Re:Gemini 3.0 spotted in the wild through A/B testing
by behnamoh on Thursday October 16, 2025 @01:51PM
(#45608511)
Gemini was good when the thinking tokens were shown to the user. As soon as Google replaced those with some thought summary, I stopped finding it as useful. Previously, the thoughts were so organized that I would often read those instead of the final answer.
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Re:Gemini 3.0 spotted in the wild through A/B testing
by dwringer on Thursday October 16, 2025 @02:24PM
(#45608906)
These were extremely helpful to read for insights on how to go back and retry different prompts instead, IMHO. I find it to be a significant step back in usability to lose those although I can understand the argument that they weren't directly useful on their own outside of that use case.
Re:Gemini 3.0 spotted in the wild through A/B testing
by kridsdale3 on Thursday October 16, 2025 @02:59PM
(#45609319)
In the API, the thinking tokens are just a different stream. You can still read them.
Re:Gemini 3.0 spotted in the wild through A/B testing
by deaux on Friday October 17, 2025 @05:31AM
(#45614794)
They aren't, in the API too they're a thought summary, not nearly as useful as actually showing the thoughts. Anthropic still does provide raw thoughts to this day, showing how it's not necessary to keep a moat. Google and OpenAI don't.
[0] https://ai.google.dev/gemini-api/docs/thinking#summaries
[1] https://discuss.ai.google.dev/t/thoughts-are-missing-cot-not...
[2] https://discuss.ai.google.dev/t/massive-regression-detailed-...
[2]
Re:Gemini 3.0 spotted in the wild through A/B testing
by behnamoh on Friday October 17, 2025 @09:54AM
(#45616857)
to be fair, Anthropic reasoning models don't have long thinking to begin with, and I find their reasoning pretty useless compared to what Gemini used to do.
Re:Gemini 3.0 spotted in the wild through A/B testing
by deaux on Friday October 17, 2025 @03:36PM
(#45621066)
Long thinking seems to be a marketing term without clear definition, only applicable to the opaque chat frontends. If you give Anthropic models a hard problem and set the thinking budget high (API), it does plenty of reasoning and the CoT helps a lot with debugging. With Gemini and OpenAI you can't debug as the summaries tell you effectively nothing about why it's giving a wrong answer or going off the rails when it does som