DeadAI Dev Tools

GPT-3.5 Turbo 0301 / 0613 (specific dated checkpoints)

by OpenAI

Announced

2024-06-13

Complete

2024-09-13

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Refund status

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OpenAI maintained both a generic `gpt-3.5-turbo` alias that pointed to the current default checkpoint, and dated checkpoints (for example `gpt-3.5-turbo-0301`) that pinned to specific model versions. `gpt-3.5-turbo-0301`, `gpt-3.5-turbo-0613` and `gpt-3.5-turbo-16k-0613` were shut down on September 13, 2024, so apps that pinned those strings for output reproducibility broke while apps on the alias kept working. Two later dates matter and are often confused with this one: `gpt-3.5-turbo-1106` is not part of this batch and shuts down September 28, 2026, and the alias itself is no longer a safe harbour, because OpenAI lists `gpt-3.5-turbo` and `gpt-3.5-turbo-0125` as shutting down October 23, 2026.

Refund flow

  1. 1

    Not applicable. Pay-as-you-go API, no credits tied to deprecated checkpoints.

Migration path

Recommended successor

gpt-5.6-terra

Why this is the closest fit

Migrating onto the `gpt-3.5-turbo` alias was the right move in 2024 and is a dead end now, because OpenAI lists the alias and `gpt-3.5-turbo-0125` as shutting down October 23, 2026. `gpt-5.6-terra` is the replacement OpenAI names on that row, and on the row for every other retiring GPT-3.5 string.

What differs from the original

If your app relied on reproducibility of a specific dated checkpoint for an evaluation harness or regression tests, no alias will honour that contract. Pin the dated snapshot of the replacement instead. Re-run your eval set after the swap rather than assuming parity: prompts tuned against a 2023 GPT-3.5 checkpoint were tuned against very different instruction-following behaviour.

What this tool meant

Dated-checkpoint pinning is the standard for production AI applications — you don't want your model behavior to drift silently when OpenAI updates the alias. The sunset of older dated checkpoints caused a quiet wave of production breakage in mid-2024 across applications that hadn't migrated to newer pins. The lesson for AI ops: monitor OpenAI's deprecation page proactively, don't pin to checkpoints near the deprecation horizon, and budget migration time well before the cutoff.

Sources

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