openai
OpenAI: GPT-5.3-Codex
openai/gpt-5.3-codex
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter’s catalog presents openai/gpt-5.3-codex as an OpenAI coding model intended for agentic software work, with text, image, and file inputs and text output. It lists a large context window, optional adjustable reasoning, tool calling, structured outputs, and response controls. The catalog also reports Design Arena results across coding and design categories. Because this evidence is catalog-only and no independent model card was supplied, its described capabilities and measured results should be validated against the intended workload.[1]
Strengths
Limitations
- Only OpenRouter catalog evidence was supplied; an independent model card was not available in this source pack.[1]
- Described coding ability and Design Arena results are not workload guarantees; validate on representative tasks.[1]
- License terms, knowledge cutoff, deployment requirements, and safety behavior are not specified.[1]
Where to use it
- Consider evaluating it for agentic coding assistants or software-maintenance agents that may use tools.[1]
- Potentially useful for code review or debugging grounded in source files, logs, images, or supplied documents.[1]
- Try a pilot where adjustable reasoning effort and machine-readable text outputs matter.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-5.3-CodexSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
GPT-5.3-Codex is OpenAI’s most advanced agentic coding model, combining the frontier software engineering performance of GPT-5.2-Codex with the broader reasoning and professional knowledge capabilities of GPT-5.2. It achieves state-of-the-art results...
Specifications
- Model ID
- openai/gpt-5.3-codex
- Canonical ID
- openai/gpt-5.3-codex-20260224
- Creator
- openai
- Added to OpenRouter
- 24.02.2026
- Context length
- 400,000
- Modality
- text+image+file->text
- Input modalities
- text, image, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $1.75 / out $14
- Knowledge cutoff
- —
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | reasoning: optional · default medium · efforts: xhigh, high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Coding | No measurement | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | reasoning: optional · default medium · efforts: xhigh, high, medium, low, none · parameters: include_reasoning, reasoning, reasoning_effort |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Design Arena | agents · androidnativewin rate 35.2% · rank 36 | 1,084Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · fullstackwin rate 36.5% · rank 44 | 961Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · godotgamedevwin rate 45.1% · rank 27 | 1,124Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · mobileappswin rate 41.4% · rank 49 | 1,048Elo | CC — below the B band | 13.11.2026 |
| Design Arena | agents · webappswin rate 36.9% · rank 45 | 1,014Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · 3dwin rate 35.3% · rank 119 | 991Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · asciiartwin rate 51.2% · rank 44 | 1,147Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 47.2% · rank 94 | 1,135Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · datavizwin rate 50.6% · rank 77 | 1,162Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · gamedevwin rate 51.3% · rank 76 | 1,152Elo | BB — next 30% of the cohort | 13.11.2026 |
| Design Arena | models · svgwin rate 54% · rank 62 | 1,121Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 47.3% · rank 91 | 1,128Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · websitewin rate 48.6% · rank 91 | 1,157Elo | CC — below the B band | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Azure | 400,000 | $1.75 | $14 | — | — | — |
| OpenAI | 400,000 | $1.75 | $14 | — | — | 100% |
| OpenAI | 400,000 | $3.5 | $28 | — | — | — |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.