Qwen3.5 Flash, the Alibaba Cloud (Qwen) model in numbers

What you need to know

Qwen3.5 Flash is a language model from Alibaba Cloud (Qwen), released on February 23, 2026. That makes it 8 months old as of October 22, 2026. It is a closed model: you access it through an API, from Alibaba Cloud (Qwen) or one of the 9 providers listed on models.dev. It has a reasoning mode: it can "think" before answering, which helps with multi-step problems but uses more tokens, and therefore more money.

We file it under budget models (24 models in this category on the site).

Pricing and budget

Qwen3.5 Flash costs $0.10 per million input tokens and $0.40 per million output tokens (developer's price, checked on October 22, 2026).

To put it in perspective: reading 20,000 tokens (about thirty pages) and writing 2,000 costs roughly $0.003; a thousand of those tasks, $2.8.

That is 2.8 times cheaper than the median output price of budget models ($1.13).

Tokens read back from cache cost $0.01 per million, which helps an agent that keeps resending the same context.

To estimate your own budget, use the agent cost calculator.

Measured performance

According to results published by Epoch AI (checked on October 22, 2026), Qwen3.5 Flash has a capability index of 62.6 out of 100, computed on 3 benchmarks from our basket.

With only 3 benchmarks reported, it does not enter the public ranking, which requires at least 4 results, so its index should be read as partial.

• GPQA Diamond (PhD-level science questions): 82.3% — the best tracked model, Gemini 4 Argon, reaches 96.4%
• OTIS Mock AIME (competition mathematics problems): 84.4% — the best tracked model, GPT-5.5 Pro, reaches 100%
• FrontierMath (very hard research-level mathematics): 18.2% — the best tracked model, GPT-6 Astra, reaches 93.7%

What it can do

Its context window reaches 1,000,000 tokens, roughly 1,500 pages of text at 500 words per page: enough to load a whole book or a mid-sized codebase. A single answer can run to 65,536 tokens.

It accepts as input: text, image and video.

It can call tools (functions, APIs) and return structured JSON output, which makes it a possible foundation for an AI agent.

What is it good for?

Given its category, Qwen3.5 Flash is mainly aimed at high volumes where every cent counts: sorting, information extraction, summaries, simple assistants.

Its very large context window makes it worth considering for analysing large sets of documents in a single request.

Its very low cost (under half a cent for our sample task) means it can be called thousands of times a day.

Before adopting it, test it on your own examples: benchmarks measure standard tasks, not your job.

Alternatives

In the same category, the models closest to Qwen3.5 Flash are:

• GPT-5 Mini (OpenAI, index 62.9) — see the comparison
• Qwen3.7 Flash (Alibaba Cloud (Qwen), index 63.7) — see the comparison
• Gemini 3.1 Flash Lite (Google DeepMind, index 64.3) — see the comparison
• Qwen3.6 Flash (Alibaba Cloud (Qwen), index 64.5) — see the comparison