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Are there any specifics about how this was trained? Especially when 5.1 is only a month old. I'm a little skeptical of benchmarks these days and wish they put t
by sigmar 10mo ago
Are there any specifics about how this was trained? Especially when 5.1 is only a month old. I'm a little skeptical of benchmarks these days and wish they put this up on llmarena
edit: noticed 5.2 is ranked in the webdev arena (#2 tied with gemini-3.0-pro), but not yet in text arena (last update 22hrs ago)
- kouteiheika 10mo agoUnfortunately there are never any real specifics about how any of their models were trained. It's OpenAI we're talking about after all.
- emp17344 10mo agoI’m extremely skeptical because of all those articles claiming OpenAI was freaking out about Gemini - now it turns out they just casually had a better model ready to go? I don’t buy it.
- tempaccount420 10mo agoThey had to rush it out, I'm sure the internal safety folks are not happy about it.
- Workaccount2 10mo agoI (and others) have a strong suspicion that they can modulate models intelligence in almost real time by adjusting quantization and thinking time. It seems if anyone wants, they can really gas a model up in the moment and back it off after the hype wave.
- bamboozled 10mo agoYeah I've noticed with Claude, around the time of the Opus 4.5 release, at least for a few days, Sonnet 4.5 was just dumb, but it seems temporary. I feel that redirected resources to Opus.
- qeternity 10mo agoQuantization is not some magical dial you can just turn. In practice you basically have 3 choices: fp16, fp8 and fp4. Also thinking time means more tokens which costs more especially at the API level where you are paying per token and would be trivially observable. There is basically no evidence that either of these are occurring in the way you suggest (boosting up and down).
- Workaccount2 10mo agoAPI users probably wouldn't be affected since they are paying in full. Most people complaining are free users, followed by $20/mo users.
- bamboozled 10mo agoIt's very inline with their PR strategy, or lack of.
- robots0only 10mo agohow do you know this is a better model? I wouldn't take any of the numbers at face value especially when all they have done is more/better post-training and thus the base pre-trained model capabilities is still the same. The model may just elicit some of the benchmark capabilities better. You really need to spend time using the model to come to any reliable conclusions.