openai
OpenAI: GPT-4.1 Nano
openai/gpt-4.1-nano
Our take
AI-assisted analysis based on the sources below. Suitability is an editorial assessment; test it on your own workload.
OpenRouter's catalog lists openai/gpt-4.1-nano as a compact OpenAI model in the GPT-4.1 series, which the catalog describes as the fastest and cheapest member of that family, aimed at low-latency tasks. The catalog reports a context window of about one million tokens, text output, and text, image, and file inputs, along with tool calling and structured output options. Its knowledge cutoff is June 2024. Only catalog data was supplied and no independent model card was available in this source pack, so capabilities are source-reported and should be validated on real workloads.[1]
Strengths
- Context window of about one million tokens per the OpenRouter catalog, suitable for long documents or many-shot prompts.[1]
- Accepts text, image, and file inputs while producing text output, enabling multimodal pipelines.[1]
- Catalog lists tool calling, tool choice, seed, and structured output parameters, suggesting integration-ready controls.[1]
Limitations
- Only an OpenRouter catalog entry was supplied; no independent model card was available in this source pack, so all capabilities are source-reported.[1]
- The catalog does not record a reasoning mode for this variant; that field is unknown rather than confirmed absent.[1]
- No independent evaluation was provided; validate latency and output quality on your own workloads before adopting.[1]
Where to use it
- High-volume, latency-sensitive text tasks such as classification or summarization, matching the provider positioning reported by the catalog; confirm with testing.[1]
- Multimodal applications that combine text with image or file inputs in a single request.[1]
- Integrations requiring tool calling or structured outputs at small-model scale; validate accuracy on your data first.[1]
Sources
- [1] OpenRouter catalog · OpenAI: GPT-4.1 NanoSources checked: Nov 13, 2026
About this model
Description below is the original text supplied by OpenRouter, shown in the source language.
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...
Specifications
- Model ID
- openai/gpt-4.1-nano
- Canonical ID
- openai/gpt-4.1-nano-2025-04-14
- Creator
- openai
- Added to OpenRouter
- 14.04.2025
- Context length
- 1,047,576
- Modality
- text+image+file->text
- Input modalities
- image, text, file
- Output modalities
- text
- Token pricing
- USD per 1M tokens: in $0.100 / out $0.400
- Knowledge cutoff
- 30.06.2024
- Expiration date
- —
Tasks and capabilities
A grade appears only where the source supplies a matching measurement for that task, the model is active and the cohort holds at least 10 comparable models. The capability column lists facts the source declares — supported formats, reasoning and tool parameters — which are not measured quality.
| Task | Grade | Source-declared capability |
|---|---|---|
| General quality | No measurement | — |
| Coding | CC — below the B band | — |
| Agents | No measurement | parameters: structured_outputs, tool_choice, tools |
| Writing | No measurement | output: text |
| Reasoning | No measurement | — |
| Document analysis | No measurement | input: file |
| Vision | No measurement | input: image |
| Image generation | No measurement | — |
| Audio | No measurement | — |
| Video | No measurement | — |
| Embeddings | No measurement | — |
Evaluations
| Source | Benchmark | Value | Grade | Data retrieved |
|---|---|---|---|---|
| Artificial Analysis | Coding index | 11.1 | CC — below the B band | 13.11.2026 |
| Design Arena | models · 3dwin rate 46% · rank 128 | 908Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · codecategorieswin rate 47.3% · rank 137 | 953Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · datavizwin rate 41.1% · rank 132 | 889Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · gamedevwin rate 49.6% · rank 131 | 961Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · uicomponentwin rate 43.9% · rank 134 | 907Elo | CC — below the B band | 13.11.2026 |
| Design Arena | models · websitewin rate 48.1% · rank 139 | 966Elo | CC — below the B band | 13.11.2026 |
How grades work
Each letter grade compares a model only against other models scored by the same source and metric in the current snapshot. S means the top 10%, A the next 20%, B the next 30%, C the rest. Models without a published measurement are shown as not rated — a supported format alone never implies measured quality.
- S — S — top 10% of the cohort
- A — A — next 20% of the cohort
- B — B — next 30% of the cohort
- C — C — below the B band
Providers
Optional live provider statistics from OpenRouter. Missing values are unknown, not zero.
| Provider | Context length | Price in /1M | Price out /1M | Latency p50 (30m, s) | Throughput p50 (30m, tok/s) | Uptime (30m) |
|---|---|---|---|---|---|---|
| Azure | 1,047,576 | $0.100 | $0.400 | — | — | 100% |
| Azure | 1,047,576 | $0.110 | $0.440 | — | — | 100% |
Provider data retrieved: 13.11.2026
Related articles
No published articles identify this model yet.