Kimi K2.5: Visual Agentic Intelligence
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Computer Science > Computation and Language
Title:Kimi K2.5: Visual Agentic Intelligence
Abstract:We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that two modalities enhance each other. This includes a series of techniques such as joint text-vision pre-training, zero-vision SFT, and joint text-vision reinforcement learning. Building on this multimodal foundation, K2.5 introduces Agent Swarm, a self-directed parallel agent orchestration framework that dynamically decomposes complex tasks into heterogeneous sub-problems and executes them concurrently. Extensive evaluations show that Kimi K2.5 achieves state-of-the-art results across various domains including coding, vision, reasoning, and agentic tasks. Agent Swarm also reduces latency by up to $4.5\times$ over single-agent baselines. We release the post-trained Kimi K2.5 model checkpoint to facilitate future research and real-world applications of agentic intelligence.
| Comments: | Kimi K2.5 tech report |
| Subjects: | Computation and Language (cs.CL); Artificial Intelligence (cs.AI); Machine Learning (cs.LG) |
| Cite as: | arXiv:2602.02276 [cs.CL] |
| (or arXiv:2602.02276v2 [cs.CL] for this version) | |
| https://doi.org/10.48550/arXiv.2602.02276
arXiv-issued DOI via DataCite
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Submission history
From: Yulun Du [view email][v1] Mon, 2 Feb 2026 16:17:38 UTC (8,217 KB)
[v2] Fri, 7 Aug 2026 05:09:52 UTC (8,214 KB)
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