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Get started freeGPT-5.1 Codex vs Gemini 2.5 Pro Experimental
Compare GPT-5.1 Codex and Gemini 2.5 Pro Experimental. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | GPT-5.1 Codex | Gemini 2.5 Pro Experimental |
|---|---|---|
| Provider | OpenAI | |
| Model Type | text | text |
| Context Window | 400,000 tokens | 1,048,576 tokens |
| Input Cost | $1.25/ 1M tokens | $1.50/ 1M tokens |
| Output Cost | $10.00/ 1M tokens | $6.00/ 1M tokens |
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Build your first app freeStrengths & Best Use Cases
GPT-5.1 Codex
OpenAI1. Purpose-Built for Agentic Coding
- Designed specifically for environments where the model acts as an autonomous or semi-autonomous coding agent.
- Optimized for multi-step reasoning in code tasks such as planning, refactoring, debugging, file generation, and tool coordination.
2. Enhanced Coding Intelligence
- Extends GPT-5.1's advanced reasoning capabilities to handle complex software architecture decisions.
- Better accuracy in code generation across languages (JavaScript, Python, TypeScript, Go, Rust, etc.).
- Produces cleaner, more idiomatic code aligned with modern frameworks and best practices.
3. Superior Tool Use & Code Navigation
- Excels at reading, understanding, and transforming multi-file codebases.
- Works well with Codex workflows that simulate real developer tooling.
- Strong at following function signatures, constraints, and code patterns within an existing project.
4. Long-Range Context Awareness
- 400,000-token context window enables the model to ingest large repositories or multiple files simultaneously.
- Supports deep analysis of project structures, dependencies, and cross-file logic.
5. Multi-Modal Development Capabilities
- Accepts text + image input and output - suitable for tasks like:
- Reading UI mockups or screenshots to generate code
- Understanding architectural diagrams
- Reviewing images of whiteboard sessions
6. Agentic Workflow Optimization
- Built to manage longer chains of thought and execution typically required in:
- Automated code repair
- Project bootstrapping
- Linting and migration tasks
- Long-running coding agents using planning + execution loops
7. Continually Updated Model Snapshot
- Codex-specific version receives regular upgrades behind the scenes.
- Ensures the latest coding improvements without requiring developers to update model names.
8. Reliable Instruction Following
- Highly consistent in honoring explicit constraints:
- Code styles
- Folder structures
- API contracts
- Framework conventions
9. Broad API Support
- Works across Chat Completions, Responses API, Realtime, Assistants, and more.
- Ideal for apps that need live, reasoning-heavy coding agents or generative dev environments.
Gemini 2.5 Pro Experimental
Google1. State-of-the-art reasoning performance
- #1 on LMArena human preference leaderboard.
- Excels at advanced reasoning benchmarks like GPQA and AIME 2025.
- Achieves 18.8% on Humanity's Last Exam (no tools), representing frontier human-level reasoning.
2. New “thinking model” architecture
- Built with explicit reasoning steps internally before responding.
- Handles complex, multi-stage logic with higher accuracy and fewer hallucinations.
3. Elite science and mathematics capabilities
- Leads in math and science tasks across industry benchmarks.
- High performance without costly inference tricks like majority voting.
4. Exceptional coding abilities
- Major leap over Gemini 2.0 in coding performance.
- 63.8% on SWE-Bench Verified with custom agent setup.
- Strong at code transformation, debugging, and building agentic apps.
- Capable of generating full applications (e.g., a playable video game) from a single-line prompt.
5. Massive multimodal context
- Ships with a 1,000,000 token window (2M coming soon).
- Handles entire documents, datasets, video sequences, audio files, and large codebases.
- Maintains strong performance even at extreme context lengths.
6. Native multimodality across all inputs
- Understands and reasons over text, images, audio, video, and code.
- Designed for real-world, multi-source problem-solving and agent workflows.
7. Consistent high-quality outputs
- Improved post-training results in more accurate, coherent, and stylistically strong responses.
- Higher reliability across complex workloads.
8. Early availability for developers
- Available today in Google AI Studio for experimentation.
- Coming soon to Vertex AI with higher rate limits and production-ready access.
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 Codex
textTechnical Debt Analysis
Analyse and prioritise technical debt in a codebase or system.
Async Team Update Template
Write a structured async update to keep a remote team informed without meetings.
SMART Goal Refinement
Refine a vague goal into a specific, measurable, achievable SMART goal.
Best for Gemini 2.5 Pro Experimental
textGroup Activity Decision Message
Write a group message to help a travel group make a decision on an activity. Organized and democratic.
Long-Term Lead Nurture Sequence
Write a 6-month real estate lead nurture email sequence. Keeps the agent top of mind for leads not yet ready to buy or sell.
Homebuyer Offer Letter
Write a personal homebuyer letter to accompany a purchase offer. Builds an emotional connection with sellers to strengthen the bid.