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OpenAI

OpenAI: GPT-5.3 Codex

openai/gpt-5.3-codex

Try GPT-5.3 Codex for free in your browser, and add it to your app for free with Puter.js AI API.

Try it free Add to your app
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';

puter.ai.chat("Explain quantum computing in simple terms", {
    model: "openai/gpt-5.3-codex"
}).then(response => {
    document.body.innerHTML = response.message.content;
});
<html>
<body>
    <script src="https://js.puter.com/v2/"></script>
    <script>
        puter.ai.chat("Explain quantum computing in simple terms", {
            model: "openai/gpt-5.3-codex"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

Model Card

GPT-5.3 Codex is OpenAI's most capable agentic coding model, combining frontier coding performance with strong general reasoning and professional knowledge capabilities. It was the first model instrumental in creating itself, having been used to debug its own training and manage its own deployment. It sets state-of-the-art on SWE-Bench Pro and Terminal-Bench while being 25% faster than its predecessor.

Context Window 128K

tokens

Max Output 128K

tokens

Input Cost $1.75

per million tokens

Output Cost $14

per million tokens

Input text, image

modalities

Tool Use Yes

 

Knowledge Cutoff Aug 31, 2025

 

Release Date Feb 24, 2026

 

Output Speed 90

tokens / sec

Latency 47.59s

time to first token

Try GPT-5.3 Codex for free

Try GPT-5.3 Codex instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat openai/gpt-5.3-codex
OpenAI
Chat with GPT-5.3 Codex
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Benchmarks

How GPT-5.3 Codex performs on standard evaluations.

Artificial Analysis
Intelligence Index
32.5
Better than 84% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
91.5%
Humanity's Last Exam Cross-domain reasoning
42.5%
IFBench Instruction following
75.4%
LCR Long-context reasoning
83.3%
Terminal-Bench Hard Agentic terminal tasks
53.0%
τ²-Bench Tool use / agents
86.0%

Scores sourced from Artificial Analysis.

Find other OpenAI models →

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GPT-6.1 Sol

GPT-6.1 Sol is OpenAI's mid-tier model in the GPT-6 family, released September 29, 2026 as an update to GPT-6 Sol. It sits below the flagship GPT-6 Astra, takes text and image input, supports tool calling, and has a 1,050,000-token context window with 128,000 max output tokens. Pricing is unchanged from GPT-6 Sol at $2 per million input tokens and $10 per million output tokens, while scores are higher. It reaches 75.2% on DeepSWE 1.1 (68.8% for GPT-6 Sol), 71.4% on OSWorld 2.0 (64.4%), and 32.0% on GDP.pdf (28.0%). Its factual error rate at low reasoning effort fell from 11.4% to 7.7%. In one third-party comparison table, GPT-6 Astra scores 74.8% on DeepSWE and 73.5% on OSWorld at roughly five times the price. GPT-6.1 Sol suits coding agents, computer use, document question answering, and workflow automation where cost per task matters.

Chat

GPT-6.1 Sol Pro

GPT-6.1 Sol Pro is OpenAI's higher-effort configuration of GPT-6.1 Sol, the mid-tier model in the GPT-6 family. Based on how OpenAI handled GPT-6 Sol Pro, it is likely the same underlying model with reasoning mode set to pro, though OpenAI's documentation for the 6.1 release does not confirm this. It has a 1,050,000-token context window and 128,000 max output tokens, at $2 per million input tokens and $10 per million output tokens. Supported parameters include reasoning effort, tools, tool choice, structured response formats, seed, and streaming. Sol Pro is intended for complex requests such as agentic coding, computer use, and workflow automation, where answer quality matters more than latency. We found no published benchmarks for the Pro configuration itself.

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GPT-6 Sol

GPT-6 Sol is OpenAI's mid-tier model in the GPT-6 family, released September 22, 2026 as a faster, cheaper counterpart to the flagship GPT-6 Astra, built on the same training methods. OpenAI positions it for complex development work that developers run repeatedly, such as building features, reviewing code, debugging, and analyzing data. OpenAI reports Sol scoring 68.8% on the DeepSWE 1.1 coding benchmark, 60.5% on OSWorld 2.0 for computer use at xhigh effort, and 56.4% on Agents' Last Exam, a test of professional work across 55 sub-industries. The company says Sol makes about half as many factual errors as GPT-5.6 Sol, approaching Astra-level reliability at a lower cost. At $2 per million input tokens and $10 per million output tokens, half of GPT-5.6 Sol's rate, Sol matches Claude Sonnet 5's standard pricing, though no published benchmark compares the two models directly.

Frequently Asked Questions

How do I use GPT-5.3 Codex?

You can access GPT-5.3 Codex by OpenAI through Puter.js AI API. Include the library in your web app or Node.js project and start making calls with just a few lines of JavaScript — no backend and no configuration required. You can also use it with Python or cURL via Puter's OpenAI-compatible API.

Can I try GPT-5.3 Codex for free?

GPT-5.3 Codex is free to try with a Puter account. Every account includes a free AI allowance, and you can chat with it in the playground on this page. You can upgrade your account anytime for a larger allowance.

Is the GPT-5.3 Codex API free for developers?

GPT-5.3 Codex is free to integrate using the Puter.js AI API. With the User-Pays Model, you can add AI to your app for $0, since users cover their own AI usage through their Puter account.

What is the pricing for GPT-5.3 Codex?
GPT-5.3 Codex costs $1.75 per 1M input tokens and $14 per 1M output tokens.
Price per 1M tokens
Input$1.75
Output$14
Who created GPT-5.3 Codex?

GPT-5.3 Codex was created by OpenAI and released on Feb 24, 2026.

What is the context window of GPT-5.3 Codex?

GPT-5.3 Codex supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.

What is the max output length of GPT-5.3 Codex?

GPT-5.3 Codex can generate up to 128K tokens in a single response.

What is the knowledge cutoff of GPT-5.3 Codex?

GPT-5.3 Codex has a knowledge cutoff date of Aug 31, 2025. This means the model was trained on data available up to that date.

What types of input can GPT-5.3 Codex process?

GPT-5.3 Codex accepts the following input types: text, image. It produces: text.

Does GPT-5.3 Codex support tool use (function calling)?

Yes, GPT-5.3 Codex supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.

How does GPT-5.3 Codex perform on benchmarks?

GPT-5.3 Codex scores 32.5 on the Artificial Analysis Intelligence Index, outperforming 84% of tracked models.

Does it work with React / Vue / Vanilla JS / Node / etc.?

Yes — the GPT-5.3 Codex API works with any JavaScript framework, Node.js, or plain HTML through Puter.js. Just include the library and start building. See the documentation for more details.

Add GPT-5.3 Codex to your app for free

Developers can integrate GPT-5.3 Codex for free using the Puter.js AI API.
With the User-Pays Model, each user covers their own AI usage instead of the developer.

Get started How pricing works