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OpenAI gpt-4.1-nano

GPT-4.1 nano (OpenAI)

Deprecated Shuts down in 85 days

Yes — OpenAI deprecated GPT-4.1 nano on April 22, 2026 and shuts it down on October 23, 2026 (in 85 days). The recommended replacement is GPT-5.6 Luna.

The cheapest model of the GPT-4.1 generation, and the only member of that family to be deprecated so far — gpt-4.1 and gpt-4.1-mini remain active. It was a common choice for classification and routing at high volume.

The facts

Provider OpenAI
Model id gpt-4.1-nano
Also published as gpt-4.1-nano-2025-04-14
Released April 14, 2025
Deprecated April 22, 2026
Shutdown October 23, 2026 · in 85 days
Status Deprecated
Last verified July 30, 2026

What to use instead

OpenAI GPT-5.6 Luna gpt-5.6-luna Provider-recommended Active

Fine-tuned gpt-4.1-nano deployments are directed to gpt-5.4-nano instead; a fine-tune does not transfer and has to be re-run on the new base.

What parameters gpt-5.6-luna accepts on modelparams.dev

Change the id

In most cases the migration is one string. Check the parameter differences before you ship — newer models drop older sampling knobs more often than they add them. 

- "model": "gpt-4.1-nano"
+ "model": "gpt-5.6-luna"

Frequently asked questions

When will OpenAI GPT-4.1 nano shut down?
OpenAI GPT-4.1 nano is scheduled to shut down on October 23, 2026, in 85 days.
What replaces OpenAI GPT-4.1 nano?
OpenAI recommends GPT-5.6 Luna (`gpt-5.6-luna`) as the replacement for OpenAI GPT-4.1 nano. Fine-tuned gpt-4.1-nano deployments are directed to gpt-5.4-nano instead; a fine-tune does not transfer and has to be re-run on the new base.
Is OpenAI GPT-4.1 nano still available?
Yes, for now. OpenAI GPT-4.1 nano is deprecated but still answers requests until October 23, 2026. Deprecated models get no further updates and are the first to lose capacity.
How do I migrate from OpenAI GPT-4.1 nano to gpt-5.6-luna?
Swap the model id in your API call: replace "gpt-4.1-nano" with "gpt-5.6-luna". Fine-tuned gpt-4.1-nano deployments are directed to gpt-5.4-nano instead; a fine-tune does not transfer and has to be re-run on the new base.
Does this apply to gpt-4.1-nano-2025-04-14 too?
Yes. OpenAI GPT-4.1 nano is also published as `gpt-4.1-nano-2025-04-14`; that id shares the same lifecycle dates as `gpt-4.1-nano`.

Sources

Found something wrong? The data is one YAML file — edit it on GitHub.

This page, for machines

JSON Markdown Badge JSON

Drop the badge in a README so it turns red the day this model is retired:

[![gpt-4.1-nano](https://img.shields.io/endpoint?url=https://modeldeprecations.dev/badge/openai/gpt-4.1-nano.json)](https://modeldeprecations.dev/openai/gpt-4.1-nano)

Other OpenAI models

All OpenAI deprecations →

How to use this site

The full guide, in Markdown. Copy it and hand it to a coding agent verbatim.

# How to use modeldeprecations.dev

[modeldeprecations.dev](https://modeldeprecations.dev) answers one question per model: is it deprecated,
when does it shut down, and what replaces it. Every date on the site is cited to the
provider's own documentation, with the date we last checked it.

Three lifecycle states are used, matching the providers' own vocabulary:

- **active** — still supported, no deprecation announced.
- **deprecated** — the provider has announced it is going away. It still answers requests.
- **retired** — API access is gone. Requests fail.

A model can be active *and* carry a shutdown date: Anthropic publishes a
"not sooner than" date and Google publishes an earliest shutdown date for models
that are current and fully supported. Those are reported as scheduled shutdowns,
not deprecations, because that is what the provider actually committed to.

## Check one model

```bash
curl https://modeldeprecations.dev/api/v1/models/openai/gpt-4-32k.json
```

Or fetch the page as Markdown, which includes the answer, the dates and the sources:

```bash
curl https://modeldeprecations.dev/openai/gpt-4-32k.md
```

## Full catalog

```bash
curl https://modeldeprecations.dev/api/v1/models.json
```

Ids are `provider/model`. Dated snapshots (`gpt-4-32k-0613`) are listed as aliases of
their canonical entry rather than as separate records.

Each entry carries `computed_status`, the lifecycle state recomputed against the build
date — so a model whose shutdown has passed reads `retired` without anyone editing data.

## Badges

A shields.io endpoint per model, for READMEs that should go red when a model dies:

```
https://img.shields.io/endpoint?url=https://modeldeprecations.dev/badge/openai/gpt-4-32k.json
```

## Calendar and changelog

- Subscribe to every shutdown date: https://modeldeprecations.dev/calendar.ics
- Changelog RSS: https://modeldeprecations.dev/changelog.xml

## JSON Schema

```bash
curl https://modeldeprecations.dev/api/v1/schema.json
```

## Contribute

Data lives in YAML under `models/{provider}/{model}.yaml` in the
[GitHub repo](https://github.com/mnfst/modeldeprecations.dev). Every lifecycle date needs a source URL; CI rejects a
date without one. Open a PR.

## For agents

- Machine-readable overview: https://modeldeprecations.dev/llms.txt
- This guide plus every model inline: https://modeldeprecations.dev/llms-full.txt
- Any page also exists as Markdown: append `.md` to a model URL.
- In a browser, this site registers a **WebMCP** tool on `navigator.modelContext`:
  `check_model_deprecation`, `list_shutdowns`, `find_replacement`, and `get_usage_guide`.
- Parameters each model accepts are catalogued on the sibling site, https://modelparams.dev.