Qwen3.5 0.8B (Reasoning)

Qwen3.5 0.8B is a compact, high-efficiency language model developed by Alibaba's Qwen team as part of the Qwen3.5 "Small" series. Optimized for edge computing, mobile devices, and low-power sensors, it is designed to deliver advanced reasoning and multimodal capabilities within a sub-billion parameter footprint. The model is built using early fusion training on trillions of multimodal tokens, allowing it to process text, images, and video natively.

The model utilizes a sophisticated hybrid architecture featuring Gated Delta Networks (GDN). This design employs a 3:1 ratio of linear attention layers to full attention layers, which facilitates a massive 262,144-token context window. By using linear layers for routine computations with constant memory usage and reserved full attention for precise calculations, the architecture effectively bypasses the "memory wall" typically associated with long-context small models.

While the 0.8B variant operates in a non-thinking mode by default to optimize for latency, it supports an optional thinking mode for complex reasoning tasks. This enables the model to perform structured chain-of-thought processing, making it suitable for agentic workflows and local reasoning applications. It also features 3D convolution in its visual encoder, enabling it to understand motion in videos and perform spatial reasoning tasks directly on-device.