agents benchmark
Kimi Code Bench v2 is Moonshot AI's in-house benchmark for evaluating coding agents on realistic software engineering tasks across 10+ mainstream programming languages and a production tech stack.
Updated Sep 5, 2026
Higher score ranks better on this benchmark.
Rank | Model | Score | Percentile | Participants | Evidence | Evaluated |
|---|
| Rank01 | ModelMA | Score72.90% | Percentile100.00% | Participants2 | EvidenceC | Evaluated |
| Rank02 | ModelMA | Score62.00% | Percentile0.00% | Participants2 | EvidenceC | Evaluated |
The leading models and scores on this benchmark.
A closer view of the leading scores on this benchmark.
The first five results on this benchmark, with official price and output speed added where the model identity can be matched.
What Kimi Code Bench v2 measures and how its scores work.
Kimi Code Bench v2 is a benchmark for coding agents covering backend services, infrastructure, performance engineering, systems programming, security, frontend development, and ML/data engineering.
It reports a Score as a ratio for performance on realistic software engineering tasks.
Scores are shown in ratio. This benchmark is not independently verified and has an evidence level of B.
LLM Stats. Benchmark scores retain their original unit. Overall score eligibility is shown separately.
Common questions about Kimi Code Bench v2.
Kimi K3 is currently ranked first with 72.90%.
The current leaders are Kimi K3 (72.90%) and Kimi K2.7 Code (62.00%).
Kimi K2.7 Code has the lowest matched official input price at $0.95 input / $4.0 output per 1M tokens.
No matched runtime record is currently available.
No. This benchmark measures one defined capability or task. The overall LLMBoard score uses a separate aggregation across eligible benchmark evidence.
It reports a Score as a ratio for performance on realistic software engineering tasks.
Yes. Higher values rank better for this benchmark.
2 model results are currently shown.
No. This benchmark is shown for reference but does not contribute to the overall score.
Ranking basisThis kimi code bench v2 AI model leaderboard uses descending score in the benchmark original unit. The leaderboard ranking keeps matched price and speed data separate from benchmark evidence.
Selection summary
Kimi K3 currently leads Kimi Code Bench v2 with 72.90%. It is the top model on this specific benchmark, while the best LLM for the broader task should also be checked against other benchmarks, price, and runtime.
Use this leaderboard with the supporting benchmark results and coverage details above. A leaderboard position summarizes the selected ranking signal; it does not replace workload-specific testing.