OpenAI: GPT-4.1 Nano
Analysis Summary
GPT-4.1 Nano is OpenAI's smallest model in this group, with a 1,047,576-token context window and support for text, image, and file inputs. Function calling and tool use make it practical for lightweight structured automation, while the measured reasoning, coding, long-context, and agentic results indicate a narrow operating envelope.
It suits high-volume SEO metadata generation, document classification, routing, tagging, simple extraction, and short-form content transformations. The large context window can support long reference inputs, but it does not compensate for weaker reasoning when tasks require synthesis, judgement, or dependable multi-step execution. Human review or escalation to a stronger model remains appropriate for client-facing strategy and complex analysis.
Pricing of $0.10 per million input tokens and $0.40 per million output tokens is its defining advantage. Use it as a volume and preprocessing model, not as the primary engine for demanding content or agent workflows.
Assessed August 9, 2026
Editorial notes
GPT-4.1 Nano offers a million-token context, vision, file input, and function calling at very low pricing, supporting high-volume classification and extraction; its reasoning, coding, and agentic reliability are limited.
Rankings consider pricing, capabilities, benchmarks, and real-world applicability and are refreshed as new models launch. Feedback?
DFO Verdict
GPT-4.1 Nano offers a million-token context, vision, file input, and function calling at very low pricing, supporting high-volume classification and extraction; its reasoning, coding, and agentic reliability are limited.
Benchmark scores
Magenta = intelligence · Ink = technical/agentic · Cyan = content & long-context · Grey = community benchmarks. Data: Artificial Analysis, Hugging Face.
9.6 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 #276 of 424 AI models we track for overall intelligence, #168 of 197 for coding, #166 of 179 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 70% 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 701 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 #168 of 197 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.
