Keye-VL-1.5 is a cutting-edge Multimodal Large Language Model (MLLM) that addresses fundamental challenges in video comprehension. It features a novel Slow-Fast video encoding strategy, a progressive four-stage pre-training methodology to extend context length up to 128K tokens, and a comprehensive post-training pipeline focusing on reasoning enhancement and human preference alignment. The model demonstrates significant improvements in video understanding tasks and maintains competitive performance on general multimodal benchmarks. See keye-vl-utils/README.md for details. contains a set of helper functions for processing and integrating visual language information with Keye Series Model. The Kwai Keye-VL-1.5 model architecture is based on the Qwen3-8B language model and incorporates a vision encoder initialized from the open-source SigLIP. It supports SlowFast video encoding and native dynamic resolution, preserving the original aspect ratio of images by dividing each into a 14x14 patch sequence. A simple MLP layer then maps and merges the visual tokens. The model uses 3D RoPE for unified processing of text, image, and video information.

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Keye-VL-2.0-30B-A3B

Kwai-Keye

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Visual QA

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Keye-VL-2.0-30B-A3B-GGUF

Kwai-Keye

Meet Keye-VL-2.0-30B-A3B — the latest 30B-class flagship base model in the Keye series, purpose-built to push the frontier of long-video understanding and to unlock the first generation of Agent capabilities in the Keye family. As the first multi-modal model to land DSA in production, Keye-VL-2.0-30B-A3B delivers nearly lossless reasoning over 256K ultra-long context. It tops video understanding benchmarks at its scale and consistently rivals — or surpasses — top-tier closed-source models on fine-grained temporal perception. More importantly, it is the first Keye base model to ship with a built-in Agent collaboration mechanism, demonstrating solid system-level orchestration in Search, Tool, and Code scenarios. We compare Keye-VL-2.0-30B-A3B against leading open- and closed-source models (Qwen3.5-35B-A3B, InternVL3.5-241B-A28B, GPT-5-mini, Qwen3-VL 30B-A3B / 32B / 235B-A22B) across **seven capability dimensions**: Video, Coding, Agent, Math & Reasoning, STEM, Instruction Following, and General VQA.

Visual QA

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Kwaipilot

This repository contains the model weights and configuration files for the post-trained KAT-Coder-V2.5-Dev in the Hugging Face Transformers format. The artifacts are compatible with Hugging Face Transformers, vLLM, SGLang, KTransformers, etc. Note: this open-weight release ships only the language-model weights and operates as a text-only model; the vision/multimodal components are not included and are unavailable. Following the release of KAT-Coder-V2.5 in July, we are pleased to release the open-weight version **KAT-Coder-V2.5-Dev**, an MOE model with a total parameter count of 35B and 3B activated parameters, to strengthen communication with the community and showcase our research achievements. Benchmark KAT-Coder-V2.5-Dev Qwen3.5-27B Qwen3.6-35BA3B Gemma4-31B Qwen3.5-35BA3B Ornith-1.0-35B Gemma4-26BA4B Qwen3-Coder-30B

Text generation

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KAT-Dev

Kwaipilot

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