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Get started freeGPT-5.3 Codex vs Gemini 3.1 Pro
Compare GPT-5.3 Codex and Gemini 3.1 Pro. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | GPT-5.3 Codex | Gemini 3.1 Pro |
|---|---|---|
| Provider | OpenAI | |
| Model Type | text | text |
| Context Window | 400,000 tokens | 1,048,576 tokens |
| Input Cost | $1.75/ 1M tokens | $4.00/ 1M tokens |
| Output Cost | $14.00/ 1M tokens | $18.00/ 1M tokens |
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Strengths & Best Use Cases
GPT-5.3 Codex
OpenAI1. Strongest Codex Model for Agentic Engineering
- OpenAI positions GPT-5.3 Codex as its most capable agentic coding model to date.
- Built for long-horizon software engineering tasks that require planning, iteration, and reliable code transformation across files.
2. Configurable Reasoning + Multimodal Input
- Supports configurable reasoning effort from low to xhigh so teams can trade off depth against latency.
- Accepts both text and image inputs while producing text output.
3. Large Context for Real Codebases
- 400 k token context window helps it work across larger repositories, implementation plans, and supporting documentation.
- Allows up to 128 k output tokens for longer code generations, patches, and technical write-ups.
4. Current Knowledge for Modern Dev Workflows
- Knowledge cut-off of Aug 31 2025 keeps it aligned with newer frameworks, libraries, and tooling.
- Supports streaming, function calling, and structured outputs for agent-style coding workflows.
Gemini 3.1 Pro
Google1. 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.
Prompts to Get Started
Use these prompts to power AI products you build on Appaca. Each works great with the models above.
Best for GPT-5.3 Codex
textProfessional Email Rewriter
Rewrite your rough drafts into polished, professional emails suitable for any business context.
Cold Outreach Email Generator
Generate high-converting cold emails for sales, networking, or partnerships.
Bug Fixer & Debugger
Identify bugs in your code, understand why they happen, and get a corrected version.
Best for Gemini 3.1 Pro
textLearning Objectives Generator
Create clear, measurable learning objectives aligned to standards using Blooms Taxonomy action verbs.
Cold Email Generator
Generate personalized cold emails that get responses using proven frameworks and personalization techniques.
Sales Objection Flipper: Reveal Hidden Pain Points
Convert common sales objections into underlying fears and create educational content ideas that overcome them before the sales call.
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