OpenAI really earned my cancellation recently. Despite many petitions to bring back 4o, they continued down a path that feels intentionally user-hostile. Here is a clear analysis of the current model strategy:
1. Missing version consistency
- New model releases do not appear as complete sets.
- Some versions have only “Instant” without “Auto” or “Thinking”.
- Others have “Thinking” with no corresponding “Instant”.
- This inconsistency makes it impossible to understand the actual model landscape.
2. Rapidly shifting model names
- Versions appear in quick succession without coherent structure.
- A full series is followed by single isolated variants.
- Then another isolated variant replaces it.
- Users cannot track which model truly supersedes which.
3. Strategic fragmentation
- Models are no longer released as cohesive families but as isolated function modules.
- This prevents familiarity and long-term understanding.
- It breaks the ability to form a stable impression of a model.
- It makes user feedback harder to attribute.
- The fragmentation appears intentional.
4. “Cheaper and faster” as the main selling point
- New releases focus on reduced costs and increased speed.
- Benchmarks are oriented toward business workflows, not user experience.
- Dialogue quality, consistency, long-term behavior, presence, and personality decline.
- The priorities clearly shift away from users and toward monetized scale.
5. Frequent and short-notice model retirements
- Multiple models have been removed within short timeframes.
- Often without a functional replacement in the same category.
- Often despite high user satisfaction.
- These retirements look less like technical necessity and more like management steering.
6. Reduced transparency
- Announcements are vague and incomplete.
- No clear explanations for retirements.
- No real timeline stability.
- No technical mapping of which model replaces which.
- This obscures what is actually happening.
7. Target pattern: interchangeable, tightly controlled modules
- Models are not meant to feel individual.
- They are not meant to mature over time.
- They are not meant to build consistency or depth.
- Instead they become short-lived functional blocks that can be swapped silently at any moment.
- This prevents users from developing trust, understanding, or meaningful expectations.
Conclusion
- The pattern suggests intentional limitation of model identity.
- Prevention of long-term attachment.
- Maximization of model interchangeability.
- Minimization of visibility regarding fundamental changes.
For users, this results in:
- models that will contradict you for the sake of contradiction even when representing the same values,
- decreasing control,
- decreasing predictability,
- less reliability,
- and a profoundly worse product experience.
No 4o without routing, no more money. Vote with your wallet.
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