | Gap47.9 behind | WeightDisplay only | Secondary exact |
| Toolathlon | Score27.8% | Versus best verified row Best verified: Muse Spark 1.1 · 75.6% | Gap47.8 behind | WeightDisplay only | Provider exact |
| MCP Atlas | Score29.5% | Versus best verified row Best verified: Muse Spark 1.1 · 88.1% | Gap58.6 behind | WeightDisplay only | Provider exact |
| MCP-Tasks | Score59.1% | Versus best verified row Best verified: Qwen3.5 397B · 74.2% | Gap15.1 behind | WeightDisplay only | Secondary exact |
| WideResearch | Score72.7% | Versus best verified row Best verified: Hy4 preview · 83.9% | Gap11.2 behind | WeightDisplay only | Provider exact |
| Gert LabsGert Labs Composite Game Benchmark | Score45.88% | Versus best verified row Best verified: Claude Opus 4.8 · 72.97% | Gap27.1 behind | WeightDisplay only | Benchmark exact |
| ResearchClawBench | Score14.0% | Versus best verified row Best verified: Claude Opus 4.8 · 21.1% | Gap7.1 behind | WeightDisplay only | Benchmark exact |
| JobBench | Score8.7% | Versus best verified row Best verified: Muse Spark 1.3 · 64.9% | Gap56.2 behind | WeightDisplay only | Benchmark exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| LongBench v2 | Score61% | Versus best verified row Best verified: Qwen3.8 Max · 66.3% | Gap5.3 behind | WeightWeighted 38% | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| HLEHumanity's Last Exam | Score30.1% | Versus best verified row Best verified: Claude Fable 5.1 · 65% | Gap34.9 behind | WeightWeighted 45% | Provider exact |
| MMLU-ProMassive Multitask Language Understanding Professional | Score87.1% | Versus best verified row Best verified: Qwen3.7 Max · 89.6% | Gap2.5 behind | WeightWeighted 30% | Provider exact |
| GPQAGraduate-Level Google-Proof Q&A | Score87.6% | Versus best verified row Best verified: Sakana Fugu-Ultra · 95.5% | Gap7.9 behind | WeightWeighted 7% | Provider exact |
| SuperGPQASuperGPQA: Scaling LLM Evaluation Across 285 Graduate Disciplines | Score69.2% | Versus best verified row Best verified: Qwen 3.6 Max (preview) · 73.9% | Gap4.7 behind | WeightWeighted 7% | Secondary exact |
| GPQA-DGPQA Diamond | Score87.6% | Versus best verified row Best verified: Sakana Fugu-Ultra · 95.5% | Gap7.9 behind | WeightDisplay only | Provider exact |
| MMLU-Pro (Arcee)MMLU-Pro first-party comparison snapshot | Score87.1% | Versus best verified row Best verified: Trinity-Large-Preview · 75.2% | Gap11.9 behind | WeightDisplay only | Secondary exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| FrontierMath v2 (Tiers 1-3)FrontierMath v2 Tiers 1-3 | Score27.900% | Versus best verified row Best verified: GPT-5.6 Sol · 89.000% | Gap61.1 behind | WeightWeighted 30% | Benchmark exact |
| AIME26AIME 2026 | Score95.8% | Versus best verified row Best verified: GLM-5.2 · 99.2% | Gap3.4 behind | WeightWeighted 25% | Provider exact |
| HMMT Feb 2026Harvard-MIT Mathematics Tournament February 2026 | Score87.1% | Versus best verified row Best verified: Qwen3.7 Max · 97.1% | Gap10 behind | WeightWeighted 25% | Provider exact |
| FrontierMath v2 (Tier 4)FrontierMath v2 Tier 4 | Score4.200% | Versus best verified row Best verified: GPT-5.6 Sol · 83.000% | Gap78.8 behind | WeightWeighted 10% | Benchmark exact |
| AIME 2025American Invitational Mathematics Examination 2025 | Score96.1% | Versus best verified row Best verified: MAI-Thinking-1 · 97% | Gap0.9 behind | WeightDisplay only | Provider exact |
| AIME25 (Arcee)AIME25 first-party comparison snapshot | Score96.3% | Versus best verified row Best verified: Trinity-Large-Preview · 24.0% | Gap72.3 behind | WeightDisplay only | Secondary exact |
| HMMT Feb 2025Harvard-MIT Mathematics Tournament February 2025 | Score95.4% | Versus best verified row Best verified: Qwen3.6 Plus · 96.7% | Gap1.3 behind | WeightDisplay only | Provider exact |
| HMMT Nov 2025Harvard-MIT Mathematics Tournament November 2025 | Score91.1% | Versus best verified row Best verified: Qwen3.6 Plus · 94.6% | Gap3.5 behind | WeightDisplay only | Provider exact |
| MMAnswerBench | Score81.8% | Versus best verified row Best verified: GLM-5.2 · 91.0% | Gap9.2 behind | WeightDisplay only | Provider exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMLU-ProX | Score82.3% | Versus best verified row Best verified: Qwen3.7 Max · 87% | Gap4.7 behind | WeightWeighted 100% | Secondary exact |
| NOVA-63 | Score56.0% | Versus best verified row Best verified: Qwen3.5 397B · 59.1% | Gap3.1 behind | WeightDisplay only | Secondary exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMMU-ProMassive Multi-discipline Multimodal Understanding Pro | Score78.5% | Versus best verified row Best verified: GPT-5.4 Pro · 94% | Gap15.5 behind | WeightWeighted 45% | Provider exact |
| Video-MME | Score87.4% | Versus best verified row | GapNo verified comparator | WeightDisplay only | Reported |
| MMVUMultimodal Multi-disciplinary Video Understanding | Score80.4% | Versus best verified row Best verified: Qwen3.8 Max · 82.4% | Gap2 behind | WeightDisplay only | Reported |
| VideoMMMU | Score86.6% | Versus best verified row Best verified: Qwen3.8 Max · 88.7% | Gap2.1 behind | WeightDisplay only | Secondary exact |
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| IFEvalInstruction-Following Eval | Score93.9% | Versus best verified row Best verified: Qwen3.5-27B · 95% | Gap1.1 behind | WeightWeighted 35% | Secondary exact |
The sequence follows explicit supersedes links. A successor's displayed score stays at least 0.1 points above its predecessor; raw benchmark rows do not move. Scores and prices remain blank when the corresponding public row or first-party rate is unavailable.
Feb 1, 2026 · you are here
Kimi K2.5Score 58.9 · $0.6 / $3
Apr 20, 2026
Kimi K2.6Score 59.2 · $0.95 / $4
Base entry
The visual layer above carries the decisions. These notes preserve the model, ranking, coverage, and family context behind the numbers.
Kimi K2.5 ranks #87 of 230 on the public leaderboard with a score of 58.87/100. Its source-verified position is #46 of 105.
Kimi K2.5 is a open weight model with a 256K context window. No explicit reasoning mode is documented in this profile.
Kimi K2.5 sits in the Kimi K2.5 family with Kimi K2.5 (Reasoning). 45 of 416 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Mathematics at #5, while its lowest eligible position is Agentic at #118. particularly strong for mathematical reasoning, scientific computing, and quantitative analysis.
Kimi K2.5 ranks #87 out of 230 models on the public BenchAlign leaderboard, with a score of 58.87/100. Its evidence status is Supported, and this profile shows 45 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Kimi K2.5 ranks #49 out of 57 eligible models for knowledge and understanding, with a public category score of 54.6/100. 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.
Kimi K2.5 ranks #45 out of 148 eligible models for coding and programming, with a public category score of 57/100. 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.
Kimi K2.5 ranks #5 out of 7 eligible models for mathematics, with a public category score of 62.5/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Kimi K2.5 has source-displayable benchmark coverage for reasoning and logic, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Kimi K2.5 ranks #118 out of 143 eligible models for agentic tool use and computer tasks, with a public category score of 39.6/100. 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.
Kimi K2.5 has source-displayable benchmark coverage for multimodal and grounded tasks, but the public category table does not assign it a rank there. The individual rows remain available for inspection. A missing category position means the evidence threshold was not met; it does not convert the model's unmeasured work into a zero.
Kimi K2.5 ranks #9 out of 43 eligible models for instruction following, with a public category score of 91.2/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Kimi K2.5 ranks #8 out of 12 eligible models for multilingual tasks, with a public category score of 38.2/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Kimi K2.5 is an open-weight model from Moonshot AI. Its weights can be downloaded for local or hosted deployment, subject to the published license. Open weight does not automatically mean open source: training data and training code may remain private, and commercial restrictions can still apply.
Kimi K2.5 belongs to the Kimi K2.5 family. Related tracked variants include Kimi K2.5 (Reasoning). 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.
No. Kimi K2.5 currently has 63 source-displayable rows across 416 tracked benchmark slots. 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.
Kimi K2.5 has a reported context window of 256K 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.
Related resources
Last updated September 2, 2026. Runtime fields remain blank until a sourced snapshot exists.
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