How to Track AI Model Deprecation Dates Across Providers

Start with the service that actually serves the model

Record the exact model ID, the API or managed platform that serves it, the region, and the application that depends on it. A team calling a model through a provider's direct API may not share the same retirement date as a service using that model through a cloud marketplace or managed platform.

For example, the Anthropic model deprecations page says partner-operated platforms such as Amazon Bedrock and Google Cloud set their own retirement schedules. Amazon's Bedrock model lifecycle policy says its lifecycle dates apply to Bedrock and may differ from dates published by a model provider. Check the page for the platform your application uses.

A useful inventory row therefore contains more than a vendor and a friendly model name. Keep the deployed identifier and serving platform next to the region and owner so a lifecycle notice can be matched to the right workload.

Translate lifecycle terms before assigning work

The OpenAI API deprecations page distinguishes a legacy model or endpoint, which no longer receives updates, from a deprecated one that is in the process of being retired. The shutdown date is when it is no longer accessible.

In the Anthropic model lifecycle, a deprecated model still works but is no longer recommended; the provider supplies a replacement and retirement date. A retired model is no longer available and its requests fail.

The Gemini API deprecations page uses deprecation for the announcement that support will end and shutdown for the point when the endpoint is unavailable. Its table can show an earliest possible shutdown date rather than a final date.

For Amazon Bedrock, the documented states are Active, Legacy, and End-of-Life. The model card carries the Bedrock schedule, and migration does not happen automatically.

Treat each lifecycle label as a provider-defined state. Before opening a migration ticket, write down what the current state allows, when access changes, and which platform's source page establishes the date.

Keep provider dates separate from your team's dates

For each notice, record the announcement date, the provider's stated retirement or shutdown date, and any uncertainty such as an earliest-possible date. Then add the team's own test, release, and rollback dates. A planned cutover is an engineering deadline; it is not the provider's shutdown date.

When the provider updates a schedule, preserve the previous date and the new official evidence. This makes it possible to see whether a changed plan came from a new source notice, a different platform, or a revised internal rollout.

Turn the notice into a migration check

First, search configuration and provider usage records for the exact model ID. Confirm the serving platform and region instead of assuming that a familiar model family name identifies every deployment. Assign an owner for each affected service and note whether the dependency is production or experimental.

Next, test a replacement on representative tasks before changing production traffic. Check the behavior your application relies on: structured output validity, tool-call arguments, latency, cost per completed task, and downstream parsing. Use a canary or staged rollout where the workload allows it, and keep a rollback path until the new model is stable.

ReleaseDelta's public AI and API deprecation calendar links published lifecycle entries to their official evidence. The coverage page describes current source and change-type boundaries. You can also inspect the sample change brief and try monitoring one declared dependency without sharing provider credentials or production traffic.