OpenAI: GPT-5.3-Codex✓ Catalog verified
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 on SWE-Bench Pro and strong performance on Terminal-Bench 2.0 and OSWorld-Verified, reflecting improved multi-language coding, terminal proficiency, and real-world computer-use skills. The model is optimized for long-running, tool-using workflows and supports interactive steering during execution, making it suitable for complex development tasks, debugging, deployment, and iterative product work. Beyond coding, GPT-5.3-Codex performs strongly on structured knowledge-work benchmarks such as GDPval, supporting tasks like document drafting, spreadsheet analysis, slide creation, and operational research across domains. It is trained with enhanced cybersecurity awareness, including vulnerability identification capabilities, and deployed with additional safeguards for high-risk use cases. Compared to prior Codex models, it is more token-efficient and approximately 25% faster, targeting professional end-to-end workflows that span reasoning, execution, and computer interaction.
Overview
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 on SWE-Bench Pro and strong performance on Terminal-Bench 2.0 and OSWorld-Verified, reflecting improved multi-language coding, terminal proficiency, and real-world computer-use skills. The model is optimized for long-running, tool-using workflows and supports interactive steering during execution, making it suitable for complex development tasks, debugging, deployment, and iterative product work. Beyond coding, GPT-5.3-Codex performs strongly on structured knowledge-work benchmarks such as GDPval, supporting tasks like document drafting, spreadsheet analysis, slide creation, and operational research across domains. It is trained with enhanced cybersecurity awareness, including vulnerability identification capabilities, and deployed with additional safeguards for high-risk use cases. Compared to prior Codex models, it is more token-efficient and approximately 25% faster, targeting professional end-to-end workflows that span reasoning, execution, and computer interaction.
Access: available through the official OpenAI API. Context window: 400K.
Specifications
| API identifier | openai/gpt-5.3-codex |
| Provider | OpenAI |
| Model type | Multimodal LLM |
| Context window | 400K catalog |
| Input modalities | text · image · file |
| Output modalities | text |
| Released | Feb 24, 2026 |
| Tokenizer | GPT |
| Moderated | Yes |
| Architecture modality | text+image+file->text |
API defaults
{
"top_k": null,
"top_p": null,
"temperature": null,
"presence_penalty": null,
"frequency_penalty": null,
"repetition_penalty": null
}Pricing
Live pricing components for openai/gpt-5.3-codex as published in the catalog.
| Pricing component | Raw unit price | Normalized | Unit |
|---|---|---|---|
| Prompt tokens | $0.00000175 | $1.75 / 1M | Per input token |
| Completion tokens | $0.000014 | $14.00 / 1M | Per output token |
| Request fee | N/A | N/A | Per request |
| Image fee | N/A | N/A | Per image unit |
| Web search fee | $0.01 | $0.010000 | Per search request |
Cost calculator
Estimate monthly spend from your own token volumes.
Estimated Total Cost
$3.68Calculated from current list pricing in the ModelsAtlas catalog.Capabilities
| Capability | Status | What it means |
|---|---|---|
| Visual Understanding | ✓ Supported | Image and document analysis support |
| Audio Processing | Not advertised | Speech and voice aligned flows |
| Tool Calling | ✓ Supported | Supports tools / function calling |
| Self-Hosting | Not advertised | Deploy outside managed APIs |
Capability signals
Directional signals derived from model metadata and capability tags — not official benchmark submissions.
Quick start
Call OpenAI: GPT-5.3-Codex through an OpenAI-compatible client.
from openai import OpenAI
client = OpenAI(
base_url="https://openrouter.ai/api/v1",
api_key="YOUR_API_KEY"
)
response = client.chat.completions.create(
model="openai/gpt-5.3-codex",
messages=[{"role": "user", "content": "Explain quantum physics."}]
)
print(response.choices[0].message.content)Alternatives
Closest models by context window from a different provider.
| Model | Provider | Context | Input /1M | Actions |
|---|---|---|---|---|
| Meta: Llama 4 Scout | Meta | 328K | $0.08 | View → |
| Amazon: Nova Lite 1.0 | Amazon | 300K | $0.06 | View → |
Head-to-head comparisons
Side-by-side breakdowns of OpenAI: GPT-5.3-Codex against other frontier models.
Sources & attribution
Pricing and metadata are maintained in the ModelsAtlas catalog.
Frequently asked questions
How much does OpenAI: GPT-5.3-Codex cost?
$1.75 per 1M input tokens and $14.00 per 1M output tokens on the official OpenAI API.
What is the context window of OpenAI: GPT-5.3-Codex?
OpenAI: GPT-5.3-Codex supports up to 400K tokens of context.
Does OpenAI: GPT-5.3-Codex support tool / function calling?
Yes, OpenAI: GPT-5.3-Codex supports tool / function calling — you can register tools and the model will emit structured tool calls.
How do I access OpenAI: GPT-5.3-Codex?
Use the official OpenAI API with the model id `openai/gpt-5.3-codex`. See the Quick start section above for code examples.