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Moonshot AI releases Kimi K2 Thinking

Moonshot AI released Kimi K2 Thinking in November 2025, a reasoning model built on the trillion-parameter Kimi K2 layout with INT4 quantization for its mixture-of-experts parts and long tool-use chains.

A dense grid of compressed tiles with a thread of light winding through chains.

Background

Kimi K2 is an open-weight language model with 1 trillion total parameters and a mixture-of-experts layout. In November 2025 Moonshot AI released Kimi K2 Thinking, a reasoning version of it [1][2]. Like other reasoning models, it produces intermediate reasoning before its final answer, which is why the length of its tool-use chains and its speed both matter.

A reasoning model is one that works through a problem before answering. Reasoning models have become important because many useful tasks, from mathematics to multi-step coding, depend on a sequence of intermediate steps rather than a single guess.

What happened

In November 2025 Moonshot AI released Kimi K2 Thinking as a reasoning model [1][2]. The model keeps the mixture-of-experts layout of Kimi K2: 1 trillion total parameters, 32 billion active per token, 384 experts with 8 selected and 1 shared, and a 256K-token context window [3].

The training cost was reported at about US$4.6 million [1].

Key details

The release used quantization-aware training in post-training to create native INT4 weight-only quantization for the mixture-of-experts components. Moonshot says this roughly doubles generation speed [3].

A second key detail is tool use. Moonshot says the model keeps stable tool use across 200 to 300 sequential calls, while earlier models degrade after 30 to 50 steps [3]. A sequential call here means one tool invocation after another, where each result feeds the next step, so stability over a longer run decides whether a multi-step task finishes.

On benchmarks, Moonshot reported 44.9 on Humanity's Last Exam with tools, 51.0 in Heavy mode, 60.2 on BrowseComp and 71.3 on SWE-bench Verified [3]. These are the company's reported results.

Impact

The release combined an open-weight reasoning model with tool use over long sequences of calls, which matters for agents that work through many steps. The quantization of the mixture-of-experts parts is aimed at generation speed, which Moonshot says roughly doubles [3].

Sources

  1. 1
    Moonshot AIWikipedia
  2. 2
  3. 3

Cite this page: Moonshot AI releases Kimi K2 Thinking. TellWorld, https://www.tellworld.net/news/kimi-k2-thinking-2025. Updated 2026-11-08

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