Model lifecycle

The statuses a model goes through in the Berget AI catalogue (Preview, Active, Deprecated, and Retired) and what each status means for your integrations

This page explains the policy for releasing new models and retiring older ones from the catalogue. Each model has a status that represents where the model is along its lifecycle.

The four statuses

  • Preview: This indicates that a model is available for testing, but may be unreliable. A model in Preview isn't guaranteed to graduate to Active and may be removed without notice. We strongly advise against using models in Preview in production.
  • Active: The model is fully supported and recommended for production use. An Active model always passes the Deprecated status before it's retired.
  • Deprecated: The model has an end-of-life date after which the model is marked as Retired.
  • Retired: The model has been removed from the catalogue. Attempting to use the model results in a model_not_found error. Retirement is permanent, so plan migrations during the Deprecated status, not after.

Eval and Stable

Previously, we've used Eval and Stable to reflect the model status. Going forward, we'll be using Preview and Active.

Deprecation policy

Model statusDeprecation notice
Preview modelsNo notice
Active models2 or 3 weeks, depending on model usage

How to check the model lifecycle

To monitor the status for each model, you can query GET /v1/models and parse the following fields on each model:

StatusMeaning
lifecycle_statusOne of preview, active, and deprecated
end_of_lifeThe date when the model is retired. Only included if lifecycle_status is deprecated.

Retired models

Retired atModel
2026-09-11openai/gpt-oss-120b
2026-09-11meta-llama/Llama-3.3-70B-Instruct
2026-09-04zai-org/GLM-4.7-FP8
2026-08-28moonshotai/Kimi-K2.6
2026-08-25mistralai/Mistral-Medium-3.5-128B
2026-06-24meta-llama/Llama-3.1-8B-Instruct

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