o3 vs Gemini 3.1 Pro
Compare pricing, context windows, and strengths for o3 by OpenAI and Gemini 3.1 Pro by Google - and see how to put either to work in Appaca.
o3
A powerful reasoning model excelling at complex, multi-step tasks across math, science, coding, and visual reasoning; succeeded by GPT-5.
View o3Gemini 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 Proo3 vs Gemini 3.1 Pro at a glance
Specs and pricing side by side, from the Appaca AI models directory.
| Spec | o3 | Gemini 3.1 Pro |
|---|---|---|
| Provider | OpenAI | |
| Model type | Text | Text |
| Context window | 200K tokens | 1.05M tokens |
| Input price | $2 / 1M tokens | $4 / 1M tokens |
| Output price | $8 / 1M tokens | $18 / 1M tokens |
| Status | Current | Current |
How o3 and Gemini 3.1 Pro differ
What the numbers mean in practice when choosing between o3 and Gemini 3.1 Pro.
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o3 is 50% cheaper on input tokens ($2 vs $4 per million), which adds up quickly in document-heavy workloads.
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o3 is 56% cheaper on output tokens ($8 vs $18 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 5.2x larger than o3's 200K 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.
o3
1. Advanced reasoning capability
- Designed for multi-step thinking across text, code, and visual inputs.
- Excels at math, science, logic puzzles, and complex analytical workflows.
2. Strong performance across domains
- Highly capable in technical writing, data analysis, and structured problem-solving.
- Useful for research, engineering tasks, and intricate instruction-following.
3. Visual reasoning support
- Accepts image inputs, enabling tasks such as diagram analysis, chart interpretation, and visual logic assessments.
4. High output capacity
- Up to 100,000 output tokens, supporting long-form content, technical breakdowns, and multi-part solutions.
5. Excellent instruction following
- Produces detailed, step-by-step responses for tasks requiring precision and clarity.
- Ideal for educational explanations, system design reasoning, and code walkthroughs.
6. Large 200K context window
- Handles long documents, multi-file reasoning, or extended conversations with minimal loss of context.
7. Broad API support
- Works with Chat Completions, Responses, Realtime, Assistants, Batch, Embeddings, Image Generation, and more.
- Supports streaming and function calling for advanced workflows.
8. Positioned as a legacy reasoning model
- Remains extremely capable but formally succeeded by GPT-5, which offers stronger reasoning and performance.
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 o3 or Gemini 3.1 Pro - or both
Appaca is the AI workspace for operators. Build internal tools and AI co-workers powered by o3 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 o3 or Gemini 3.1 Pro. No code, no API keys, no deployment.
Switch models without rebuilding
Start on o3, 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 o3 or Gemini 3.1 Pro - connected to the tools you already use.
Related comparisons
See how o3 and Gemini 3.1 Pro stack up against other models in the directory.
FAQs
o3 is generally cheaper: $2 input / $8 output per million tokens, versus $4 / $18 for Gemini 3.1 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 200K tokens for o3. 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 o3, 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 o3, 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 o3 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.