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Providers

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Providers

Alibaba 26 Amazon Bedrock 8 Anthropic 31 Cohere 35 DeepSeek 5 Google 34 MiniMax 17 Mistral 53 Moonshot AI 18 OpenAI 106 Vertex AI 8 xAI 26 Xiaomi MiMo 4 Z.ai 22
Vertex AI gemini-2.5-pro

Gemini 2.5 Pro (Vertex AI) (Vertex AI)

Deprecated Shutdown

Yes — Vertex AI deprecated Gemini 2.5 Pro (Vertex AI) and shuts it down on October 20, 2026 (in 39 days). The recommended replacement is Gemini 3.5 Flash (Vertex AI).

The Vertex AI (Gemini Enterprise Agent Platform) flavour of Gemini 2.5 Pro, with thinking enabled by default and a million-token context window. Google has committed to retiring it on the platform on October 20, 2026 — a firmer date than the Gemini API's "not before" window, so it counts as deprecated here even though the model is still active and widely used.

The facts

Provider Vertex AI
Model id gemini-2.5-pro
Released June 17, 2025
Deprecated date not published
Shutdown October 20, 2026 ·
Status Deprecated
Last verified August 21, 2026

What to use instead

Vertex AI Gemini 3.5 Flash (Vertex AI) gemini-3.5-flash Provider-recommended Shutdown scheduled

What parameters gemini-3.5-flash 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": "gemini-2.5-pro"
+ "model": "gemini-3.5-flash"

Frequently asked questions

When will Vertex AI Gemini 2.5 Pro (Vertex AI) shut down?
Vertex AI Gemini 2.5 Pro (Vertex AI) is scheduled to shut down on October 20, 2026, in 39 days.
What replaces Vertex AI Gemini 2.5 Pro (Vertex AI)?
Vertex AI recommends Gemini 3.5 Flash (Vertex AI) (`gemini-3.5-flash`) as the replacement for Vertex AI Gemini 2.5 Pro (Vertex AI).
Is Vertex AI Gemini 2.5 Pro (Vertex AI) still available?
Yes, for now. Vertex AI Gemini 2.5 Pro (Vertex AI) is deprecated but still answers requests until October 20, 2026. Deprecated models get no further updates and are the first to lose capacity.
How do I migrate from Vertex AI Gemini 2.5 Pro (Vertex AI) to gemini-3.5-flash?
Swap the model id in your API call: replace "gemini-2.5-pro" with "gemini-3.5-flash". Keep the rest of the request the same, then re-check the parameters the new model accepts before you ship.

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:

[![gemini-2.5-pro](https://img.shields.io/endpoint?url=https://modeldeprecations.dev/badge/vertex/gemini-2.5-pro.json)](https://modeldeprecations.dev/vertex/gemini-2.5-pro)

Other Vertex AI models

All Vertex AI 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.