Kimi-VL-Thinking-2506

[!Note] This is an improved version of Kimi-VL-A3B-Thinking. Please consider using this updated model instead of the previous version.

[!Note] Please visit our tech blog for recommended inference recipe of this model: Kimi-VL-A3B-Thinking-2506: A Quick Navigation

1. Introduction

This is an updated version of Kimi-VL-A3B-Thinking, with following improved abilities:

• It Thinks Smarter while Consuming Less Tokens: The 2506 version reaches better accuracy on multimodal reasoning benchmarks: 56.9 on MathVision (+20.1), 80.1 on MathVista (+8.4), 46.3 on MMMU-Pro (+3.3), 64.0 on MMMU (+2.1), while in average requires 20% reduced thinking length.
• It Sees Clearer with Thinking: Unlike the previous version that specializes on thinking tasks, the 2506 version can also achieve the same or even better ability on general visual perception and understanding, e.g. MMBench-EN-v1.1 (84.4), MMStar (70.4), RealWorldQA (70.0), MMVet (78.4), surpassing or matching abilties of our non-thinking model (Kimi-VL-A3B-Instruct).
• It Extends to Video Scenarios: The new 2506 version also improves on video reasoning and understanding benchmarks. It sets new state-of-the-art for open-source models on VideoMMMU (65.2), while also retains good ability on general video understanding (71.9 on Video-MME, matching Kimi-VL-A3B-Instruct).
• It Extends to Higher Resolution: The new 2506 version supports 3.2 million total pixels in a single image, 4X compared to the previous version. This leads to non-trivial improvements on high-resolution perception and OS-agent grounding benchmarks: 83.2 on V* Benchmark (without extra tools), 52.8 on ScreenSpot-Pro, 52.5 on OSWorld-G (full set with refusal).

2. Performance

Comparison with efficient models and two previous versions of Kimi-VL (*Results of GPT-4o is for reference here, and shown in italics):

Comparison with 30B-70B open-source models: