Qwen3.5-Flash — Hosted Speed When It Matters

Qwen3.5-Flash delivers the fastest response times in the Qwen 3.5 lineup. Perfect for quick questions and lightweight workflows. Try it free.

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Qwen3.5-Flash
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Qwen3.5-Flash is ready

Qwen3.5-Flash is the default model for this page. Lowest-latency Qwen 3.5 option for quick questions, lightweight workflows, and retries.

Pick a model, decide whether this needs web search or thinking, then start with a real prompt.
Fast
Low Cost

Starter prompts

Free to try in the browser. Flash uses Qwen3.5-35B-A3B as its public reference base.

Optimized For
Speed
Model Type
Hosted
Context
1M default
Base Model
35B-A3B
Overview

Built for Low-Latency Workloads

Qwen3.5-Flash is a hosted model built on Qwen3.5-35B-A3B. It keeps the fast MoE base and adds a larger default context window plus hosted tooling.

1M Default Context

Alibaba Cloud documents a 1M default context window for the hosted Flash route.

Base Model

Flash scores are based on Qwen3.5-35B-A3B, the closest public reference in the family.

Hosted Tooling

The hosted version is documented with built-in tools and production features beyond the public base checkpoint.

Qwen3.5-Flash Benchmark

How Qwen3.5-Flash compares to nearby models in the Qwen family.

Qwen3.5-9B

Light dense model for quick prompts and lightweight coding.

Updated 2026-04-02
MMLU-Pro
82.5
GPQA / GPQA-family
81.7
LiveCodeBench v6
65.6

Qwen3.5-35B-A3B

Compact MoE model, also the base model behind Qwen3.5-Flash.

Updated 2026-04-02
MMLU-Pro
85.3
GPQA / GPQA-family
84.2
LiveCodeBench v6
74.6

Qwen3.5-Flash

Hosted

Hosted version built on Qwen3.5-35B-A3B with additional tooling and a 1M context window.

Scores reference the Qwen3.5-35B-A3B base model.

Updated 2026-04-02
MMLU-Pro
85.3
GPQA / GPQA-family
84.2
LiveCodeBench v6
74.6

Scores are from public model cards and the qwen.ai release page. Hosted models are labeled with their open-weight base.

Updated 2026-04-02
Use Cases

What Qwen3.5-Flash Is Best For

Flash is the route to pick when response time matters more than squeezing out the last bit of reasoning depth.

Real-Time Chat

Power instant-response chatbots and customer support interfaces.

Quick Q&A

Answer simple factual questions with minimal latency.

Batch Processing

Process large volumes of text quickly for classification, extraction, or tagging.

Prompt Iteration

Test and refine prompts rapidly before running them on larger models.

Autocomplete

Power inline suggestions and code completions with minimal delay.

High-Volume Workloads

Keep latency low in chat, support, routing, and other fast feedback loops.

FAQ

Qwen3.5-Flash FAQ

Common questions about the Flash model.

1

What model are Flash scores based on?

Flash uses Qwen3.5-35B-A3B as its public reference base. The hosted version then adds the low-latency serving layer, tools, and 1M context window.

2

Is Flash good enough for production?

Yes, when your workload is latency-sensitive and you want a hosted endpoint. If you need deeper reasoning or a fully public open-weight checkpoint, move up to 27B, 122B-A10B, 397B-A17B, or the matching 35B-A3B base release.

3

How does Flash compare to Qwen3.5-9B?

They solve different problems. Flash is the hosted speed-first path; 9B is the smallest public dense checkpoint. Pick Flash for low-latency hosted use, and 9B when you want the small open-weight release.

4

Can I self-host Flash?

Not as the identical hosted product. If you need the closest public reference for self-hosting, use Qwen3.5-35B-A3B and treat Flash as the hosted production layer built on top of it.

5

What is Flash's context window?

1M tokens by default. This is larger than the 262K native context on the open Qwen 3.5 models.

6

Is Flash free to use here?

Yes. You can try Qwen3.5-Flash for free on this site. It is a hosted model accessed through APIs.

7

When should I use Flash vs Plus?

Use Flash when speed matters most. Use Plus when you need stronger reasoning and are willing to trade some latency for quality.

8

Does Flash support tool calling?

Yes. Flash is a hosted model with built-in tool support. It works well for lightweight tool flows where latency matters more than maximum reasoning depth.