OpenAI: GPT-4.1 Nano
openai/gpt-4.1-nano
Access GPT-4.1 Nano from OpenAI using Puter.js AI API.
Get Started// 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>
# pip install openai
from openai import OpenAI
client = OpenAI(
base_url="https://api.puter.com/puterai/openai/v1/",
api_key="YOUR_PUTER_AUTH_TOKEN",
)
response = client.chat.completions.create(
model="openai/gpt-4.1-nano",
messages=[
{"role": "user", "content": "Explain quantum computing in simple terms"}
],
)
print(response.choices[0].message.content)
curl https://api.puter.com/puterai/openai/v1/chat/completions \
-H "Content-Type: application/json" \
-H "Authorization: Bearer YOUR_PUTER_AUTH_TOKEN" \
-d '{
"model": "openai/gpt-4.1-nano",
"messages": [
{"role": "user", "content": "Explain quantum computing in simple terms"}
]
}'
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 $0.1
per million tokens
Output Cost $0.4
per million tokens
Input text, image
modalities
Tool Use Yes
Knowledge Cutoff Apr 2024
Release Date Apr 14, 2025
Output Speed 149
tokens / sec
Latency 0.47s
time to first token
Model Playground
Try GPT-4.1 Nano instantly in your browser.
This playground uses the Puter.js AI API — no API keys or setup required.
Benchmarks
How GPT-4.1 Nano performs on standard evaluations.
| Benchmark | Score |
|---|---|
| GPQA Diamond Graduate-level science Q&A | 51.2% |
| Humanity's Last Exam Cross-domain reasoning | 3.9% |
| LiveCodeBench Recent coding problems | 32.6% |
| SciCode Scientific programming | 25.9% |
| 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 | 17.0% |
| Terminal-Bench Hard Agentic terminal tasks | 3.8% |
| τ²-Bench Tool use / agents | 17.3% |
Scores sourced from Artificial Analysis.
Find other OpenAI models →
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GPT-5.6 Sol is OpenAI's flagship model in the GPT-5.6 family, sitting above Terra and Luna as the most capable and most expensive of the three. It reached general availability on July 9, 2026. Sol is built for agentic coding, cybersecurity research, and long-horizon autonomous work. OpenAI reports it sets a new state of the art on Terminal-Bench 2.1, a benchmark for command-line workflows that require planning, iteration, and tool coordination, and describes it as the most capable model yet for cybersecurity tasks such as vulnerability research. The GPT-5.6 family adds a max reasoning effort setting, an ultra mode that coordinates subagents on complex tasks, and Programmatic Tool Calling in the Responses API. Sol carries a 1.05M token context window, 128,000 max output tokens, and a February 16, 2026 knowledge cutoff, making it best suited for teams that need the highest available capability and can absorb its premium per-token cost.
ChatGPT-5.6 Sol Pro
GPT-5.6 Sol Pro is OpenAI's highest-capability configuration of GPT-5.6 Sol, the flagship tier in the GPT-5.6 family alongside the smaller Terra and Luna models. Sol is built for complex reasoning, coding, scientific work, and long-running agentic tasks. Sol Pro is not a separate, larger model. It runs the same underlying model as base Sol with reasoning mode set to pro for higher-quality responses on harder problems, which is why it shares identical pricing with the base model, $5 per million input tokens and $30 per million output tokens, unlike GPT-5.4 Pro and GPT-5.5 Pro, which cost several times more than their base models. It carries the same 1,050,000-token context window and 128,000 max output tokens as GPT-5.6 Sol, and supports image input, function calling, and the Responses API tool suite. It launched July 9, 2026, aimed at the hardest, longest-running tasks where response quality matters more than cost or latency.
ChatGPT-5.6 Terra
GPT-5.6 Terra is OpenAI's mid-tier chat model in the GPT-5.6 family, positioned between the flagship Sol and the faster, cheaper Luna. OpenAI's documentation describes it as designed for workloads that balance intelligence and cost, corresponding to the mini tier used in earlier GPT-5 families. In OpenAI's naming system, the number marks a model's generation, while Sol, Terra, and Luna mark capability tiers that can each advance on their own schedule. It has a 1,050,000 token context window, up to 128,000 output tokens, and a February 16, 2026 knowledge cutoff. Pricing is $2.50 per million input tokens and $15 per million output tokens, between Luna's $1/$6 and Sol's $5/$30. Terra accepts text and image input, supports function calling and tool use, and is aimed at high-volume business tasks such as customer support, internal tools, and document analysis, alongside everyday interactive and agentic coding where Sol's higher reasoning ceiling isn't needed.
Frequently Asked Questions
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.
Yes, it is free if you're using it through Puter.js. With the User-Pays Model, you can add GPT-4.1 Nano to your app at no cost — your users pay for their own AI usage directly, making it completely free for you as a developer.
| Price per 1M tokens | |
|---|---|
| Input | $0.1 |
| Output | $0.4 |
GPT-4.1 Nano was created by OpenAI and released on Apr 14, 2025.
GPT-4.1 Nano supports a context window of 1M tokens. For reference, that is roughly equivalent to 2,095 pages of text.
GPT-4.1 Nano can generate up to 33K tokens in a single response.
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.
GPT-4.1 Nano accepts the following input types: text, image. It produces: text.
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.
GPT-4.1 Nano scores 9.6 on the Artificial Analysis Intelligence Index, outperforming 35% of tracked models. On coding, it scores 11.1 (outperforms 13% of models). On math, it scores 24.0 (outperforms 25% of models).
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.
Get started with Puter.js
Add GPT-4.1 Nano to your app without worrying about API keys or setup.
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