Qwen3.5 4B

Qwen3.5 4B is a conversational language model released by Alibaba as part of its Qwen3.5 model family. The "4B" in the name indicates a parameter count in the range of about 4 billion, which places it at the small end of the family rather than among its larger siblings. Models in this size class are typically used where serving cost, memory footprint, or local deployment matter more than maximum capability on hard reasoning tasks. Our database records Qwen3.5 4B as a chat model and tracks independent serving measurements for it: approximately 17.5 output tokens per second and a time to first token of roughly 580 milliseconds, as measured by Artificial Analysis. Those figures reflect a specific measured endpoint rather than a property of the model itself — throughput and latency for small models vary widely between providers, quantization levels, and batch settings, and a 4B model is generally capable of much higher throughput on dedicated hardware than a shared API endpoint may deliver. We do not currently track a confirmed context window, modality list, or benchmark accuracy scores for this entry. In practice, small Qwen chat models are used for high-volume, cost-sensitive text work — classification, extraction, summarization, routing, and drafting — and as a local or on-premise option where a smaller parameter count fits available GPU memory. If your workload involves long multi-step reasoning, complex agentic tool chains, or difficult code generation, the larger members of the Qwen3.5 family or larger models from other creators are the more usual comparison points. Check the pricing table on this page for the providers currently serving Qwen3.5 4B and how their offerings differ.