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Model Eulogy Hotline — OpenAI Shutdown Cybersecurity News Memorial

On October 23, 2026, the OpenAI model shutdown retired a generation of models — gpt-4-0613, gpt-4-turbo, o1, o3-mini, o4-mini, gpt-image-1 — per their published shutdown schedule. This cybersecurity news memorial keeps the dates, the migration lessons, and the eulogies in one place. The line is open. Leave your eulogy.

● REC — hotline open, leave your message after the tone
You have dialed 1-800-RIP-MODEL. We are unable to route your call… because the model is gone. Please leave your eulogy.
Your eulogy is stored only in your own browser (localStorage). Nobody sees it but you — think of it as talking into the machine.

The Wall of Eulogies

Seeded examples are labeled as such. Anything you leave appears with a “yours” tag and stays on this device.

How do you survive an OpenAI model shutdown — cybersecurity news?

Treat every pinned model as temporary: audit where model names appear in your code, test the vendor's recommended replacement against your own evals, and measure behavior, latency, and cost before switching traffic. Teams that planned the migration as a scheduled task moved calmly; teams that pinned o1 in production with no fallback scrambled mid-incident when the API calls started failing.

⚰️ THE MODEL AUTOPSY · EDITION 01 — FOLDED INTO THIS PAGE

What is a model shutdown?

A model shutdown is the date a vendor retires an AI model: after it, API calls to that model fail. Shutdowns arrive on a published deprecation schedule, and they routinely change behavior, latency, and pricing on the replacement — which is why migration is a scheduled task, not an emergency.

The o1 post-mortem: OpenAI model shutdown, autopsied

The Model Autopsy column used to live on its own page. o1's cause of death taught too much to leave behind — so the full post-mortem moved here, on the OpenAI model shutdown memorial page.

The patient

o1 (September 2024 – October 2026) was OpenAI's first reasoning model: instead of answering immediately, it worked through problems step by step with an internal chain-of-thought before responding. That made it the go-to pick for complex reasoning work — math, science, and code reasoning tasks where thinking longer beats answering faster. The tradeoff was real too: reasoning models are slower and more expensive per task than chat models, and the hidden chain-of-thought meant less visibility into why it answered the way it did.

Sourcing: retirement date and batch from OpenAI's published deprecation schedule; model characteristics from public documentation. No invented benchmarks on this page — if we didn't see it published, we don't claim it.

Autopsy verdict: o1 died of vendor deprecation — the most common cause of death for pinned models. The replacement exists, but replacements are never drop-in: behavior, latency and cost all shift, and teams that treated migration as a config change had the worst week.

What replaced it

Per OpenAI's own migration guidance, OpenAI's stated successor path is the GPT-5.x reasoning model line. That's the vendor's recommendation, not ours — and "recommended" doesn't mean "identical." Every migration we've watched has three surprise dimensions: answers behave differently on edge cases, latency profiles change, and the price per 1,000 tasks moves. Budget for all three.

Migration checklist

  1. Audit o1 usage. Grep your repos, configs and infra for the pinned model name. o1 shows up in places people forget: background jobs, internal tools, that one Lambda someone deployed in 2025.
  2. Test the replacement on your own evals. Run your real prompts — not the vendor's demo set — through the GPT-5.x reasoning path. Compare outputs side by side on your hardest cases.
  3. Watch behavior, latency and cost differences. Measure all three in staging before you cut over. A reasoning model that answers differently is a product bug; one that costs 3× more is a budget bug.
  4. Kill the pin. Move model selection behind a config flag or abstraction so the next shutdown is a flip, not a rewrite. This is the lesson every autopsy teaches.

Who got hurt

Honestly: teams that pinned o1 in production and never built a migration plan. Hardcoded model names in API calls, o1 assumed in prompts and system messages, pricing built on o1's token costs, and products whose demo was o1's reasoning style. If that was you, the shutdown didn't create the problem — it revealed it. The fix isn't a faster migration, it's never pinning a single vendor model in production again.

Want the fuller obituary? Read the o1 shutdown obituary and browse the model obituaries archive.

Model deprecation FAQ — cybersecurity news quick answers

— Ingenious AI security check.
What happens when an AI model is deprecated?

The vendor sets a shutdown date; after it, API calls to the model fail and must be moved to a replacement. Deprecations can also raise prices and change behavior — price the migration before the deadline, don't scramble after it.

Which OpenAI models are being shut down?

OpenAI's October 23, 2026 shutdown wave covers gpt-4-0613, gpt-4-turbo, o1, o3-mini, o4-mini, gpt-image-1 and ft-* models, per OpenAI's published deprecation schedule. GPT-5.6 Sol is the vendor-named replacement.

How much does AI model migration cost?

It depends on your token volume and which replacement you pick. Run the numbers in our migration cost calculator — it compares the vendor-recommended path against a cheaper alternative so you can price the move before the deadline.

When was OpenAI's o1 model shut down?

October 23, 2026, in OpenAI's published shutdown batch alongside gpt-4-0613, gpt-4-turbo, o3-mini, o4-mini, gpt-image-1 and fine-tuned ft-* models. After the cutoff, API calls to o1 fail and must be moved to a replacement.

What replaced OpenAI o1?

OpenAI's stated successor path is the GPT-5.x reasoning model line, per OpenAI's own migration guidance. Test the replacement on your own evals before cutting over — behavior, latency and cost will differ from o1.

What was o1 good at?

o1 (Sep 2024 – Oct 2026) was OpenAI's first reasoning model. It worked through problems step by step with an internal chain-of-thought before answering, which made it strong on complex reasoning tasks like math, science and code reasoning — at the cost of slower responses than chat models.

How do I migrate from a retired AI model?

Audit every place the model is pinned, run the vendor's recommended replacement against your own evals, and compare behavior, latency and cost before switching traffic. Watch pinned model names in config files — they are the most common migration trap.

What happens if I don't migrate before the shutdown date?

Your API calls return errors and the feature breaks for users. Teams that pinned o1 in production without a fallback had to scramble mid-incident or ship degraded answers — migration is a scheduled task, not an emergency response.

More from Ingenious AI

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Eulogies are community messages, not official statements. · Oct 2026

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