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Get started freeGPT-5.1 vs Gemini 3.1 Pro
Compare GPT-5.1 and Gemini 3.1 Pro. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | GPT-5.1 | Gemini 3.1 Pro |
|---|---|---|
| Provider | OpenAI | |
| Model Type | text | text |
| Context Window | 400,000 tokens | 1,048,576 tokens |
| Input Cost | $1.25/ 1M tokens | $4.00/ 1M tokens |
| Output Cost | $10.00/ 1M tokens | $18.00/ 1M tokens |
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Strengths & Best Use Cases
GPT-5.1
OpenAI1. Configurable Reasoning for Agentic Tasks
- Built to excel in autonomous or semi-autonomous coding workflows, with adjustable reasoning effort for planning, refactoring and debugging.
2. Fast Multi-Modal Input with Large Output
- Accepts both text and image inputs while producing text outputs.
- Offers up to 128 k output tokens, allowing long responses and code generation across multiple files.
3. Large Context & Knowledge Cut-Off
- 400 k token context window supports processing large codebases or documents.
- Knowledge cut-off of Sep 30 2024 ensures familiarity with recent tools and frameworks.
4. Reasoning Token Support
- Provides explicit support for reasoning tokens, enabling developers to fine-tune the balance between reasoning depth and speed.
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-5.1
textCode Review Assistant
Get constructive feedback on your code regarding performance, security, and readability.
Blog Post Outline Generator
Generate detailed outlines for blog posts to streamline your writing process and ensure comprehensive coverage.
Content Hub (Central Resource Library)
Create a website content hub that centralizes resources related to persona challenges and positions your USP as the solution.
Best for Gemini 3.1 Pro
textZero-Click SERP ROI Strategy
Build an SEO strategy to generate business value even when the SERP answers the question (snippets, PAA, AI overviews).
AI Tutor - Concept Explainer
Create an AI tutor that explains complex concepts in simple terms, adapting to the students learning level and style.
Learning Objectives Generator
Create clear, measurable learning objectives aligned to standards using Blooms Taxonomy action verbs.
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