# Kimi K2.5 (1T)

> Native-multimodal Moonshot flagship that keeps the K2/DeepSeek-style MoE layout and pushes native context to 256k.

| Property | Value |
| --- | --- |
| Lab | Moonshot AI (China) |
| Released | 2026-01-27 |
| Decoder type | Sparse MoE |
| Family | Sparse MoE |
| Scale | 1T total, 32B active (3.2% active) |
| Context window | 256,000 tokens |
| Attention | MLA |
| Layer mix | 61 MLA |
| KV cache / token (bf16) | 68.6 KiB (Low) |
| License | Modified MIT License |

**Key detail:** Keeps the 384-expert K2 backbone, but adds multimodal capabilities (not shown) and doubles the native context length.

## 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 19.4 (Scientific 6.9)

## Links

- Architecture diagram: https://sebastianraschka.com/llm-architecture-gallery/images/architectures/kimi-k2-5.webp
- View in article: https://magazine.sebastianraschka.com/p/a-dream-of-spring-for-open-weight#%C2%A72-moonshot-ais-kimi-k25-a-deepseek-like-model-at-a-1-trillion-parameter-scale
- config.json: https://huggingface.co/moonshotai/Kimi-K2.5/blob/main/config.json
- License: https://huggingface.co/moonshotai/Kimi-K2.5/blob/main/LICENSE
- Tech report: https://arxiv.org/pdf/2602.02276
- Source card (source of truth): https://sebastianraschka.com/llm-architecture-gallery/#card-kimi-k2-5
- Web page: https://llm-atlas-7or.pages.dev/models/kimi-k2-5/
- JSON: https://llm-atlas-7or.pages.dev/api/models/kimi-k2-5.json

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