OpenAI: GPT-4.1 Nano
Analysis Summary
OpenAI's GPT-4.1 Nano supports text, image, and file inputs, tool use, and function calling, with a context window of roughly one million tokens. Its supplied benchmark results indicate limited reasoning and coding capability relative to more capable models, but its listed pricing is low at $0.10 input and $0.40 output per million tokens.
That makes Nano a candidate for high-volume, bounded tasks such as basic extraction, classification, and simple structured tool calls, provided outputs are checked. Vision and file support broaden its use, while the low long-context score cautions against relying on it for deep analysis of large documents simply because the context limit is high. It is not the right default for complex coding or autonomous agents.
Use it where cost and throughput are priorities and task quality can be measured. Route ambiguous, high-stakes, or complex work to a stronger model.
Assessed September 23, 2026
Editorial notes
GPT-4.1 Nano offers vision, file inputs, tool and function calling, a 1M-token context, and very low listed rates; its measured reasoning and coding capability is limited.
The DFO score ranks models on the Artificial Analysis Intelligence Index and is refreshed as new models launch. The write-up and verdict are our own. Feedback?
DFO Verdict
GPT-4.1 Nano offers vision, file inputs, tool and function calling, a 1M-token context, and very low listed rates; its measured reasoning and coding capability is limited.
Benchmarks
Artificial Analysis data refreshed Oct 12, 2026. Arena ratings from the Oct 2, 2026 text leaderboard, with style control. Bars: magenta = reasoning, ink = coding and agents, cyan = instructions and long context.
How OpenAI: GPT-4.1 Nano compares
OpenAI: GPT-4.1 Nano ranks #279 of 436 AI models we track for overall intelligence, #165 of 198 for coding, #149 of 181 for agentic tasks. Its 1M-token context window is larger than 87% of the models we list. At $0.10 per million input tokens it is cheaper than 65% of comparable models.
Dark bar = input · light bar = output, scaled to the priciest peer.
1M tokens ≈ 8 full-length novels or ~2,500 pages of business documents in a single request.
Pricing
| Token Type | Cost per 1M tokens | Cost per 1K tokens |
|---|---|---|
| Input | $0.10 | $0.000100 |
| Output | $0.40 | $0.000400 |
What would OpenAI: GPT-4.1 Nano cost your business?
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A website chatbot handling around 100 customer conversations a day, a few short messages each.
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These numbers get smaller with the right architecture.
We route routine calls to cheap models and save OpenAI: GPT-4.1 Nano for the hard ones. Most clients cut their estimate by 60-80%.
Talk to our teamAbout OpenAI: GPT-4.1 Nano
For tasks that demand low latency, GPT‑4.1 nano is the fastest and cheapest model in the GPT-4.1 series. It delivers exceptional performance at a small size with its 1 million..
Frequently asked questions about OpenAI: GPT-4.1 Nano
How much does OpenAI: GPT-4.1 Nano cost?
OpenAI: GPT-4.1 Nano costs $0.10 per million input tokens and $0.40 per million output tokens.
What is the context window of OpenAI: GPT-4.1 Nano?
OpenAI: GPT-4.1 Nano has a context window of 1,047,576 tokens (1M).
Is OpenAI: GPT-4.1 Nano good for coding?
On our coding benchmark index, OpenAI: GPT-4.1 Nano ranks #165 of 198 models, placing it in the broader range of the field for code generation and debugging.
What can OpenAI: GPT-4.1 Nano do?
OpenAI: GPT-4.1 Nano supports image/vision input, tool use, and function calling.
Who created OpenAI: GPT-4.1 Nano?
OpenAI: GPT-4.1 Nano is developed by OpenAI and was released on April 14, 2025.