OpenAI: GPT-5 Codex
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GPT-5 Codex is a version of GPT-5 optimized for agentic coding tasks in Codex or similar environments. It's designed for software engineering workflows with enhanced code generation capabilities.
Context Window 128K
tokens
Max Output 128K
tokens
Input Cost $1.25
per million tokens
Output Cost $10
per million tokens
Input text, image
modalities
Tool Use Yes
Knowledge Cutoff Sep 30, 2024
Release Date Aug 7, 2025
Code Example
Add AI to your app with the Puter.js AI API, no API keys or setup required.
// npm install @heyputer/puter.js
import { puter } from '@heyputer/puter.js';
puter.ai.chat("Explain quantum computing in simple terms").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").then(response => {
document.body.innerHTML = response.message.content;
});
</script>
</body>
</html>
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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.
ChatGPT-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.
ChatGPT-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
GPT-5 Codex is no longer available through Puter.js. Explore other AI models for alternatives.
| Price per 1M tokens | |
|---|---|
| Input | $1.25 |
| Output | $10 |
GPT-5 Codex was created by OpenAI and released on Aug 7, 2025.
GPT-5 Codex supports a context window of 128K tokens. For reference, that is roughly equivalent to 256 pages of text.
GPT-5 Codex can generate up to 128K tokens in a single response.
GPT-5 Codex has a knowledge cutoff date of Sep 30, 2024. This means the model was trained on data available up to that date.
GPT-5 Codex accepts the following input types: text, image. It produces: text.
Yes, GPT-5 Codex supports tool use (function calling), allowing it to interact with external tools, APIs, and data sources as part of its response flow.
GPT-5 Codex scores 24.9 on the Artificial Analysis Intelligence Index, outperforming 75% of tracked models. On math, it scores 98.7 (outperforms 99% of models).
Yes — the GPT-5 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.
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