Quick answer: Kimi K2 Instruct 0905 is Moonshot AI's September 2025 checkpoint of Kimi K2 Instruct, scoring 76.5% ACEBench and 81.1% MMLU-Pro. Apache 2.0 licensed for full commercial use.
Where Kimi K2 Instruct 0905 leads
Where it lags
Best for: Open-source coding and reasoning pipelines; teams requiring Apache 2.0 MoE models with strong coding capability.
Kimi K2 Instruct 0905 is the September 2025 checkpoint of Moonshot AI's Kimi K2 Instruct model. The "0905" suffix (September 5, 2025) indicates a post-release update from the base Kimi K2 Instruct. Kimi K2 is a mixture-of-experts (MoE) model built for agentic tasks and coding, with the Instruct variant optimised for instruction-following.
With 76.5% ACEBench and 81.1% MMLU-Pro under Apache 2.0, this checkpoint is competitive for open-source deployment in coding-heavy pipelines.
| Field | Value |
|---|---|
| Organization | Moonshot AI |
| License | Apache 2.0 |
| Release date | July 2025 (checkpoint: Sept 2025) |
| Architecture | MoE (Mixture of Experts) |
| Modality | Text only |
Open weights under Apache 2.0 — self-host at no license cost. Also available via Moonshot AI API.
| Benchmark | Score | Source | Date |
|---|---|---|---|
| ACEBench | 76.5% | Benchgen evaluation | 2025-09 |
| MMLU-Pro | 81.1% | Benchgen evaluation | 2025-09 |
| Model | MMLU-Pro | License | Architecture |
|---|---|---|---|
| Kimi K2 Instruct 0905 | 81.1% | Apache 2.0 | MoE |
| Kimi K2 Thinking 0905 | 84.6% | Apache 2.0 | MoE (Thinking) |
| QwQ-32B | — | Apache 2.0 | Dense |
| DeepSeek-V3 | — | MIT | MoE |
Kimi K2 Instruct 0905 vs Kimi K2 Thinking 0905: lower MMLU-Pro (81.1% vs 84.6%) but likely faster inference without thinking overhead. For direct instruction-following, Instruct 0905; for advanced reasoning, Thinking 0905.
Specs from Moonshot AI's Kimi K2 Instruct 0905 release and Benchgen evaluations. Last updated 2026-07-24.
This model isn’t on any benchmark leaderboard yet.