GPT-5.5 vs Qwen3-Omni-Flash
Compare pricing, context windows, and strengths for GPT-5.5 by OpenAI and Qwen3-Omni-Flash by Alibaba Cloud - and see how to put either to work in Appaca.
GPT-5.5
OpenAI's smartest and most capable model yet for agentic coding, knowledge work, and computer use, delivering a new class of intelligence at GPT-5.4 latency.
View GPT-5.5Qwen3-Omni-Flash
Hybrid thinking multimodal model with upgraded vision, audio, and agent abilities.
View Qwen3-Omni-FlashGPT-5.5 vs Qwen3-Omni-Flash at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.5 | Qwen3-Omni-Flash |
|---|---|---|
| Provider | OpenAI | Alibaba Cloud |
| Model type | Text | Multimodal |
| Context window | 1M tokens | 65.5K tokens |
| Input price | $5 / 1M tokens | $0.43 / 1M tokens |
| Output price | $30 / 1M tokens | $1.66 / 1M tokens |
| Status | Current | Current |
How GPT-5.5 and Qwen3-Omni-Flash differ
What the numbers mean in practice when choosing between GPT-5.5 and Qwen3-Omni-Flash.
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Qwen3-Omni-Flash is 91% cheaper on input tokens ($0.43 vs $5 per million), which adds up quickly in document-heavy workloads.
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Qwen3-Omni-Flash is 94% cheaper on output tokens ($1.66 vs $30 per million) - the bigger factor for tools that generate long documents.
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GPT-5.5's 1M tokens context window is roughly 15.3x larger than Qwen3-Omni-Flash's 65.5K tokens, so it can work across bigger codebases, contracts, or archives in one pass.
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These are different kinds of model: GPT-5.5 is a text model while Qwen3-Omni-Flash is a multimodal model, so they often complement each other in a workflow rather than compete.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
GPT-5.5
1. Strongest Agentic Coding Model
- State-of-the-art on Terminal-Bench 2.0 (82.7%), Expert-SWE (73.1%), and SWE-Bench Pro (58.6%), outperforming GPT-5.4 on complex coding tasks.
- Holds context across large systems, reasons through ambiguous failures, and carries changes through surrounding codebases with fewer tokens.
2. Higher Intelligence at GPT-5.4 Latency
- Co-designed, trained, and served on NVIDIA GB200/GB300 NVL72 systems to match GPT-5.4 per-token latency while performing at a significantly higher level.
- Uses fewer tokens to complete the same tasks, making it more efficient as well as more capable.
3. Powerful for Knowledge Work & Computer Use
- Scores 84.9% on GDPval (44 occupations) and 78.7% on OSWorld-Verified for autonomous computer operation.
- Excels at generating documents, spreadsheets, and reports; naturally moves across finding information, using tools, and checking output.
4. Scientific Research Co-Scientist
- Leading performance on GeneBench, BixBench, and FrontierMath; helped discover a new proof about Ramsey numbers verified in Lean.
- Strong enough to meaningfully accelerate progress at the frontiers of biomedical and mathematical research.
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 GPT-5.5 or Qwen3-Omni-Flash - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5.5 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 GPT-5.5 or Qwen3-Omni-Flash. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.5, 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 GPT-5.5 or Qwen3-Omni-Flash - connected to the tools you already use.
Related comparisons
See how GPT-5.5 and Qwen3-Omni-Flash stack up against other models in the directory.
FAQs
Qwen3-Omni-Flash is generally cheaper: $0.43 input / $1.66 output per million tokens, versus $5 / $30 for GPT-5.5. Actual cost depends on how many tokens your workload reads and writes.
GPT-5.5 has the larger context window at 1M tokens, compared to 65.5K tokens for Qwen3-Omni-Flash. 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 GPT-5.5, 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 GPT-5.5, 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 GPT-5.5 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.