Qwen: Qwen3.5 Plus 2026-02-15

What genuinely separates this February 2026 Plus release from the obvious alternatives is its native vision-language design built on a hybrid architecture that pairs linear attention with a sparse mixture-of-experts model for higher inference efficiency, which the data says shows across a range of benchmarks. That efficiency pays off in a task like analyzing a batch of marketing images against a long brand-guidelines document, where a 1,000,000-token context window holds the guidelines and structured JSON output returns each verdict cleanly. Chain-of-thought reasoning, image input, and tool and function calling are all present. Compared with ChatGPT or Gemini, which lead with polished consumer chat, the differentiator here is that mixture-of-experts vision-language build offered at a low $0.26 per 1M tokens; against the costlier Claude Sonnet 5, it trades brand depth for inference economy. The single caveat the data records is no free tier, so usage bills per token from the start. Ideal for teams needing efficient image-and-text reasoning at volume who care about the unit cost of inference. A strong pick where multimodal throughput and price drive the choice; less suitable if you want a ready-made consumer assistant or the ability to trial it at no cost first.