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OpenAI

OpenAI: GPT-4.1 Nano

openai/gpt-4.1-nano

Try GPT-4.1 Nano 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-4.1-nano"
}).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-4.1-nano"
        }).then(response => {
            document.body.innerHTML = response.message.content;
        });
    </script>
</body>
</html>

Model Card

GPT-4.1 Nano is OpenAI's fastest and cheapest model, designed for low-latency tasks like classification and autocompletion. It features a 1M token context window and scores 80.1% on MMLU despite its small size.

Context Window 1M

tokens

Max Output 33K

tokens

Input Cost $0.08

per million tokens

Output Cost $0.3

per million tokens

Input text, image

modalities

Tool Use Yes

 

Knowledge Cutoff Apr 2024

 

Release Date Apr 14, 2025

 

Try GPT-4.1 Nano for free

Try GPT-4.1 Nano instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.

Chat openai/gpt-4.1-nano
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Chat with GPT-4.1 Nano
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Benchmarks

How GPT-4.1 Nano performs on standard evaluations.

Artificial Analysis
Intelligence Index
7.8
Better than 29% of tracked models
Artificial Analysis
Coding Index
11.1
Better than 10% of tracked models
Artificial Analysis
Math Index
24.0
Better than 25% of tracked models
BenchmarkScore
GPQA Diamond Graduate-level science Q&A
51.2%
Humanity's Last Exam Cross-domain reasoning
3.8%
LiveCodeBench Recent coding problems
32.6%
MATH-500 Competition math
84.8%
AIME 2024 Advanced math exam
23.7%
AIME 2025 Advanced math exam
24.0%
IFBench Instruction following
32.0%
LCR Long-context reasoning
20.3%
Terminal-Bench Hard Agentic terminal tasks
3.8%
τ²-Bench Tool use / agents
17.3%

Scores sourced from Artificial Analysis.

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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.

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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-4.1 Nano?

You can access GPT-4.1 Nano 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-4.1 Nano for free?

GPT-4.1 Nano 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-4.1 Nano API free for developers?

GPT-4.1 Nano 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-4.1 Nano?
GPT-4.1 Nano costs $0.08 per 1M input tokens and $0.3 per 1M output tokens.
Price per 1M tokens
Input$0.08
Output$0.3
Who created GPT-4.1 Nano?

GPT-4.1 Nano was created by OpenAI and released on Apr 14, 2025.

What is the context window of GPT-4.1 Nano?

GPT-4.1 Nano supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,100 pages of text.

What is the max output length of GPT-4.1 Nano?

GPT-4.1 Nano can generate up to 33K tokens in a single response.

What is the knowledge cutoff of GPT-4.1 Nano?

GPT-4.1 Nano has a knowledge cutoff date of Apr 2024. This means the model was trained on data available up to that date.

What types of input can GPT-4.1 Nano process?

GPT-4.1 Nano accepts the following input types: text, image. It produces: text.

Does GPT-4.1 Nano support tool use (function calling)?

Yes, GPT-4.1 Nano 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-4.1 Nano perform on benchmarks?

GPT-4.1 Nano scores 7.8 on the Artificial Analysis Intelligence Index, outperforming 29% of tracked models. On coding, it scores 11.1 (outperforms 10% of models). On math, it scores 24.0 (outperforms 25% of models).

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

Yes — the GPT-4.1 Nano 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-4.1 Nano to your app for free

Developers can integrate GPT-4.1 Nano 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