OpenAI: GPT-4.1 Nano
Analysis Summary
GPT-4.1 Nano is a low-cost multimodal model aimed at fast, repetitive API tasks. Its 1M token context, image and file support, and tool and function calling create a useful deployment surface for classification, extraction, routing, and lightweight structured generation. The price is particularly attractive for high-volume workloads.
Its measured intelligence, coding, and long-context reasoning are limited relative to larger models, so it should not own complex strategy, editorial judgement, or autonomous software work. It fits metadata generation, content tagging, lead processing, simple support responses, and workflow pre-processing. Use Nano as an economical first-pass model, with human review or escalation to a stronger system for nuanced client-facing outputs.
Assessed September 7, 2026
Editorial notes
GPT-4.1 Nano combines low pricing, a 1M token context, vision, files, and tool calling for high-volume automation. Its limited reasoning and coding depth make it unsuitable for complex content or autonomous agent work.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
GPT-4.1 Nano combines low pricing, a 1M token context, vision, files, and tool calling for high-volume automation. Its limited reasoning and coding depth make it unsuitable for complex content or autonomous agent work.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
7.8 Intelligence Index·11.1 Coding Index·1.2 Agentic Index·24 Math Index
How OpenAI: GPT-4.1 Nano compares
OpenAI: GPT-4.1 Nano ranks #289 of 438 AI models we track for overall intelligence, #180 of 210 for coding, #168 of 192 for agentic tasks. Its 1M-token context window is larger than 84% of the models we list. At $0.10 per million input tokens it is cheaper than 69% 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.
Strongest on value. The pulled-in technical corner is the trade-off, and if the shape matters more than the price, this is your model.
Compare shapes side-by-side →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?
Pick the job that looks most like yours, then fine-tune with the sliders. Estimates update live.
A website chatbot handling around 100 customer conversations a day, a few short messages each.
Full calculator with 779 models → Price Calculator
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 #180 of 210 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.