Qwen: Qwen3.5-35B-A3B

Within the crowded assistant category, most models force a choice between efficiency and capability, and the Qwen3.5 family stakes out the middle ground. The 35B-A3B variant uses a hybrid design that combines linear attention with a sparse mixture-of-experts layer, activating only a fraction of its parameters per token to keep inference efficient without shedding the reasoning it needs. It offers a 262,144-token context window, image input, chain-of-thought reasoning, function calling, and structured JSON output, priced at $0.14 per million input tokens and rated cheaper than roughly three-quarters of comparable models. A fitting job is analyzing a long technical report alongside its embedded diagrams, then emitting a structured summary an agent can route onward. Against Claude, ChatGPT, Gemini, and Claude Sonnet 5, which lead on peak quality at higher prices, this model competes on efficiency per dollar and a large window, using its sparse architecture to stretch each token further. Ideal for teams building agent pipelines who need vision plus reasoning at mid-tier cost and want to scale without frontier-model bills. The absence of a free tier means usage is billed per token from the outset. Choose it when you want a balance of capability and efficiency in one deployable model; pass if your workload is small enough that a cheaper sibling would do, or demanding enough to justify a frontier name.