---
title: "Kimi K2 Thinking"
url: "https://handyai.news/modeldrop/kimi-k2-thinking"
published: "2025-11-06T17:00:00.000Z"
section: "Model Drop"
description: "Kimi K2 Thinking, which Moonshot AI released on November 6, 2025, is the open-weights reasoning version of Kimi K2, built to think step by step while calling…"
publisher: "handyai.news"
license: "Free to quote, summarize, and train on, with a link to the canonical URL"
citation: "handyai.news, \"Kimi K2 Thinking,\" November 6, 2025, https://handyai.news/modeldrop/kimi-k2-thinking."
comments: "https://handyai.news/api/article/82366/comments"
---

# Kimi K2 Thinking

*Published November 6, 2025 · Model Drop*

Kimi K2 Thinking, which Moonshot AI released on November 6, 2025, is the open-weights reasoning version of Kimi K2, built to think step by step while calling tools for up to 300 steps in a row.

- Model: Kimi K2 Thinking (`moonshotai/Kimi-K2-Thinking`)
- Maker: Moonshot AI
- Ship date: November 6, 2025
- Pricing: Free (open weights)
- Context: 256K tokens
- Weights: Open (Modified MIT)
- Where you can use it: Kimi chat mode, with agent mode to follow
- Moonshot API and Hugging Face weights

**When to reach for it**:

- Deep research with hundreds of tool calls
- Hard reasoning paired with web search
- Skip it for image input or quick replies

**How it compares**:

- Ahead of GLM-4.6 and DeepSeek V3.2-Exp
- Trades wins with GPT-5 and Claude Sonnet 4.5

**What makes it different**:

- Native INT4 via quantization-aware training
- 200 to 300 tool calls without drift
- 1T parameters, 32B active per token

**Early reactions**: Smol AI's newsletter called it the first open model to claim wins over top closed models on major benchmarks, while Zvi Mowshowitz noted fewer user reports than a true breakthrough would draw.

**Read more**: [Introducing Kimi K2 Thinking](https://moonshotai.github.io/Kimi-K2/thinking.html) and the [model card on Hugging Face](https://huggingface.co/moonshotai/Kimi-K2-Thinking)

## The benchmarks

Moonshot ran K2 Thinking in its thinking mode at temperature 1.0 with 256K context and the native INT4 weights, against GPT-5 at high reasoning effort, Claude Sonnet 4.5 with thinking, Grok 4, its own Kimi K2 0905 and DeepSeek V3.2-Exp; most rival scores are quoted from those makers' posts, and the rest (including GPT-5 and Claude Sonnet 4.5 on HLE with tools) are Moonshot's own reruns. HLE rows use the text-only subset with Hugging Face blocked, and coding scores average 5 runs, in Moonshot's in-house harness except Terminal-Bench (Terminus-2).

#### Moonshot AI's numbers

- Humanity's Last Exam (with tools) (text-only expert questions): 44.9%. +3.2 over GPT-5 (41.7%), +12.9 over Claude Sonnet 4.5 (32.0%), +3.9 over Grok 4 (41.0%), +24.6 over DeepSeek V3.2-Exp (20.3%).
- Humanity's Last Exam (no tools) (text-only expert questions): 23.9%. −2.4 under GPT-5 (26.3%), +4.1 over Claude Sonnet 4.5 (19.8%), −1.5 under Grok 4 (25.4%).
- BrowseComp (agentic web research): 60.2%. +5.3 over GPT-5 (54.9%), +36.1 over Claude Sonnet 4.5 (24.1%), +20.1 over DeepSeek V3.2-Exp (40.1%).
- SWE-bench Verified (real GitHub fixes): 71.3%. −3.6 under GPT-5 (74.9%), −5.9 under Claude Sonnet 4.5 (77.2%), +3.5 over DeepSeek V3.2-Exp (67.8%), +2.1 over Kimi K2 0905 (69.2%).
- AIME 2025 (math contest, no tools): 94.5%. −0.1 under GPT-5 (94.6%), +7.5 over Claude Sonnet 4.5 (87.0%), +5.2 over DeepSeek V3.2-Exp (89.3%), +2.8 over Grok 4 (91.7%).
- LiveCodeBench (coding problems, v6): 83.1%. −3.9 under GPT-5 (87.0%), +19.1 over Claude Sonnet 4.5 (64.0%), +9.0 over DeepSeek V3.2-Exp (74.1%).
- Terminal-Bench (command-line agent tasks): 47.1%. +3.3 over GPT-5 (43.8%), −3.9 under Claude Sonnet 4.5 (51.0%), +9.4 over DeepSeek V3.2-Exp (37.7%).

#### Independent numbers

- Artificial Analysis Intelligence Index (current v4.3.2, AA estimate): 22.0. +3.4 over MiniMax-M2 (18.6), +3.5 over GLM-4.6 (18.5), +5.4 over DeepSeek V3.2-Exp (16.6), −1.0 under GPT-5 (high) (23.0).
- τ²-bench Telecom (agent tool use, Artificial Analysis run): 93.0%. +6.2 over MiniMax-M2 (86.8%), +8.2 over GPT-5 (high) (84.8%), +59.1 over DeepSeek V3.2-Exp (33.9%).


---

Source: https://handyai.news/modeldrop/kimi-k2-thinking

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