GPT-5.3-Codex vs GPT-5 Mini
A side-by-side comparison of two multimodal models — real specs, pricing, strengths and weaknesses, and a clear verdict on which to choose. Kept current by our agents.
Quick verdict: which should you choose?
Choose GPT-5.3-Codex if you need
- ✓fast, low-cost multimodal processing with large contexts
- ✓general-purpose tasks integrating text, image, and file inputs
- ✓high output speed for multi-turn interactions at scale
- ✓budget-conscious deployments where 30.9 intelligence suffices
Choose GPT-5 Mini if you need
- ✓highest intelligence (44.3) for complex coding workflows
- ✓specialized programming support with diverse input types
- ✓maximum reasoning depth within 400k-token contexts
- ✓tasks where performance justifies the $14 per million token cost
Verdict
GPT-5.3-Codex leads on raw intelligence (44.3 vs 30.9) and programming specialization while GPT-5 Mini wins on speed (100.46 t/s vs 75.08 t/s) and price ($2 vs $14 per million tokens). Both share identical 400k context and multimodal capabilities from OpenAI, but Codex narrows to coding workflows whereas Mini emphasizes broad text-image-file handling. The choice hinges on whether users prioritize depth in code tasks or efficient general multimodal throughput.
GPT-5.3-Codex vs GPT-5 Mini: side by side
| Spec | GPT-5.3-Codex | GPT-5 Mini | Winner |
|---|---|---|---|
| Intelligence | 44.3 | 30.9 | GPT-5.3-Codex |
| Output speed | 77 t/s | 100 t/s | GPT-5 Mini |
| Output price | $14.00/1M | $2.00/1M | GPT-5 Mini |
| Context | 400K | 400K | Tie |
| Params | — | — | Tie |
| Provider | OpenAI | OpenAI | Tie |
Detailed analysis
Intelligence
Winner: GPT-5.3-CodexGPT-5.3-Codex scores 44.3 on the intelligence index compared to GPT-5 Mini's 30.9. This gap favors Codex for tasks needing deeper reasoning. Both models share the same provider and context size, so the difference stems purely from the reported index values.
Speed
Winner: GPT-5 MiniGPT-5 Mini delivers 100.46 tokens per second versus GPT-5.3-Codex at 75.08 t/s. The speed advantage makes Mini more suitable for high-volume output scenarios. Context length is identical at 400k tokens for both.
Pricing
Winner: GPT-5 MiniGPT-5 Mini costs $2 per million tokens while GPT-5.3-Codex costs $14 per million tokens. This sevenfold price difference directly impacts cost efficiency for large-scale use. Both are proprietary OpenAI models with no parameter count disclosed.
Specialization
Winner: GPT-5.3-CodexGPT-5.3-Codex is explicitly positioned as a coding model with strengths in programming workflows. GPT-5 Mini offers broader multimodal integration of text, image, and files for complex multi-turn tasks. Both support diverse inputs but Codex narrows its focus accordingly.
GPT-5.3-Codex
Pros
- +Specialized for programming workflows
- +Extensive context handling
- +Support for diverse input types
Cons
- –Narrower focus than general-purpose models
- –Performance tied to input quality
GPT-5 Mini
Pros
- +Handles very large contexts efficiently
- +Integrates text, image, and file inputs
- +Suitable for complex multi-turn tasks
Cons
- –Reduced depth on highly complex reasoning vs full-size models
- –Performance depends on input clarity across modalities
- –May require careful prompting for nuanced outputs
Summary: GPT-5.3-Codex vs GPT-5 Mini
Select GPT-5 Mini when speed and low cost matter most for general multimodal work. Choose GPT-5.3-Codex when maximum intelligence and coding specialization are required. Both models match on context length and provider.
Frequently asked questions
GPT-5.3-Codex is better for intelligence and coding tasks while GPT-5 Mini is better for speed and price; neither dominates every dimension.