Gemini 3 Pro vs Qwen-Long
Compare pricing, context windows, and strengths for Gemini 3 Pro by Google and Qwen-Long by Alibaba Cloud - and see how to put either to work in Appaca.
Gemini 3 Pro
Google's most intelligent multimodal model designed for advanced reasoning, coding, and agentic tasks.
View Gemini 3 ProQwen-Long
Long-context model with 10M tokens for huge document analysis and summarization.
View Qwen-LongGemini 3 Pro vs Qwen-Long at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | Gemini 3 Pro | Qwen-Long |
|---|---|---|
| Provider | Alibaba Cloud | |
| Model type | Text | Text |
| Context window | 1M tokens | 10M tokens |
| Input price | $4 / 1M tokens | $0.072 / 1M tokens |
| Output price | $18 / 1M tokens | $0.287 / 1M tokens |
| Status | Superseded by Gemini 3.1 Pro | Current |
How Gemini 3 Pro and Qwen-Long differ
What the numbers mean in practice when choosing between Gemini 3 Pro and Qwen-Long.
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Qwen-Long is 98% cheaper on input tokens ($0.072 vs $4 per million), which adds up quickly in document-heavy workloads.
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Qwen-Long is 98% cheaper on output tokens ($0.287 vs $18 per million) - the bigger factor for tools that generate long documents.
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Qwen-Long's 10M tokens context window is roughly 10x larger than Gemini 3 Pro's 1M tokens, so it can work across bigger codebases, contracts, or archives in one pass.
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Gemini 3 Pro has been superseded by Gemini 3.1 Pro - for new builds, consider the newer model first.
Strengths side by side
Where each model shines, according to benchmarks and provider positioning.
Gemini 3 Pro
1. State-of-the-art reasoning
- Top performance across academic reasoning, scientific knowledge, math, and complex problem-solving.
- Excels at long-horizon, multi-step workflows and deep logical interpretation.
2. World-leading multimodal capabilities
- Natively understands text, images, videos, audio, and code.
- Ranked highest on benchmarks like MMMU-Pro, Video-MMMU, ScreenSpot-Pro.
3. Exceptional coding + agentic workflows
- Strong in competitive coding and real-world agentic tasks (SWE-Bench Verified, Terminal-Bench, LiveCodeBench).
- Improved tool calling, planning, and execution for autonomous or semi-autonomous agents.
4. Powerful for long-context tasks
- Effective at 128K-1M context windows with high retrieval accuracy.
- Ideal for document-heavy workflows, research, analysis, multi-file coding, and multi-document reasoning.
5. Strong information synthesis and interpretation
- Outperforms peers in chart reasoning, OCR, structured extraction, and screen understanding.
- Excellent at combining multimodal inputs into coherent, concise answers.
6. High reliability for enterprise tasks
- Benchmarks show superior factuality, grounding, and parametric knowledge.
- Strong multilingual accuracy and global commonsense performance.
7. Optimized for production agents
- Designed for complex multi-step planning, simultaneous task execution, and improved consistency.
- Works across coding, research, creative workflows, UI generation, and data-heavy applications.
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 Gemini 3 Pro or Qwen-Long - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by Gemini 3 Pro 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 Gemini 3 Pro or Qwen-Long. No code, no API keys, no deployment.
Switch models without rebuilding
Start on Gemini 3 Pro, 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 Gemini 3 Pro or Qwen-Long - connected to the tools you already use.
Related comparisons
See how Gemini 3 Pro 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 $4 / $18 for Gemini 3 Pro. 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 Gemini 3 Pro. 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 Gemini 3 Pro, 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 Gemini 3 Pro, 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 Gemini 3 Pro 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.