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Get started freeGPT-5.1 Codex vs Claude 4 Sonnet
Compare GPT-5.1 Codex and Claude 4 Sonnet. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | GPT-5.1 Codex | Claude 4 Sonnet |
|---|---|---|
| Provider | OpenAI | Anthropic |
| Model Type | text | text |
| Context Window | 400,000 tokens | 1,000,000 tokens |
| Input Cost | $1.25/ 1M tokens | $3.00/ 1M tokens |
| Output Cost | $10.00/ 1M tokens | $15.00/ 1M tokens |
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Strengths & 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.
Claude 4 Sonnet
Anthropic- Hybrid reasoning: supports both fast (“near-instant”) and extended thinking modes.
- Optimised for responsiveness, cost and high-volume production workloads.
- Strong coding performance relative to prior Sonnet versions (improved over Sonnet 3.7).
- Available even in free tiers (alongside paid plans).
- Better suited for general-purpose use and agents where speed + cost-efficiency matter.
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
textCode Review Assistant
Get constructive feedback on your code regarding performance, security, and readability.
Cold Outreach Email Generator
Generate high-converting cold emails for sales, networking, or partnerships.
Code Generator
Generate efficient, documented, and bug-free code snippets in any programming language.
Best for Claude 4 Sonnet
textCustomer Advisory Board (CAB) Program
Design a customer advisory board that gathers persona leader insights to refine marketing strategy, strengthen your USP, and address evolving challenges.
User-Generated Content Campaign (Social Proof at Scale)
Create a UGC campaign that encourages your persona to share wins and stories that prove your USP and relate to common challenges.
Video Marketing Strategy (Storytelling + Proof)
Build a video marketing strategy that uses storytelling to show how your USP transforms persona challenges into outcomes.
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