qwen3.5-flash

By price, qwen3.5-flash ranks 2nd cheapest of 68 on input and 2nd on output. Its quality score of 82 ranks 45th of 68, and on value (quality score ÷ output price) it ranks 2nd of 68. Its blended rate sits 98% below the catalog average.

In real billing terms: a support chatbot handling 50,000 turns a month (2,000 input / 500 output tokens each) costs about $6.25 per month on qwen3.5-flash, while a RAG workload of 20,000 queries (8,000 input / 800 output tokens each) runs about $6.88. Because output is priced 4.3× input here, long-generation tasks scale cost fastest — cap output length before you optimise anything else.

A 1000K context window holds roughly 1,333 pages of A4 text (at ~750 tokens per page), ranking 22nd of 68 here. That is enough to drop in an entire technical manual or several source files at once, which suits long-document summarization and codebase-wide analysis. Output runs at about 200 tok/s (5th fastest of 68), fast enough for real-time interaction and high-throughput batches.

We track 6 Alibaba models, and qwen3.5-flash's blended rate sits 93% below that provider's average. Among the models tracked here it is already one of the cheapest options at this quality level. Going the other way, Hunyuan HY3 scores 87 on quality for about 81% more.

The closest model in Alibaba's line-up is qwen-turbo ($0.05 input / $0.20 output, quality 74). Against it, qwen3.5-flash scores 8 points higher on quality, runs 40 tok/s slower (about 17%), costs 59% less blended. When two models sit this close on price, the deciding factor is usually the quality ceiling — run both against your real prompts before picking.