Data as of October 17, 2026 · How the score is built
Released Jan 27, 2026256K context
Kimi K2.5
Decision readingKimi K2.5 scores 53.1 out of 100 and ranks #86 of 224. This profile shows 68 source-displayable benchmark rows; its strongest eligible category is Multilingual at #8. API pricing is $0.6 input and $3 output per million tokens.
Released Jan 27, 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
53.1/100
field median 49.6#86 of 224 ranked models
Public
#86of 224
Verified #52 of 88
Price
$0.60input / $3 output
input median $0.75blended $1.80
Speed
58tok/s
field median 92 tok/sFirst token 52.9 s
Context
256Ktokens
field median 256,000Reported for this model; direct source link not stored
Strongest published evidence
Multilingual ranks #8. A well-rounded choice across a range of tasks.
Validate before choosing
68 published rows leave some tracked benchmark slots empty. Knowledge is its lowest eligible category at #75.
Source-linked · 68 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 #66 of 128Percentile 49thWeight 22%16 benchmarksMixed sources | 40.7 | 16 benchmarks | Mixed sources | |||
| CodingRank #68 of 150Percentile 55thWeight 20%10 benchmarksMixed sources | 38.5 | 10 benchmarks | Mixed sources | |||
| ReasoningRank Not rankedWeight 17%1 benchmarkVerified | 72.2 | 1 benchmark | Verified | |||
| MultimodalRank #32 of 54Percentile 42ndWeight 12%20 benchmarksMixed sources | 70.4 | 20 benchmarks | Mixed sources | |||
| KnowledgeRank #75 of 184Percentile 60thWeight 12%8 benchmarksMixed sources | 51.4 | 8 benchmarks | Mixed sources | |||
| MultilingualRank #8 of 17Percentile 56thWeight 7%5 benchmarksReported | 87.3 | 5 benchmarks | Reported | |||
| Inst. FollowingRank #48 of 148Percentile 68thWeight 5%1 benchmarkReported | 85.8 | 1 benchmark | Reported | |||
| MathRank Not rankedWeight 5%7 benchmarksMixed sources | 83.3 | 7 benchmarks | Mixed sources |
68 of 681 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.
- Agentic11/16 verified
- Coding8/10 verified
- Reasoning1/1 verified
- Multimodal5/20 verified
- Knowledge4/8 verified
- Multilingual0/5 verified
- Inst. Following0/1 verified
- Math6/7 verified
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.
Kimi K2.5 category percentile values
- Agentic49th percentile
- Coding55th percentile
- ReasoningNot eligible
- Multimodal42nd percentile
- Knowledge60th percentile
- Multilingual56th percentile
- Instruction following68th percentile
- MathNot eligible
The dashed outline is median of 6 nearest peers.
Eligible category ranks
- Agentic#66/128
- Coding#68/150
- ReasoningNot ranked
- Multimodal#32/54
- Knowledge#75/184
- Multilingual#8/17
- Inst. Following#48/148
- 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.
Coding10 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| SWE-bench Pro | Score50.7% | Versus best verified row Best verified: Claude Opus 5.5 · 89.9% | Gap39.2 behind | Weight26% ref. weight | Provider exact |
| SciCodeScientific Code Benchmark | Score48.7% | Versus best verified row Best verified: Sakana Fugu · 60.1% | Gap11.4 behind | Weight10% ref. weight | Provider exact |
| SWE Multilingual | Score73% | Versus best verified row Best verified: Claude Opus 5.5 · 93.9% | Gap20.9 behind | Weight5% ref. weight | Provider exact |
| SWE-Rebench | Score58.5% | Versus best verified row Best verified: Claude Opus 4.6 · 65.3% | Gap6.8 behind | Weight5% ref. weight | Benchmark exact |
| Terminal-Bench 2.0 | Score50.8% | Versus best verified row Best verified: GPT-5.5 · 82.0% | Gap31.2 behind | WeightScored in Agentic | Provider exact |
| SWE-bench VerifiedSoftware Engineering Benchmark Verified | Score76.8% | Versus best verified row Best verified: Claude Opus 5 · 96% | Gap19.2 behind | WeightDisplay only | 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 |
| React Native Evals | Score77.2% | Versus best verified row Best verified: Composer 2 · 96.1% | Gap18.9 behind | WeightDisplay only | Benchmark exact |
| NL2Repo | Score32% | Versus best verified row Best verified: DeepSeek V4.1 Flash 1017 · 68.2% | Gap36.2 behind | WeightDisplay only | Secondary exact |
Agentic16 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| BrowseComp | Score60.6% | Versus best verified row Best verified: Atria Dawn Preview · 92.5% | Gap31.9 behind | Weight8% ref. weight | Provider exact |
| Terminal-Bench 2.0 | Score50.8% | Versus best verified row Best verified: GPT-5.5 · 82% | Gap31.2 behind | Weight7% ref. weight | Provider exact |
| OSWorld-Verified | Score63.3% | Versus best verified row Best verified: Qwen3.8 Max · 86.1% | Gap22.8 behind | Weight7% ref. weight | Provider exact |
| JobBench | Score8.7% | Versus best verified row Best verified: Muse Wonder Full · 75.3% | Gap66.6 behind | Weight6% ref. weight | Benchmark exact |
| MCP Atlas | Score29.5% | Versus best verified row Best verified: Muse Spark Open · 89.2% | Gap59.7 behind | Weight4% ref. weight | Provider exact |
| Toolathlon | Score27.8% | Versus best verified row Best verified: Muse Spark 1.1 · 75.6% | Gap47.8 behind | Weight3% ref. weight | Provider exact |
| BFCL v4Berkeley Function Calling Leaderboard v4 | Score68.3% | Versus best verified row Best verified: BTL-3 · 88.5% | Gap20.2 behind | Weight3% ref. weight | Secondary exact |
| τ³-bench resultsτ³-Bench Tool-Agent-User Evaluation | Score65.7% | Versus best verified row Best verified: Mercury 2.5 · 96.0% | Gap30.3 behind | Weight2% ref. weight | Secondary exact |
| DeepSearchQA | Score77.1% | Versus best verified row Best verified: Atria Dawn Preview · 96.0% | Gap18.9 behind | Weight2% ref. weight | 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 |
| DeepPlanning | Score14.4% | Versus best verified row Best verified: Qwen3.7 Plus · 62.3% | Gap47.9 behind | WeightDisplay only | Secondary 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 |
Reasoning1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| LongBench v2 | Score61% | Versus best verified row Best verified: Beam 1.0 501B-A23B FP8 · 67.6% | Gap6.6 behind | WeightWeighted 25% | Provider exact |
Multimodal20 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| MMMU-ProMassive Multi-discipline Multimodal Understanding Pro | Score78.5% | Versus best verified row Best verified: Gemini 3.5 Flash · 83.6% | Gap5.1 behind | WeightWeighted 40% | Provider exact |
| CharXivCharXiv Reasoning | Score77.5% | Versus best verified row Best verified: Qwen3.8 Max · 93.5% | Gap16 behind | WeightWeighted 20% | Provider exact |
| MMMUMassive Multi-discipline Multimodal Understanding | Score84.3% | Versus best verified row Best verified: Qwen3.5 397B · 85.0% | Gap0.7 behind | WeightDisplay only | Secondary exact |
| RealWorldQA | Score81.0% | Versus best verified row Best verified: Qwen3.8-Flash-Next · 88.5% | Gap7.5 behind | WeightDisplay only | Secondary exact |
| OmniDocBench 1.5 | Score88.8% | Versus best verified row Best verified: Qwen3.8 Max · 92.1% | Gap3.3 behind | WeightDisplay only | Provider exact |
| Video-MME | Score87.4% | Versus best verified row Best verified: Seed 2.1 Pro · 89.2% | Gap1.8 behind | WeightDisplay only | Reported |
| Video-MME (with subtitle)Video-MME with subtitle | Score87.4% | Versus best verified row Best verified: Qwen3.8 Max · 90.4% | Gap3 behind | WeightDisplay only | Secondary exact |
| Video-MME (w/o subtitle)Video-MME without subtitle | Score83.2% | Versus best verified row Best verified: Qwen3.5 397B · 83.7% | Gap0.5 behind | WeightDisplay only | Secondary exact |
| MathVision | Score84.2% | Versus best verified row Best verified: Qwen3.8 Max · 95.2% | Gap11 behind | WeightDisplay only | Provider exact |
| We-Math | Score84.7% | Versus best verified row Best verified: Qwen3.5 397B · 87.9% | Gap3.2 behind | WeightDisplay only | Secondary exact |
| DynaMath | Score84.4% | Versus best verified row Best verified: Qwen3.5 397B · 86.3% | Gap1.9 behind | WeightDisplay only | Secondary exact |
| SimpleVQA | Score71.2% | Versus best verified row Best verified: Qwen3.7 Plus · 81.7% | Gap10.5 behind | WeightDisplay only | Provider exact |
| MMLongBench-Doc | Score58.5% | Versus best verified row Best verified: Nemotron 3.5 Super VL 120B A12B · 62.8% | Gap4.3 behind | WeightDisplay only | Secondary exact |
| CC-OCR | Score79.7% | Versus best verified row Best verified: Qwen3.5 397B · 82.0% | Gap2.3 behind | WeightDisplay only | Secondary exact |
| AI2D_TESTAI2D test split | Score90.8% | Versus best verified row Best verified: Qwen3.5 397B · 93.9% | Gap3.1 behind | WeightDisplay only | Secondary exact |
| CountBench | Score94.1% | Versus best verified row Best verified: Qwen3.6-27B · 97.8% | Gap3.7 behind | WeightDisplay only | Secondary exact |
| RefCOCO (avg)RefCOCO average | Score87.8% | Versus best verified row Best verified: Qwen3.6-27B · 92.5% | Gap4.7 behind | WeightDisplay only | Secondary exact |
| 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 |
| MLVU (M-Avg)MLVU mean average | Score85.0% | Versus best verified row Best verified: Qwen3.8 Max · 90.8% | Gap5.8 behind | WeightDisplay only | Secondary exact |
Knowledge8 rows
| 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 | Weight44% ref. weight | Provider exact |
| MMLU-ProMassive Multitask Language Understanding Professional | Score87.1% | Versus best verified row Best verified: Qwen3.7 Max · 89.6% | Gap2.5 behind | Weight6% ref. weight | Provider exact |
| GPQAGraduate-Level Google-Proof Q&A | Score87.6% | Versus best verified row Best verified: GPT-6 Astra · 96% | Gap8.4 behind | Weight3% ref. weight | 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 | Weight2% ref. weight | Secondary exact |
| GPQA-DGPQA Diamond | Score87.6% | Versus best verified row Best verified: GPT-6 Astra · 96.0% | Gap8.4 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 |
| MMLU-Redux | Score94.5% | Versus best verified row Best verified: Qwen3.7 Max · 95% | Gap0.5 behind | WeightDisplay only | Secondary exact |
| C-Eval | Score94% | Versus best verified row Best verified: Qwen3.6 Plus · 93.3% | Gap0.7 behind | WeightDisplay only | Secondary exact |
Multilingual5 rows
| 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 |
| INCLUDE | Score83.3% | Versus best verified row Best verified: Claude Opus 5 · 89.8% | Gap6.5 behind | WeightDisplay only | Secondary exact |
| PolyMath | Score43.1% | Versus best verified row Best verified: Qwen3.7 Max · 86.5% | Gap43.4 behind | WeightDisplay only | Secondary exact |
| MAXIFE | Score72.8% | Versus best verified row Best verified: Qwen3.7 Max · 89.2% | Gap16.4 behind | WeightDisplay only | Secondary exact |
Inst. Following1 row
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| IFEvalInstruction-Following Eval | Score93.9% | Versus best verified row Best verified: LFM2.5-24B-A2B · 96.8% | Gap2.8 behind | WeightDisplay only | Secondary exact |
Math7 rows
| Benchmark | Score | Versus best verified row | Gap | Weight | Evidence |
|---|---|---|---|---|---|
| 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 |
| AIME 2025American Invitational Mathematics Examination 2025 | Score96.1% | Versus best verified row Best verified: GPT-5.2 · 100% | Gap3.9 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: GLM-4.7 · 97.1% | Gap1.7 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 |
Bars run 0–100; the dark tick marks the best source-verified value
All 68 rowsWhat it costs to get this score
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.
Kimi K2.5 · 53.0 score · $1.80 blended per million tokens
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
Lineage
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.
Base entry
Kimi K2.5 (Reasoning) · 56.1Spec 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
- 256K
- Maximum output
- Not sourced yet
- Knowledge cutoff
- Not sourced yet
- Input modalities
- Not sourced yet
- Output modalities
- Not sourced yet
- Parameters
- Not sourced yet
- 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
- Kimi K2.5 needs ~320GB VRAM (4× NVIDIA A100 (80GB)).
- 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.
Kimi K2.5 ranks #86 of 224 on the public leaderboard with a score of 53.05/100. Its source-verified position is #52 of 88.
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). 68 of 681 tracked benchmark slots currently have displayable evidence. Missing categories stay blank.
Its strongest eligible category is Multilingual at #8, while its lowest eligible position is Knowledge at #75. a well-rounded choice across a range of tasks.
Last updated October 17, 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.
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Questions
How does Kimi K2.5 perform overall in AI benchmarks?
Kimi K2.5 ranks #86 out of 224 models on the public BenchAlign leaderboard, with a score of 53.05/100. Its evidence status is Supported, and this profile shows 68 source-displayable benchmark rows. The label describes evidence depth, not a provider quality claim; inspect category rows before choosing a workload.
Is Kimi K2.5 good for knowledge and understanding?
Kimi K2.5 ranks #75 out of 184 eligible models for knowledge and understanding, with a public category score of 51.4/100. 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 Kimi K2.5 good for coding and programming?
Kimi K2.5 ranks #68 out of 150 eligible models for coding and programming, with a public category score of 38.5/100. 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 Kimi K2.5 good for mathematics?
Kimi K2.5 has source-displayable benchmark coverage for mathematics, 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.
Is Kimi K2.5 good for reasoning and logic?
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.
Is Kimi K2.5 good for agentic tool use and computer tasks?
Kimi K2.5 ranks #66 out of 128 eligible models for agentic tool use and computer tasks, with a public category score of 40.7/100. 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 Kimi K2.5 good for multimodal and grounded tasks?
Kimi K2.5 ranks #32 out of 54 eligible models for multimodal and grounded tasks, with a public category score of 70.4/100. 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 Kimi K2.5 good for instruction following?
Kimi K2.5 ranks #48 out of 148 eligible models for instruction following, with a public category score of 85.8/100. 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.
Is Kimi K2.5 good for multilingual tasks?
Kimi K2.5 ranks #8 out of 17 eligible models for multilingual tasks, with a public category score of 87.3/100. That places it in the current top ten for this category. Check the underlying rows before treating the aggregate as a workload guarantee.
Is Kimi K2.5 open source?
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.
Which sibling models are related to Kimi K2.5?
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.
Does Kimi K2.5 have full benchmark coverage on BenchLM?
No. Kimi K2.5 currently has 84 source-displayable rows across 681 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.
What is the context window size of Kimi K2.5?
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.