Kimi K2.6
Self-host vs API cost
Estimates at 50,000 req/day · 1000 tokens/req average.
According to BenchLM.ai, Kimi K2.6 ranks #15 out of 119 models on the provisional leaderboard with an overall score of 85/100. It also ranks #9 out of 27 on the verified leaderboard. This places it in the upper tier of AI models, with competitive scores across most benchmark categories.
Kimi K2.6 is a open weight model with a 256K token context window. It uses explicit chain-of-thought reasoning, which typically improves performance on math and complex reasoning tasks at the cost of higher latency and token usage.
BenchLM links it directly to Kimi K2.5 as the earlier related model in that lineage. This profile currently has 46 of 223 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 Coding (#7), while its weakest is Multimodal & Grounded (#27). This performance profile makes it particularly well-suited for software development and code generation tasks.
Ranking Distribution
Category rank across 4 benchmark categories — sorted by best rank
Category Performance
Scores across all benchmark categories (0-100 scale)
Category Breakdown
Agentic
#10Coding
#7Reasoning
Knowledge
Math
Multilingual
Multimodal
#27Inst. Following
Chatbot Arena Performance
Benchmark Details
Only benchmark rows with an attached exact-source record are shown here. Source-unverified manual rows and generated rows are hidden from model pages.
Compare This Model
See how Kimi K2.6 stacks up against similar models
Frequently Asked Questions
How does Kimi K2.6 perform overall in AI benchmarks?
Kimi K2.6 currently ranks #15 out of 119 models on BenchLM's provisional leaderboard with an overall score of 85. It also ranks #9 out of 27 on the verified leaderboard. It is created by Moonshot AI and features a 256K context window.
Is Kimi K2.6 good for knowledge and understanding?
Kimi K2.6 has visible benchmark coverage in knowledge and understanding, but BenchLM does not currently assign it a global category rank there.
Is Kimi K2.6 good for coding and programming?
Kimi K2.6 ranks #7 out of 119 models in coding and programming benchmarks with an average score of 89.2. It is among the top performers in this category.
Is Kimi K2.6 good for mathematics?
Kimi K2.6 has visible benchmark coverage in mathematics, but BenchLM does not currently assign it a global category rank there.
Is Kimi K2.6 good for reasoning and logic?
Kimi K2.6 has visible benchmark coverage in reasoning and logic, but BenchLM does not currently assign it a global category rank there.
Is Kimi K2.6 good for agentic tool use and computer tasks?
Kimi K2.6 ranks #10 out of 119 models in agentic tool use and computer tasks benchmarks with an average score of 87.3. It is among the top performers in this category.
Is Kimi K2.6 good for multimodal and grounded tasks?
Kimi K2.6 ranks #27 out of 119 models in multimodal and grounded tasks benchmarks with an average score of 71.7. There are stronger options in this category.
Is Kimi K2.6 good for instruction following?
Kimi K2.6 has visible benchmark coverage in instruction following, but BenchLM does not currently assign it a global category rank there.
Is Kimi K2.6 open source?
Yes, Kimi K2.6 is an open weight model created by Moonshot AI, meaning it can be downloaded and run locally or fine-tuned for specific use cases.
Does Kimi K2.6 have full benchmark coverage on BenchLM?
Not yet. Kimi K2.6 currently has 46 published benchmark scores out of the 223 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 K2.6?
Kimi K2.6 has a context window of 256K, which determines how much text it can process in a single interaction.
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