GPT-5.5 vs Qwen-Long
Compare pricing, context windows, and strengths for GPT-5.5 by OpenAI and Qwen-Long 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-5.5Qwen-Long
Long-context model with 10M tokens for huge document analysis and summarization.
View Qwen-LongGPT-5.5 vs Qwen-Long at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5.5 | Qwen-Long |
|---|---|---|
| Provider | OpenAI | Alibaba Cloud |
| Model type | Text | Text |
| Context window | 1M tokens | 10M tokens |
| Input price | $5 / 1M tokens | $0.072 / 1M tokens |
| Output price | $30 / 1M tokens | $0.287 / 1M tokens |
| Status | Current | Current |
How GPT-5.5 and Qwen-Long differ
What the numbers mean in practice when choosing between GPT-5.5 and Qwen-Long.
-
Qwen-Long is 99% cheaper on input tokens ($0.072 vs $5 per million), which adds up quickly in document-heavy workloads.
-
Qwen-Long is 99% cheaper on output tokens ($0.287 vs $30 per million) - the bigger factor for tools that generate long documents.
-
Qwen-Long's 10M tokens context window is roughly 10x larger than GPT-5.5's 1M 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.
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.
Qwen-Long
1. Extremely long context window
- Up to 10 million tokens.
2. Ideal for document-heavy workflows
- Legal, financial, RAG, compliance, research.
3. Low-cost for large-scale ingestion
- Optimized pricing for big inputs.
Use GPT-5.5 or Qwen-Long - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5.5 or Qwen-Long - 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 Qwen-Long. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5.5, test the same tool on Qwen-Long, 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 Qwen-Long - connected to the tools you already use.
Related comparisons
See how GPT-5.5 and Qwen-Long stack up against other models in the directory.
FAQs
Qwen-Long is generally cheaper: $0.072 input / $0.287 output per million tokens, versus $5 / $30 for GPT-5.5. Actual cost depends on how many tokens your workload reads and writes.
Qwen-Long has the larger context window at 10M tokens, compared to 1M tokens for GPT-5.5. 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 Qwen-Long, 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, Qwen-Long, 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 Qwen-Long
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.