Qwen3.5 Plus 2026-02-15

The Qwen3.5 Plus represents a hosted production tier built atop a hybrid architecture that blends linear attention through Gated Delta Networks with a sparse mixture-of-experts design. The open-weight foundation it draws from contains 397 billion total parameters, yet activates only 17 billion per forward pass—dramatically cutting computational overhead while preserving the model's full capability ceiling. This architectural philosophy treats inference efficiency as a core feature rather than an afterthought, allowing the model to handle complex, multi-turn tasks across vision and language without the deployment burden that typically accompanies models at this scale.

The Plus tier layers production infrastructure onto that foundation, adding official built-in tool integrations—including search and code interpreter—and an adaptive tool-use system where the model autonomously decides when to invoke these capabilities. This moves beyond the manual tool-calling pipelines common in open-weight deployments, which typically require 8 or more GPUs and custom integration work. The architecture's linear attention mechanism specifically accelerates long-context decoding, making the model's native the cataloged API limit practical for real workloads rather than theoretical. Supporting 201 languages, the model serves as a unified multimodal endpoint that can process text, images, and video within a single context window—positioning it as a general-purpose reasoning and generation layer for applications that need to operate across modalities and languages at scale.