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Data

Data as of October 17, 2026 · How the score is built

Superseded.Moonshot AI has newer models in this line:Kimi K2.6
SupersededOpen WeightNon-Reasoning

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 scores, ranks, weighting, benchmark coverage, and evidence status
CategoryScore
AgenticRank #66 of 128Percentile 49thWeight 22%16 benchmarksMixed sources
40.7
CodingRank #68 of 150Percentile 55thWeight 20%10 benchmarksMixed sources
38.5
ReasoningRank Not rankedWeight 17%1 benchmarkVerified
72.2
MultimodalRank #32 of 54Percentile 42ndWeight 12%20 benchmarksMixed sources
70.4
KnowledgeRank #75 of 184Percentile 60thWeight 12%8 benchmarksMixed sources
51.4
MultilingualRank #8 of 17Percentile 56thWeight 7%5 benchmarksReported
87.3
Inst. FollowingRank #48 of 148Percentile 68thWeight 5%1 benchmarkReported
85.8
MathRank Not rankedWeight 5%7 benchmarksMixed sources
83.3

68 of 681 tracked benchmark slots have displayable evidence · bars run 0–100

Coverage details

How 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.

  1. Agentic11/16 verified
  2. Coding8/10 verified
  3. Reasoning1/1 verified
  4. Multimodal5/20 verified
  5. Knowledge4/8 verified
  6. Multilingual0/5 verified
  7. Inst. Following0/1 verified
  8. Math6/7 verified
Verified sourceProvisionalNot 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.

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

  1. Agentic#66/128
  2. Coding#68/150
  3. ReasoningNot ranked
  4. Multimodal#32/54
  5. Knowledge#75/184
  6. Multilingual#8/17
  7. Inst. Following#48/148
  8. MathNot ranked
Top decileTop quartileMid-fieldNot eligible

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
Coding benchmark values, best verified comparison, weight, and source status
SWE-bench ProScore50.7%Versus best verified row

Best verified: Claude Opus 5.5 · 89.9%

Gap39.2 behindWeight26% ref. weight
SciCodeScientific Code BenchmarkScore48.7%Versus best verified row

Best verified: Sakana Fugu · 60.1%

Gap11.4 behindWeight10% ref. weight
SWE MultilingualScore73%Versus best verified row

Best verified: Claude Opus 5.5 · 93.9%

Gap20.9 behindWeight5% ref. weight
SWE-RebenchScore58.5%Versus best verified row

Best verified: Claude Opus 4.6 · 65.3%

Gap6.8 behindWeight5% ref. weight
Terminal-Bench 2.0Score50.8%Versus best verified row

Best verified: GPT-5.5 · 82.0%

Gap31.2 behindWeightScored in Agentic
SWE-bench VerifiedSoftware Engineering Benchmark VerifiedScore76.8%Versus best verified row

Best verified: Claude Opus 5 · 96%

Gap19.2 behindWeightDisplay only
SWE-bench Verified*SWE-bench Verified (mini-swe-agent-v2)Score70.8%Versus best verified rowGapNo verified comparatorWeightDisplay only
LiveCodeBench v6Score85.0%Versus best verified row

Best verified: Sakana Fugu-Ultra · 93.2%

Gap8.2 behindWeightDisplay only
React Native EvalsScore77.2%Versus best verified row

Best verified: Composer 2 · 96.1%

Gap18.9 behindWeightDisplay only
NL2RepoScore32%Versus best verified row

Best verified: DeepSeek V4.1 Flash 1017 · 68.2%

Gap36.2 behindWeightDisplay only
Agentic16 rows
Agentic benchmark values, best verified comparison, weight, and source status
BrowseCompScore60.6%Versus best verified row

Best verified: Atria Dawn Preview · 92.5%

Gap31.9 behindWeight8% ref. weight
Terminal-Bench 2.0Score50.8%Versus best verified row

Best verified: GPT-5.5 · 82%

Gap31.2 behindWeight7% ref. weight
OSWorld-VerifiedScore63.3%Versus best verified row

Best verified: Qwen3.8 Max · 86.1%

Gap22.8 behindWeight7% ref. weight
Provider exact
JobBenchScore8.7%Versus best verified row

Best verified: Muse Wonder Full · 75.3%

Gap66.6 behindWeight6% ref. weight
Benchmark exact
MCP AtlasScore29.5%Versus best verified row

Best verified: Muse Spark Open · 89.2%

Gap59.7 behindWeight4% ref. weight
ToolathlonScore27.8%Versus best verified row

Best verified: Muse Spark 1.1 · 75.6%

Gap47.8 behindWeight3% ref. weight
BFCL v4Berkeley Function Calling Leaderboard v4Score68.3%Versus best verified row

Best verified: BTL-3 · 88.5%

Gap20.2 behindWeight3% ref. weight
τ³-bench resultsτ³-Bench Tool-Agent-User EvaluationScore65.7%Versus best verified row

Best verified: Mercury 2.5 · 96.0%

Gap30.3 behindWeight2% ref. weight
DeepSearchQAScore77.1%Versus best verified row

Best verified: Atria Dawn Preview · 96.0%

Gap18.9 behindWeight2% ref. weight
Claw-EvalScore52.3%Versus best verified row

Best verified: Ornith-1.5-397B · 81.4%

Gap29.1 behindWeightDisplay only
Benchmark exact
QwenClawBenchScore54.3%Versus best verified row

Best verified: Qwen3.7 Max · 64.3%

Gap10 behindWeightDisplay only
DeepPlanningScore14.4%Versus best verified row

Best verified: Qwen3.7 Plus · 62.3%

Gap47.9 behindWeightDisplay only
MCP-TasksScore59.1%Versus best verified row

Best verified: Qwen3.5 397B · 74.2%

Gap15.1 behindWeightDisplay only
WideResearchScore72.7%Versus best verified row

Best verified: Hy4 preview · 83.9%

Gap11.2 behindWeightDisplay only
Gert LabsGert Labs Composite Game BenchmarkScore45.88%Versus best verified row

Best verified: Claude Opus 4.8 · 72.97%

Gap27.1 behindWeightDisplay only
Benchmark exact
ResearchClawBenchScore14.0%Versus best verified row

Best verified: Claude Opus 4.8 · 21.1%

Gap7.1 behindWeightDisplay only
Reasoning1 row
Reasoning benchmark values, best verified comparison, weight, and source status
LongBench v2Score61%Versus best verified row

Best verified: Beam 1.0 501B-A23B FP8 · 67.6%

Gap6.6 behindWeightWeighted 25%
Multimodal20 rows
Multimodal benchmark values, best verified comparison, weight, and source status
MMMU-ProMassive Multi-discipline Multimodal Understanding ProScore78.5%Versus best verified row

Best verified: Gemini 3.5 Flash · 83.6%

Gap5.1 behindWeightWeighted 40%
CharXivCharXiv ReasoningScore77.5%Versus best verified row

Best verified: Qwen3.8 Max · 93.5%

Gap16 behindWeightWeighted 20%
MMMUMassive Multi-discipline Multimodal UnderstandingScore84.3%Versus best verified row

Best verified: Qwen3.5 397B · 85.0%

Gap0.7 behindWeightDisplay only
RealWorldQAScore81.0%Versus best verified row

Best verified: Qwen3.8-Flash-Next · 88.5%

Gap7.5 behindWeightDisplay only
OmniDocBench 1.5Score88.8%Versus best verified row

Best verified: Qwen3.8 Max · 92.1%

Gap3.3 behindWeightDisplay only
Video-MMEScore87.4%Versus best verified row

Best verified: Seed 2.1 Pro · 89.2%

Gap1.8 behindWeightDisplay only
Video-MME (with subtitle)Video-MME with subtitleScore87.4%Versus best verified row

Best verified: Qwen3.8 Max · 90.4%

Gap3 behindWeightDisplay only
Video-MME (w/o subtitle)Video-MME without subtitleScore83.2%Versus best verified row

Best verified: Qwen3.5 397B · 83.7%

Gap0.5 behindWeightDisplay only
MathVisionScore84.2%Versus best verified row

Best verified: Qwen3.8 Max · 95.2%

Gap11 behindWeightDisplay only
We-MathScore84.7%Versus best verified row

Best verified: Qwen3.5 397B · 87.9%

Gap3.2 behindWeightDisplay only
DynaMathScore84.4%Versus best verified row

Best verified: Qwen3.5 397B · 86.3%

Gap1.9 behindWeightDisplay only
SimpleVQAScore71.2%Versus best verified row

Best verified: Qwen3.7 Plus · 81.7%

Gap10.5 behindWeightDisplay only
MMLongBench-DocScore58.5%Versus best verified row

Best verified: Nemotron 3.5 Super VL 120B A12B · 62.8%

Gap4.3 behindWeightDisplay only
CC-OCRScore79.7%Versus best verified row

Best verified: Qwen3.5 397B · 82.0%

Gap2.3 behindWeightDisplay only
AI2D_TESTAI2D test splitScore90.8%Versus best verified row

Best verified: Qwen3.5 397B · 93.9%

Gap3.1 behindWeightDisplay only
CountBenchScore94.1%Versus best verified row

Best verified: Qwen3.6-27B · 97.8%

Gap3.7 behindWeightDisplay only
RefCOCO (avg)RefCOCO averageScore87.8%Versus best verified row

Best verified: Qwen3.6-27B · 92.5%

Gap4.7 behindWeightDisplay only
MMVUMultimodal Multi-disciplinary Video UnderstandingScore80.4%Versus best verified row

Best verified: Qwen3.8 Max · 82.4%

Gap2 behindWeightDisplay only
VideoMMMUScore86.6%Versus best verified row

Best verified: Qwen3.8 Max · 88.7%

Gap2.1 behindWeightDisplay only
MLVU (M-Avg)MLVU mean averageScore85.0%Versus best verified row

Best verified: Qwen3.8 Max · 90.8%

Gap5.8 behindWeightDisplay only
Knowledge8 rows
Knowledge benchmark values, best verified comparison, weight, and source status
HLEHumanity's Last ExamScore30.1%Versus best verified row

Best verified: Claude Fable 5.1 · 65%

Gap34.9 behindWeight44% ref. weight
MMLU-ProMassive Multitask Language Understanding ProfessionalScore87.1%Versus best verified row

Best verified: Qwen3.7 Max · 89.6%

Gap2.5 behindWeight6% ref. weight
GPQAGraduate-Level Google-Proof Q&AScore87.6%Versus best verified row

Best verified: GPT-6 Astra · 96%

Gap8.4 behindWeight3% ref. weight
SuperGPQASuperGPQA: Scaling LLM Evaluation Across 285 Graduate DisciplinesScore69.2%Versus best verified row

Best verified: Qwen 3.6 Max (preview) · 73.9%

Gap4.7 behindWeight2% ref. weight
GPQA-DGPQA DiamondScore87.6%Versus best verified row

Best verified: GPT-6 Astra · 96.0%

Gap8.4 behindWeightDisplay only
MMLU-Pro (Arcee)MMLU-Pro first-party comparison snapshotScore87.1%Versus best verified row

Best verified: Trinity-Large-Preview · 75.2%

Gap11.9 behindWeightDisplay only
MMLU-ReduxScore94.5%Versus best verified row

Best verified: Qwen3.7 Max · 95%

Gap0.5 behindWeightDisplay only
C-EvalScore94%Versus best verified row

Best verified: Qwen3.6 Plus · 93.3%

Gap0.7 behindWeightDisplay only
Multilingual5 rows
Multilingual benchmark values, best verified comparison, weight, and source status
MMLU-ProXScore82.3%Versus best verified row

Best verified: Qwen3.7 Max · 87%

Gap4.7 behindWeightWeighted 100%
NOVA-63Score56.0%Versus best verified row

Best verified: Qwen3.5 397B · 59.1%

Gap3.1 behindWeightDisplay only
INCLUDEScore83.3%Versus best verified row

Best verified: Claude Opus 5 · 89.8%

Gap6.5 behindWeightDisplay only
PolyMathScore43.1%Versus best verified row

Best verified: Qwen3.7 Max · 86.5%

Gap43.4 behindWeightDisplay only
MAXIFEScore72.8%Versus best verified row

Best verified: Qwen3.7 Max · 89.2%

Gap16.4 behindWeightDisplay only
Inst. Following1 row
Inst. Following benchmark values, best verified comparison, weight, and source status
IFEvalInstruction-Following EvalScore93.9%Versus best verified row

Best verified: LFM2.5-24B-A2B · 96.8%

Gap2.8 behindWeightDisplay only
Math7 rows
Math benchmark values, best verified comparison, weight, and source status
AIME26AIME 2026Score95.8%Versus best verified row

Best verified: GLM-5.2 · 99.2%

Gap3.4 behindWeightWeighted 25%
HMMT Feb 2026Harvard-MIT Mathematics Tournament February 2026Score87.1%Versus best verified row

Best verified: Qwen3.7 Max · 97.1%

Gap10 behindWeightWeighted 25%
AIME 2025American Invitational Mathematics Examination 2025Score96.1%Versus best verified row

Best verified: GPT-5.2 · 100%

Gap3.9 behindWeightDisplay only
AIME25 (Arcee)AIME25 first-party comparison snapshotScore96.3%Versus best verified row

Best verified: Trinity-Large-Preview · 24.0%

Gap72.3 behindWeightDisplay only
HMMT Feb 2025Harvard-MIT Mathematics Tournament February 2025Score95.4%Versus best verified row

Best verified: GLM-4.7 · 97.1%

Gap1.7 behindWeightDisplay only
HMMT Nov 2025Harvard-MIT Mathematics Tournament November 2025Score91.1%Versus best verified row

Best verified: Qwen3.6 Plus · 94.6%

Gap3.5 behindWeightDisplay only
MMAnswerBenchScore81.8%Versus best verified row

Best verified: GLM-5.2 · 91.0%

Gap9.2 behindWeightDisplay only

Bars run 0–100; the dark tick marks the best source-verified value

All 68 rows

What 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.

Current modelExplore all models

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.

405060708090100$0.10$0.50$1$5$10$25$50$100↘ frontierKimi K2.5

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.

  1. Jan 27, 2026 · you are here

    Kimi K2.5

    Score 53.0 · $0.6 / $3

  2. Apr 20, 2026

    Kimi K2.6

    Score 58.4 · $0.95 / $4

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
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.

Kimi K2.5
API / mo$2,700
Self-host / mo$7,358
Break-even186M/day
Model the full break-even

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.

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