GPT-5.1-Codex vs GPT-5 Nano
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-5.1-Codex if you need
- ✓Choose GPT-5 Nano if you need very low-cost inference at $0.4 per million tokens for high-volume use.
- ✓Choose GPT-5 Nano if you need support for text, image, and file inputs together.
- ✓Choose GPT-5 Nano if you need lightweight handling of long documents without high capability depth.
- ✓Choose GPT-5 Nano if you need faster responses on extended but non-complex tasks.
Choose GPT-5 Nano if you need
- ✓Choose GPT-5.1-Codex if you need higher intelligence (43.1 index) for complex reasoning.
- ✓Choose GPT-5.1-Codex if you need specialized performance on extended coding workflows with visual context.
- ✓Choose GPT-5.1-Codex if you need strong coherence on very large text and image inputs.
- ✓Choose GPT-5.1-Codex if you need maximum capability despite the $10 per million token price.
Verdict
GPT-5.1-Codex leads decisively on intelligence (43.1 vs 26.8) and coding specialization while matching context length and slightly edging speed, but GPT-5 Nano dominates on price ($0.4 vs $10 per million tokens) and broader file-input support. The Nano model trades depth for affordability and efficiency on extended documents, whereas Codex prioritizes advanced multimodal coding workflows at much higher cost. Neither wins outright; selection hinges on whether raw capability or cost-effective scale matters most.
GPT-5.1-Codex vs GPT-5 Nano: side by side
| Spec | GPT-5.1-Codex | GPT-5 Nano | Winner |
|---|---|---|---|
| Intelligence | 43.1 | 26.8 | GPT-5.1-Codex |
| Output speed | 178 t/s | 170 t/s | GPT-5.1-Codex |
| Output price | $10.00/1M | $0.40/1M | GPT-5 Nano |
| Context | 400K | 400K | Tie |
| Params | — | — | Tie |
| Type | Proprietary | Proprietary | Tie |
| Provider | OpenAI | OpenAI | Tie |
Detailed analysis
Intelligence
Winner: GPT-5.1-CodexGPT-5.1-Codex scores 43.1 on the intelligence index compared with 26.8 for GPT-5 Nano. This gap indicates stronger performance on complex tasks. Both share the same 400k context window.
Pricing
Winner: GPT-5 NanoGPT-5 Nano costs $0.4 per million output tokens while GPT-5.1-Codex costs $10 per million. The 25x price difference favors Nano for budget-sensitive or high-volume workloads. Both are proprietary OpenAI models.
Speed & Context
Winner: TieOutput speeds are close at 170.06 t/s for Nano versus 178.06 t/s for Codex. Both support identical 400k context lengths. Nano emphasizes lightweight efficiency while Codex notes higher cost at maximum context.
Input Capabilities
Winner: GPT-5 NanoGPT-5 Nano supports text, image, and file inputs; GPT-5.1-Codex is limited to text and image only. This gives Nano an edge for document-heavy multimodal tasks. Both handle large contexts without coherence loss per their listed strengths.
GPT-5.1-Codex
Pros
- +Strong performance on extended coding workflows
- +Effective integration of visual context with code
- +Handles very large inputs without losing coherence
- +Specialized for software development tasks
Cons
- –Limited to text and image inputs only
- –High computational cost for maximum context
- –May require careful prompt engineering for complex tasks
GPT-5 Nano
Pros
- +Handles very large contexts efficiently
- +Supports text, image, and file inputs
- +Lightweight design for faster responses
- +Practical for extended document tasks
Cons
- –Lower capability depth than full-scale models
- –May struggle with highly complex reasoning
- –Trade-off in advanced task performance
Summary: GPT-5.1-Codex vs GPT-5 Nano
Select GPT-5 Nano when cost, file support, and lightweight long-context use are priorities. Choose GPT-5.1-Codex when higher intelligence and coding-focused multimodal performance justify the premium price. The models serve distinct segments within the same provider ecosystem.
Frequently asked questions
GPT-5.1-Codex is stronger on intelligence and coding tasks while GPT-5 Nano wins on price and input flexibility; neither is universally better.