Moonshot’s flagship MoE. Trained for long-horizon agentic workflows; the model engineering teams reach for when the cheap models stop being enough.Documentation Index
Fetch the complete documentation index at: https://docs.cogito.decart.ai/llms.txt
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| Slug | kimi-k2.6 |
| Parameters | 1T MoE (~32B active) |
| Context | 262,144 tokens (256k) |
| Throughput | 70 tokens/sec |
| TTFT | 280ms |
| License | Modified MIT |
| Hardware | NVIDIA Blackwell |
| Input price | $0.74 / 1M tokens |
| Output price | $3.49 / 1M tokens |
Best for
- Coding agents (multi-file refactors, multi-step PRs)
- Long-horizon agentic reasoning
- Complex tool use with parallel function calls
- Workloads that benefit from long, reliable reasoning chains