Model profile
Kimi K2.5
Evidence coverage
63 of 321 tracked benchmarks are published. 31 are verified and 32 provisional. 8 of 8 categories are measured.
- Published / tracked
- 63 / 321
- Verified
- 31
- Provisional
- 32
- Categories with evidence
- 8 / 8
Evidence by category
- Agentic19 benchmarksMixed evidence
- Coding10 benchmarksMixed evidence
- Reasoning3 benchmarksMixed evidence
- Knowledge12 benchmarksMixed evidence
- Math9 benchmarksMixed evidence
- Multilingual2 benchmarksReported
- Multimodal6 benchmarksMixed evidence
- Inst. Following2 benchmarksReported
Kimi K2.5 ranks #54 out of 200 models on the public leaderboard with an overall score of 59.66/100. It also ranks #41 out of 99 on the verified leaderboard. While not a frontier model, it offers specific advantages depending on the use case.
Kimi K2.5 is a open weight model with a 256K token context window. It processes queries without explicit chain-of-thought reasoning, offering faster response times and lower token usage.
Kimi K2.5 sits inside the Kimi K2.5 family alongside Kimi K2.5 (Reasoning). This profile currently has 63 of 321 tracked benchmarks. BenchLM only exposes non-generated benchmark rows publicly, so missing categories stay blank until a sourced evaluation is available.
Its strongest category is Mathematics (#5), while its weakest is Agentic (#95). This performance profile makes it particularly strong for mathematical reasoning, scientific computing, and quantitative analysis.
Peer position
Exact provisional scores and ranks for the closest listed peers. A score can appear before a model clears the evidence threshold for a rank, so equal scores can have different rank states.
Range 59.35–59.97
- Grok 4.1xAICompare#5159.97Grok 4.1 is #51 with a score of 59.97.
- GLM-5 (Reasoning)Z.AICompare#5259.77GLM-5 (Reasoning) is #52 with a score of 59.77.
- Qwen 3.6 Max (preview)AlibabaCompare#5359.72Qwen 3.6 Max (preview) is #53 with a score of 59.72.
- Kimi K2.5Current modelMoonshot AI#5459.66Kimi K2.5 is #54 with a score of 59.66.
- MiniMax M2.5MiniMaxCompare#5559.52MiniMax M2.5 is #55 with a score of 59.52.
- Qwen3.5 397B (Reasoning)AlibabaCompare#5659.5Qwen3.5 397B (Reasoning) is #56 with a score of 59.5.
- Kimi K2.5 (Reasoning)Moonshot AICompare#5759.35Kimi K2.5 (Reasoning) is #57 with a score of 59.35.
Category percentile
More
Relative position among models eligible for each sourced category. A higher percentile means a stronger position within that category's ranked cohort; 100 is highest.
- Math33%Eligible cohort rank #5 of 7Category score 62.8
- Inst. Following81%Eligible cohort rank #8 of 38Category score 90.3
- Multilingual42%Eligible cohort rank #8 of 13Category score 38.2
- Coding75%Eligible cohort rank #31 of 122Category score 57.0
- Knowledge22%Eligible cohort rank #41 of 52Category score 58.6
- Agentic20%Eligible cohort rank #95 of 119Category score 39.6
Category evidence
Scores and ranks appear only where this model has published benchmark evidence. Categories without displayable source records remain not measured.
| Category | Score | Rank | Percentile | Weight | Benchmarks | Evidence |
|---|---|---|---|---|---|---|
| AgenticRank #95 of 119Percentile 20thWeight 22%19 benchmarksMixed sources | 39.6 | #95 of 119 | 20th | 22% | 19 benchmarks | Mixed sources |
| CodingRank #31 of 122Percentile 75thWeight 20%10 benchmarksMixed sources | 57.0 | #31 of 122 | 75th | 20% | 10 benchmarks | Mixed sources |
| ReasoningRank Not rankedWeight 17%3 benchmarksMixed sources | 79.6 | Not ranked | Not available | 17% | 3 benchmarks | Mixed sources |
| KnowledgeRank #41 of 52Percentile 22ndWeight 12%12 benchmarksMixed sources | 58.6 | #41 of 52 | 22nd | 12% | 12 benchmarks | Mixed sources |
| MathRank #5 of 7Percentile 33rdWeight 5%9 benchmarksMixed sources | 62.8 | #5 of 7 | 33rd | 5% | 9 benchmarks | Mixed sources |
| MultilingualRank #8 of 13Percentile 42ndWeight 7%2 benchmarksReported | 38.2 | #8 of 13 | 42nd | 7% | 2 benchmarks | Reported |
| MultimodalRank Not rankedWeight 12%6 benchmarksMixed sources | 65.9 | Not ranked | Not available | 12% | 6 benchmarks | Mixed sources |
| Inst. FollowingRank #8 of 38Percentile 81stWeight 5%2 benchmarksReported | 90.3 | #8 of 38 | 81st | 5% | 2 benchmarks | Reported |
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
Chatbot Arena performance
Scroll horizontally to inspect confidence intervals and vote counts.
| View | Elo | Confidence interval | Votes |
|---|---|---|---|
| Text Overall | 1400 | Not available | Not available |
Benchmark Details
Rows below have a displayable published verification record. Each source link and provenance note remains in the page HTML while its category is closed. Source-unverified manual rows and generated rows stay hidden.
Agentic19 benchmarks
τ³-Bench Tool-Agent-User Evaluation
τ²-Bench Tool-Agent-User Evaluation
Gert Labs Composite Game Benchmark
Artificial Analysis Agentic Index
GDPval-AA normalized
Coding10 benchmarks
Software Engineering Benchmark Verified
Scientific Code Benchmark
SWE-bench Verified (mini-swe-agent-v2)
Artificial Analysis SciCode
Artificial Analysis Coding Index
Reasoning3 benchmarks
Artificial Analysis Long Context Reasoning
Critical Physics Tasks
Knowledge12 benchmarks
Humanity's Last Exam
Massive Multitask Language Understanding Professional
Graduate-Level Google-Proof Q&A
SuperGPQA: Scaling LLM Evaluation Across 285 Graduate Disciplines
GPQA Diamond
MMLU-Pro first-party comparison snapshot
Artificial Analysis GPQA Diamond
Artificial Analysis Humanity's Last Exam
Artificial Analysis Omniscience Index
Artificial Analysis Omniscience Accuracy
Artificial Analysis Omniscience Hallucination Rate
Math9 benchmarks
FrontierMath v2 Tiers 1-3
AIME 2026
Harvard-MIT Mathematics Tournament February 2026
FrontierMath v2 Tier 4
American Invitational Mathematics Examination 2025
AIME25 first-party comparison snapshot
Harvard-MIT Mathematics Tournament February 2025
Harvard-MIT Mathematics Tournament November 2025
Multilingual2 benchmarks
Multimodal6 benchmarks
Massive Multi-discipline Multimodal Understanding Pro
Multimodal Multi-disciplinary Video Understanding
Artificial Analysis MMMU-Pro
Design Arena Website Elo
Inst. Following2 benchmarks
Instruction-Following Eval
Artificial Analysis IFBench
Frequently Asked Questions
How does Kimi K2.5 perform overall in AI benchmarks?
Kimi K2.5 currently ranks #54 out of 200 models on BenchLM's provisional leaderboard with an overall score of 59.66. It also ranks #41 out of 99 on the verified leaderboard. It is created by Moonshot AI. Its published context window is 256K.
Is Kimi K2.5 good for knowledge and understanding?
Kimi K2.5 ranks #41 out of 52 models in knowledge and understanding benchmarks with an average score of 58.6. There are stronger options in this category.
Is Kimi K2.5 good for coding and programming?
Kimi K2.5 ranks #31 out of 122 models in coding and programming benchmarks with an average score of 57. There are stronger options in this category.
Is Kimi K2.5 good for mathematics?
Kimi K2.5 ranks #5 out of 7 models in mathematics benchmarks with an average score of 62.8. It is among the top performers in this category.
Is Kimi K2.5 good for reasoning and logic?
Kimi K2.5 has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is Kimi K2.5 good for agentic tool use and computer tasks?
Kimi K2.5 ranks #95 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 39.6. There are stronger options in this category.
Is Kimi K2.5 good for multimodal and grounded tasks?
Kimi K2.5 has visible benchmark coverage in multimodal and grounded tasks, but BenchLM does not currently assign it a global category rank there.
Is Kimi K2.5 good for instruction following?
Kimi K2.5 ranks #8 out of 38 models in instruction following benchmarks with an average score of 90.3. It is among the top performers in this category.
Is Kimi K2.5 good for multilingual tasks?
Kimi K2.5 ranks #8 out of 13 models in multilingual tasks benchmarks with an average score of 38.2. It is among the top performers in this category.
Is Kimi K2.5 open source?
Yes, Kimi K2.5 is an open weight model created by Moonshot AI, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Which sibling models are related to Kimi K2.5?
Kimi K2.5 belongs to the Kimi K2.5 family. Related variants on BenchLM include Kimi K2.5 (Reasoning).
Does Kimi K2.5 have full benchmark coverage on BenchLM?
Not yet. Kimi K2.5 currently has 63 published benchmark scores out of the 321 benchmarks BenchLM tracks. BenchLM only exposes non-generated public benchmark rows, so missing categories stay blank until a sourced evaluation is available.
What is the context window size of Kimi K2.5?
Kimi K2.5 has a published context window of 256K, which determines how much text it can process in a single interaction.
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