GPT-5 Pro vs Gemini 3.1 Pro
Compare pricing, context windows, and strengths for GPT-5 Pro by OpenAI and Gemini 3.1 Pro by Google - and see how to put either to work in Appaca.
GPT-5 Pro
A premium GPT-5 variant that uses more compute to deliver consistently smarter, more precise reasoning for the toughest problems.
View GPT-5 ProGemini 3.1 Pro
Google's most advanced reasoning Gemini model, built for complex multimodal problem-solving, software engineering, and long-horizon agentic workflows.
View Gemini 3.1 ProGPT-5 Pro vs Gemini 3.1 Pro at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | GPT-5 Pro | Gemini 3.1 Pro |
|---|---|---|
| Provider | OpenAI | |
| Model type | Text | Text |
| Context window | 400K tokens | 1.05M tokens |
| Input price | $15 / 1M tokens | $4 / 1M tokens |
| Output price | $120 / 1M tokens | $18 / 1M tokens |
| Status | Current | Current |
How GPT-5 Pro and Gemini 3.1 Pro differ
What the numbers mean in practice when choosing between GPT-5 Pro and Gemini 3.1 Pro.
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Gemini 3.1 Pro is 73% cheaper on input tokens ($4 vs $15 per million), which adds up quickly in document-heavy workloads.
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Gemini 3.1 Pro is 85% cheaper on output tokens ($18 vs $120 per million) - the bigger factor for tools that generate long documents.
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Gemini 3.1 Pro's 1.05M tokens context window is roughly 2.6x larger than GPT-5 Pro's 400K 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 Pro
1. Highest reasoning quality in the GPT-5 family
- Uses significantly more compute to "think harder" before responding.
- Designed for the toughest reasoning tasks where answer quality matters more than speed.
- Produces more precise, reliable, and detailed outputs than standard GPT-5.
2. Advanced multi-turn reasoning via Responses API
- Available only in the Responses API to support:
- Multi-turn internal model interactions before returning a reply.
- Advanced control patterns (e.g., background mode for long-running jobs).
- Ideal for complex workflows, deep planning, and multi-step analysis.
3. Configured for maximum effort by default
- Always runs with reasoning.effort: 'high' (no lower-effort mode).
- Prioritizes depth and correctness over latency and cost.
4. Multimodal input
- Accepts text + image as input.
- Outputs text, with strong instruction-following and analysis capabilities.
5. Tooling and ecosystem integration
- Supports Web Search, File Search, and Image Generation (as tools).
- Supports MCP and other Responses API tooling patterns.
- Does not support Code Interpreter and does not support Computer Use, keeping focus on pure reasoning + tools.
Gemini 3.1 Pro
1. Google's most advanced reasoning Gemini model
- Designed to solve complex problems across multimodal inputs, including text, audio, images, video, PDFs, and full code repositories.
- Google highlights improved software engineering behavior, better agentic performance, and stronger usability in domains like finance and spreadsheets.
2. Large multimodal context with substantial output room
- Supports a 1,048,576 token input context window for large repositories, long documents, and multi-source workflows.
- Allows up to 65,536 output tokens for longer answers, plans, and code generations.
3. More efficient thinking with expanded controls
- Improves token efficiency and reasoning performance across use cases.
- Adds the
MEDIUMthinking_leveloption to better balance cost, speed, and quality.
4. Strong support for production agents
- Supports grounding with Google Search, code execution, function calling, structured outputs, context caching, RAG, and chat completions.
- Also offers a custom-tools endpoint tuned for agentic workflows that mix bash-like tools with custom code tools.
Use GPT-5 Pro or Gemini 3.1 Pro - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by GPT-5 Pro or Gemini 3.1 Pro - 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 Pro or Gemini 3.1 Pro. No code, no API keys, no deployment.
Switch models without rebuilding
Start on GPT-5 Pro, test the same tool on Gemini 3.1 Pro, 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 Pro or Gemini 3.1 Pro - connected to the tools you already use.
Related comparisons
See how GPT-5 Pro and Gemini 3.1 Pro stack up against other models in the directory.
FAQs
Gemini 3.1 Pro is generally cheaper: $4 input / $18 output per million tokens, versus $15 / $120 for GPT-5 Pro. Actual cost depends on how many tokens your workload reads and writes.
Gemini 3.1 Pro has the larger context window at 1.05M tokens, compared to 400K tokens for GPT-5 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 GPT-5 Pro, test the same tool on Gemini 3.1 Pro, 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 Pro, Gemini 3.1 Pro, 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 Pro or Gemini 3.1 Pro
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.