# Moonshot releases Kimi K2 Thinking, a 1T MoE thinking agent with native INT4

> Kimi K2 Thinking is a 1T-parameter MoE with 32B active, 256K context and native INT4 quantisation, under a modified MIT licence.

Published 2025-11-04

Canonical: https://shipped.anth.us/open-weights/moonshotai-kimi-k2-thinking/

The moonshotai organisation published Kimi K2 Thinking, which its card calls the latest and most capable open-source thinking model in the line. It is built as a thinking agent that reasons step by step while calling tools. The card claims stable behaviour across 200 to 300 sequential tool calls.

The model is a mixture-of-experts with 1T total and 32B activated parameters, 61 layers, 384 experts with 8 selected per token, and a 256K context. Quantisation-aware training in post-training gives native INT4 weights, which the card says double speed in low-latency mode without loss. The card claims state-of-the-art results on Humanity's Last Exam and BrowseComp. Those are the maker's claims.

Both code and weights are under a Modified MIT License. Kimi K3, covered separately, is the later model.

The card gives no release date; the date used is the Hugging Face repo creation date.

An older sibling now, though still a reference for open tool-using models.

## Sources
- [Model card on Hugging Face](https://huggingface.co/moonshotai/Kimi-K2-Thinking)
- [Hugging Face repo metadata (creation date, licence, size)](https://huggingface.co/api/models/moonshotai/Kimi-K2-Thinking)

## Editor's first pass (AI-assisted)
- Real 3.5: Ungated weights under a modified MIT licence; 1T parameters even at INT4 needs a large cluster.
- Useful 3.5: Tool-heavy reasoning and research workflows, with 200 to 300 sequential tool calls claimed.
- Notable 4: Over 1,700 likes; an earlier step on the road to Kimi K3.
- Novel 3.5: Quantisation-aware training for lossless INT4 is the distinct feature.