Change log, by what changed

Weight and alias changes

These are the changes that reach you without a deploy on your side, because the string your code sends now resolves to something else. Rerun your suite.

What a model id returns has changed while the id stayed the same. This is the category that makes pinning a dated id worth the trouble.

2 entries . window ends 2026-09-24

By provider

OpenAI: 1
Google: 1

Recommended action

Re-pin the version 2

Other views

Weight and alias changes over twelve months

Tracked provider changes, Oct 2025 to Sep 2026

New version
Weight refresh
Deprecation
Pricing, context and tool changes share these three colours and always carry a label.

The same timeline as a list, 2 changes

2026-06-24 OpenAI, Weight refresh: chat-latest
2026-01-21 Google, Weight refresh: gemini-3-pro-preview, gemini-3-flash-preview

Every entry

Weight and alias changes, newest first

OpenAIWeight refresh24 June 2026

chat-latest

OpenAI updated the chat-latest snapshot to point to the latest Instant model in ChatGPT.

Chat assistant: An alias that is repointed changes the model behind the assistant with no deploy on your side. Google documents the same mechanism for Gemini, where a latest alias points at the most recent release of a model variation and is hot swapped with every new release.
Generation: Future AGI recommends refreshing a golden dataset immediately after a model update, monthly by default and weekly during rapid change, sampling 200-500 recent production traces stratified by intent and persona.

Re-pin the versionReplace any chat-latest alias in production with a dated snapshot id, so a future repoint does not change behaviour without a deploy.

Source: OpenAI, OpenAI API changelog . verified 2026-09-22

GoogleWeight refresh21 January 2026

gemini-3-pro-preview, gemini-3-flash-preview

Google changed the latest aliases to point to Gemini 3 models.

Chat assistant: Google says a latest alias points at the most recent release of a model variation and is hot swapped with every new release of that variation, so an assistant served through the alias changes with no action on your side.
RAG: An answer path that reads retrieved documents is easier to reason about when the model id is explicit. Google's documentation says most production apps should use a specific stable model, and hedges that stable models usually do not change.
Generation: Future AGI writes that OpenAI, Anthropic, Google and most frontier providers update model weights without a major version bump. That is one vendor's characterisation of the market, and Google's documented alias behaviour is the provider's own side of it.

Re-pin the versionReplace any latest alias in your configuration with an explicit model id, and rerun the suites that were served through the alias to see what moved.

Source: Google, Gemini API changelog . verified 2026-09-22

The full change log

Sources

Change-log entries restate provider announcements with sources and dates. Impact notes cite public practitioner reports. The site publishes no measurements of its own on any model.

Questions about weight and alias changes

How is a change classified as a weight and alias change?

From what the provider wrote, not from a guess about severity. Where a provider states that weights are unchanged, the entry is not classified as a weight change, and where an unchanged model string starts returning something else, it is.

Is this list complete?

It covers the model families we track for customers, inside a twelve-month window, where the announcement is reachable on the provider's own domain. Anything we cannot reach there is not published, however widely it was reported. Send us a provider link and we will add it.

Do you say what this did to real features?

No. The impact notes say what this kind of change typically touches, each citing a published practitioner source. What it did to your feature is a question only a rerun against your own dataset answers.