TOTopfi·Feb 27, 2025
Considering both this blog post and the livestream demos, I am underwhelmed. Having just finished the stream, I had a real "was that all" moment, which on one hand shows how spoiled I've gotten by new models impressing me, but on another feels like OpenAI really struggles to stay ahead of their competitors.
What has been shown feels like it could be achieved using a custom system prompt on older versions of OpenAIs models, and I struggle to see anything here that truly required ground-up training on such a massive scale. Hearing that they were forced to spread their training across multiple data centers simultaneously, coupled with their recent release of SWE-Lancer [0] which showed Anthropic (Claude 3.5 Sonnet (new) to be exact) handily beating them, I was really expecting something more than "slightly more casual/shorter output", which
Read the rest
again, I fail to see how that wasn't possible by prompting GPT-4o.
Looking at pricing [1], I am frankly astonished.
> Input: $75.00 / 1M tokens
> Cached input: $37.50 / 1M tokens
> Output: $150.00 / 1M tokens
How could they justify that asking price? And, if they have some amazing capabilities that make a 30-fold pricing increase justifiable, why not show it? Like, OpenAI are many things, but I always felt they understood price vs performance incredibly well, from the start with gpt-3.5-turbo up to now with o3-mini, so this really baffles me. If GPT-4.5 can justify such immense cost in certain tasks, why hide that and if not, why release this at all?
[0] https://github.com/openai/SWELancer-Benchmark
[1] https://openai.com/api/pricing/