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Qwen-Flash vs Qwen-Turbo

Compare pricing, context windows, and strengths for Qwen-Flash by Alibaba Cloud and Qwen-Turbo by Alibaba Cloud - and see how to put either to work in Appaca.

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Qwen-Flash

The fastest and cheapest Qwen model, ideal for high-volume workloads.

View Qwen-Flash
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Qwen-Turbo

Fast, low-cost model for general tasks; being phased out in favor of Flash.

View Qwen-Turbo

Qwen-Flash vs Qwen-Turbo at a glance

Specs and pricing side by side, from the Appaca AI models directory.

Spec Qwen-Flash Qwen-Turbo
Provider Alibaba Cloud Alibaba Cloud
Model type Text Text
Context window 1M tokens 1M tokens
Input price $0.022 / 1M tokens $0.044 / 1M tokens
Output price $0.216 / 1M tokens $0.431 / 1M tokens
Status Current Current
Key differences

How Qwen-Flash and Qwen-Turbo differ

What the numbers mean in practice when choosing between Qwen-Flash and Qwen-Turbo.

  • Qwen-Flash is 50% cheaper on input tokens ($0.022 vs $0.044 per million), which adds up quickly in document-heavy workloads.

  • Qwen-Flash is 50% cheaper on output tokens ($0.216 vs $0.431 per million) - the bigger factor for tools that generate long documents.

  • Both models offer the same 1M tokens context window.

Strengths side by side

Where each model shines, according to benchmarks and provider positioning.

Qwen-Flash

1. Ultra-fast, ultra-cheap

  • Designed for mass-scale workloads.
  • Excellent for rewriting, extraction, classification.

2. Limited reasoning but great utility

  • High throughput, low latency.

3. Optional thinking mode

  • Adds chain-of-thought when needed.

4. Supports context cache & batch calls

  • Very cost-effective system design.

Qwen-Turbo

1. Fast and affordable

  • Good for standard LLM workloads.

2. Supports thinking mode

  • Allows moderate reasoning.

3. Being replaced by Qwen-Flash

  • Flash has better pricing and performance.
Appaca

Use Qwen-Flash or Qwen-Turbo - or both

Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by Qwen-Flash or Qwen-Turbo - connected to your real data and ready for your whole team. No code, no deployment.

Describe it, and it's built

Tell the Appaca agent the internal tool you need and it builds a working app powered by Qwen-Flash or Qwen-Turbo. No code, no API keys, no deployment.

Switch models without rebuilding

Start on Qwen-Flash, test the same tool on Qwen-Turbo, and keep whichever performs better - the rest of your app stays exactly as it is.

Automated for the whole team

Schedule tools to run on autopilot - daily digests, weekly reports, real-time triggers - and share them with your whole team from one workspace.

Describe it, and it's built

Tell the Appaca agent what your team needs and it builds a working app powered by Qwen-Flash or Qwen-Turbo - connected to the tools you already use.

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FAQs

Is Qwen-Flash cheaper than Qwen-Turbo?

Qwen-Flash is generally cheaper: $0.022 input / $0.216 output per million tokens, versus $0.044 / $0.431 for Qwen-Turbo. Actual cost depends on how many tokens your workload reads and writes.

Which has the larger context window, Qwen-Flash or Qwen-Turbo?

They are equal: both Qwen-Flash and Qwen-Turbo support a 1M tokens context window.

Should I use Qwen-Flash or Qwen-Turbo?

It depends on the job. Compare the pricing, context window, and strengths above against your workload - and remember the choice isn't permanent. In Appaca you can build a tool on Qwen-Flash, test the same tool on Qwen-Turbo, and switch at any time without rebuilding anything.

Can I use Qwen-Flash and Qwen-Turbo without writing code?

Yes. Appaca is a no-code AI workspace: describe the internal tool your team needs and the Appaca agent builds it as a working app powered by Qwen-Flash, Qwen-Turbo, or any other model in the directory - with a built-in database, team access, and integrations. No API keys to wire up and nothing to deploy.

Build AI tools with Qwen-Flash or Qwen-Turbo

Describe the tool your team needs and get a working app powered by the model you choose - with a built-in database, team access, and integrations. No code, no deployment.