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Get started freeGPT-5.3 Codex vs GPT-3.5 Turbo
Compare GPT-5.3 Codex and GPT-3.5 Turbo. Build AI products powered by either model on Appaca.
Model Comparison
| Feature | GPT-5.3 Codex | GPT-3.5 Turbo |
|---|---|---|
| Provider | OpenAI | OpenAI |
| Model Type | text | text |
| Context Window | 400,000 tokens | 16,385 tokens |
| Input Cost | $1.75/ 1M tokens | $0.50/ 1M tokens |
| Output Cost | $14.00/ 1M tokens | $1.50/ 1M tokens |
Stop choosing. Use both.
With Appaca you don't have to pick — build apps that are powered by GPT-5.3 Codex, GPT-3.5 Turbo, for your specific use case.
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New appStrengths & 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.
GPT-3.5 Turbo
OpenAI1. Extremely low-cost text model
- One of the cheapest legacy models available.
- Suitable for very high-volume workloads with simple requirements.
2. Good for lightweight NLP tasks
- Classification, summarization, rewriting, paraphrasing, intent detection.
- Works for simple logic tasks and short reasoning sequences.
3. Works well for basic chatbots
- Optimized for Chat Completions API, originally powering early ChatGPT use cases.
- Good for rule-based or templated conversation flows.
4. Stable and predictable outputs
- Legacy behavior makes it suitable for systems built years ago that rely on its quirks.
- Good for backward compatibility or long-term enterprise pipelines.
5. Supports fine-tuning
- Useful for teams maintaining older fine-tuned GPT-3.5 models.
- Allows domain-specific compression of older datasets.
6. Limited capabilities compared to newer models
- No vision, no audio, no streaming, and no function calling.
- Much weaker reasoning and correctness vs GPT-4o mini or GPT-5.1.
7. Small context window (16K)
- Limited for multi-document tasks or long conversations.
- Best used for short, simple prompts or structured tasks.
8. Recommended migration path
- OpenAI explicitly recommends using GPT-4o mini instead.
- 4o mini is cheaper, smarter, faster, multimodal, and far more capable.
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
textDependency Review Checklist
Create a checklist for evaluating whether to add a new library or dependency.
Email Thread Summary
Summarise a long email thread into key points and required actions.
Inbox Zero Strategy
Create a personalised system to achieve and maintain inbox zero.
Best for GPT-3.5 Turbo
textDebate Topic & Preparation
Set up a classroom debate with positions, evidence prompts, and rules.
Marketing Tech Stack (MarTech) Recommendations
Design a marketing technology stack that supports executing and measuring persona-targeted campaigns centered on your USP and challenges.
Landing Page Long-Form Copy
Write complete long-form sales page copy from headline to CTA.