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Get started freeGPT-5.1 Codex vs GPT-5 Nano
Compare GPT-5.1 Codex and GPT-5 Nano. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | GPT-5.1 Codex | GPT-5 Nano |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model Type | text | text |
| Context Window | 400,000 tokens | 400,000 tokens |
| Input Cost | $1.25/ 1M tokens | $0.05/ 1M tokens |
| Output Cost | $10.00/ 1M tokens | $0.40/ 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.
GPT-5 Nano
OpenAI1. Extremely fast performance
- Fastest model in the GPT-5 family.
- Great for real-time workflows, rapid responses, and high-throughput systems.
2. Most cost-efficient GPT-5 model
- Lowest input and output token costs.
- Suitable for large-scale or budget-sensitive applications.
3. Ideal for lightweight, well-scoped tasks
- Excels at summarization, classification, text extraction, and simple logic tasks.
- Best used when tasks are narrow and well-defined.
4. Multimodal input
- Accepts text + image as input.
- Outputs text only.
5. Broad tool support
- Supports Web Search, File Search, Image Generation (as a tool), Code Interpreter, and MCP.
- (Does not support Computer Use.)
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
textConflict Resolution Message
Write a message to address a workplace conflict directly and constructively.
Platform Engineering RFC
Write a Request for Comments (RFC) for a proposed platform change.
Pull Request Description
Write a comprehensive pull request description for a code change.
Best for GPT-5 Nano
textMobile App Crash Report Analysis
Analyse a mobile app crash report and suggest a debugging approach.
Anchor Activity Set
Design meaningful anchor activities for early finishers in a differentiated classroom.
Prepare a Case (Outcome Matrix + Preparation Plan)
Map likely outcomes for a dispute and generate a practical preparation plan across facts, evidence, procedure, and settlement.