Qwen-Omni-Turbo vs Qwen3-Omni-Flash
Compare pricing, context windows, and strengths for Qwen-Omni-Turbo by Alibaba Cloud and Qwen3-Omni-Flash by Alibaba Cloud - and see how to put either to work in Appaca.
Qwen-Omni-Turbo
Multimodal turbo model supporting text, image, audio, and video with fast output.
View Qwen-Omni-TurboQwen3-Omni-Flash
Hybrid thinking multimodal model with upgraded vision, audio, and agent abilities.
View Qwen3-Omni-FlashQwen-Omni-Turbo vs Qwen3-Omni-Flash at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | Qwen-Omni-Turbo | Qwen3-Omni-Flash |
|---|---|---|
| Provider | Alibaba Cloud | Alibaba Cloud |
| Model type | Multimodal | Multimodal |
| Context window | 32.8K tokens | 65.5K tokens |
| Input price | $0.058 / 1M tokens | $0.43 / 1M tokens |
| Output price | $0.23 / 1M tokens | $1.66 / 1M tokens |
| Status | Current | Current |
How Qwen-Omni-Turbo and Qwen3-Omni-Flash differ
What the numbers mean in practice when choosing between Qwen-Omni-Turbo and Qwen3-Omni-Flash.
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Qwen-Omni-Turbo is 87% cheaper on input tokens ($0.058 vs $0.43 per million), which adds up quickly in document-heavy workloads.
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Qwen-Omni-Turbo is 86% cheaper on output tokens ($0.23 vs $1.66 per million) - the bigger factor for tools that generate long documents.
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Qwen3-Omni-Flash's 65.5K tokens context window is roughly 2x larger than Qwen-Omni-Turbo's 32.8K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
Qwen-Omni-Turbo
1. Fast multimodal understanding
- Handles text, audio, images.
2. Supports text+audio outputs
- Great for assistants and education.
3. Strong cross-modal alignment
- Solid for recognition, instructions, and conversion tasks.
Qwen3-Omni-Flash
1. Advanced multimodal reasoning
- Vision, audio, video inputs.
2. Supports thinking mode
- Unique for multimodal.
3. 17 voices, 10 languages
- Great for voice agents.
4. Designed for real-world interactions
- Recognition, teaching, analysis.
Use Qwen-Omni-Turbo or Qwen3-Omni-Flash - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by Qwen-Omni-Turbo or Qwen3-Omni-Flash - 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-Omni-Turbo or Qwen3-Omni-Flash. No code, no API keys, no deployment.
Switch models without rebuilding
Start on Qwen-Omni-Turbo, test the same tool on Qwen3-Omni-Flash, 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-Omni-Turbo or Qwen3-Omni-Flash - connected to the tools you already use.
Related comparisons
See how Qwen-Omni-Turbo and Qwen3-Omni-Flash stack up against other models in the directory.
FAQs
Qwen-Omni-Turbo is generally cheaper: $0.058 input / $0.23 output per million tokens, versus $0.43 / $1.66 for Qwen3-Omni-Flash. Actual cost depends on how many tokens your workload reads and writes.
Qwen3-Omni-Flash has the larger context window at 65.5K tokens, compared to 32.8K tokens for Qwen-Omni-Turbo. A larger window means the model can consider more text at once - useful for long contracts, codebases, or months of records.
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-Omni-Turbo, test the same tool on Qwen3-Omni-Flash, and switch at any time without rebuilding anything.
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-Omni-Turbo, Qwen3-Omni-Flash, 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-Omni-Turbo or Qwen3-Omni-Flash
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.