# Kimi K2 (1T)

> Trillion-parameter Moonshot model that essentially scales the DeepSeek V3 recipe upward.

| Property | Value |
| --- | --- |
| Lab | Moonshot AI (China) |
| Released | 2025-07-10 |
| Decoder type | Sparse MoE |
| Family | Sparse MoE |
| Scale | 1T total, 32B active (3.2% active) |
| Context window | 128,000 tokens |
| Attention | MLA |
| Layer mix | 61 MLA |
| KV cache / token (bf16) | 68.6 KiB (Low) |
| License | Modified MIT License |

**Key detail:** More experts and fewer MLA heads than DeepSeek V3.

## Architecture concepts

- [Multi-Head Latent Attention (MLA)](https://llm-atlas-7or.pages.dev/concepts/mla.md): Keys and values are compressed into a small latent vector that is cached instead of full K/V.
- [Mixture of Experts (MoE)](https://llm-atlas-7or.pages.dev/concepts/moe.md): Many feed-forward experts, but a router sends each token to only a few of them.

## Benchmark (Artificial Analysis Intelligence Index)

- AA Intelligence Index v4.3.2: total 12.7 (Scientific 3.7)

## Links

- Architecture diagram: https://sebastianraschka.com/llm-architecture-gallery/images/architectures/kimi-k2-1-trillion.webp
- View in article: https://magazine.sebastianraschka.com/p/the-big-llm-architecture-comparison#%C2%A78-kimi-k2-and-kimi-k2-thinking
- config.json: https://huggingface.co/moonshotai/Kimi-K2-Base/blob/main/config.json
- License: https://huggingface.co/moonshotai/Kimi-K2-Base/blame/main/LICENSE
- Tech report: https://arxiv.org/pdf/2507.20534
- Source card (source of truth): https://sebastianraschka.com/llm-architecture-gallery/#card-kimi-k2
- Web page: https://llm-atlas-7or.pages.dev/models/kimi-k2/
- JSON: https://llm-atlas-7or.pages.dev/api/models/kimi-k2.json

_Data from Sebastian Raschka's LLM Architecture Gallery (https://sebastianraschka.com/llm-architecture-gallery/). Synced 2026-11-04._