Qwen: Qwen3.5-Flash
Analysis Summary
Qwen3.5-Flash is positioned as a high-volume Qwen model with a very large 1M token context window. It accepts text, image, and video input and supports tool use and function calling, giving it a useful operational profile for document-heavy automation. The available data does not include benchmark results, so its reasoning, coding, and reliability cannot be placed confidently against measured alternatives.
The pricing strongly favours bulk traffic, including SEO classification, content preprocessing, long-document extraction, and routine multimodal transformations. Its context capacity can reduce the need to split large client materials into many requests. Design for Online should pilot it on lower-risk workflows first, then expand usage if output consistency and tool execution meet production requirements.
Assessed August 9, 2026
Editorial notes
Qwen3.5-Flash offers a 1M token context, multimodal input, tool use, and very low pricing, making it attractive for high-volume document and content workflows. It has no benchmark data here, so capability claims should be validated before critical deployment.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
Qwen3.5-Flash offers a 1M token context, multimodal input, tool use, and very low pricing, making it attractive for high-volume document and content workflows. It has no benchmark data here, so capability claims should be validated before critical deployment.
How Qwen: Qwen3.5-Flash compares
Its 1M-token context window is larger than 86% of the models we list. At $0.07 per million input tokens it is cheaper than 73% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Strongest on business fit. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.07 | $0.000065 |
| Output | $0.26 | $0.000260 |
What would Qwen: Qwen3.5-Flash cost your business?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 701 models → Price Calculator
These numbers get smaller with the right architecture.
We route routine calls to cheap models and save Qwen: Qwen3.5-Flash for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout Qwen: Qwen3.5-Flash
The Qwen3.5 native vision-language Flash models are built on a hybrid architecture that integrates a linear attention mechanism with a sparse mixture-of-experts model, achieving higher inference efficiency. Compared to the..
Frequently asked questions about Qwen: Qwen3.5-Flash
How much does Qwen: Qwen3.5-Flash cost?
Qwen: Qwen3.5-Flash costs $0.07 per million input tokens and $0.26 per million output tokens.
What is the context window of Qwen: Qwen3.5-Flash?
Qwen: Qwen3.5-Flash has a context window of 1,000,000 tokens (1M).
What can Qwen: Qwen3.5-Flash do?
Qwen: Qwen3.5-Flash supports image/vision input, tool use, and function calling.
Who created Qwen: Qwen3.5-Flash?
Qwen: Qwen3.5-Flash is developed by Qwen and was released on February 25, 2026.
