Qwen3.8-27B is a compact, open-weight dense multimodal model designed for advanced coding, professional work, research, visual understanding, and long-horizon agentic tasks. Built on the Qwen3.5 architecture, it contains 27B parameters and combines Gated DeltaNet with gated attention across 64 layers. The model natively understands text, images, and videos, including documents, STEM diagrams, and hour-scale video content. Agent capabilities emphasize autonomous planning, environment feedback, computer and browser use, and reliable completion of complex multi-step workflows. Qwen3.8-27B supports a native 262,144-token context window that can be extended to one million tokens. Thinking is enabled by default, with low, medium, and xhigh reasoning-effort settings and preserved reasoning across conversations. It also delivers substantial improvements over Qwen3.6-27B on coding and agent benchmarks while remaining deployment-friendly and compatible with Transformers, vLLM, SGLang, etc.
Features
- 27B-parameter dense language model with vision encoder
- Native text, image, and video understanding
- 262K native context, extensible up to 1M tokens
- Hybrid Gated DeltaNet and gated attention architecture
- Advanced agentic coding and repository-level engineering
- Autonomous planning, computer use, and browser interaction
- Low, medium, and xhigh configurable reasoning effort
- Preserve-thinking support for long multi-turn workflows