291–300 of 1001 posts
If you want to try it out via their API you can run it through my LLM tool using uvx like this: uvx --with 'https://github.com/simonw/llm/archive/801b08bf40788c09aed6175252876310312fe667.zip' \ llm -m gpt-4.5-preview 'impress me' You may need to set an API key first, either with `export OPENAI_API_KEY='xxx'` or using this command to save it to a file: uvx llm keys set openai # paste key here Or this to get a chat ses…
It is interesting that they are focusing a large part of this release on the model having a higher "EQ" (Emotional Quotient). We're far from the days of "this is not a person, we do not want to make it addictive" and getting a firm foot on the territory of "here's your new AI friend". This is very visible in the example comparing 4o with 4.5 when the user is complaining about failing a test, where 4o's response is wh…
I would like to see a humor test. So far, I have not seen any model response that has made me laugh.
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Altman's claim and NVIDIA's consumer launch supply problems may be related - OpenAI may be eating up the GPU supply...
OpenAI is not purchasing consumer 5090s... :)
> Because of this, we’re evaluating whether to continue serving it in the API long-term as we balance supporting current capabilities with building future models. Seems like it's not going to be deployed for long. $75.00 / 1M tokens for input $150.00 / 1M tokens for output That's crazy prices.
Until GPT-4.5, GPT-4 32K was certainly the most heavy model available at OpenAI. I can imagine the dilemma between to keep it running or stop it to free GPU for training new models. This time, OpenAI was clear whether to continue serving it in the API long-term.
$60/M input tokens vs $75/M input tokens
$120/M output tokens vs $150/M output tokens
The results for GPT - 4.5 are in for Kagi LLM benchmark too. It does crush our benchmark - time to make new? ;) - with performance similar of that of reasoning models. It does come at a great price both in cost and speed. A monster is what they created. But looking at the tasks it fails, some of them my 9 year old would solve. Still in this weird limbo space of super knowledge and low intelligence. May be remembered…
If Gemini 2 is the top in your benchmark, make sure to re-check your benchmark.
I am beginning to think these human eval tests are a waste of time at best, and negative value at worst. Maybe I am being snobby, but I don't think the average human is able to properly evaluate usefulness, truthfulness, or other metrics that I actually care about. I am sure this is good for openAI since if more people like what the hear, they are more likely come back. I don't want my AI more obsequious, I want it m…
First impression of GPT-4.5: 1. It is very very slow, for some applications where you want real time interactions is just not viable, the text attached below took 7s to generate with 4o, but 46s with GPT4.5 2. The style it writes is way better: it keeps the tone you ask and makes better improvements on the flow. One of my biggest complaints with 4o is that you want for your content to be more casual and accessible bu…
If you want to try it out via their API you can run it through my LLM tool using uvx like this: uvx --with 'https://github.com/simonw/llm/archive/801b08bf40788c09aed6175252876310312fe667.zip' \ llm -m gpt-4.5-preview 'impress me' You may need to set an API key first, either with `export OPENAI_API_KEY='xxx'` or using this command to save it to a file: uvx llm keys set openai # paste key here Or this to get a chat ses…
Just curious, does this stream the output or renders all at once ?
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> We look forward to learning more about its strengths, capabilities, and potential applications in real-world settings. If GPT‑4.5 delivers unique value for your use case, your feedback (opens in a new window) will play an important role in guiding our decision. "We don't really know what this is good for, but spent a lot of money and time making it and are under intense pressure to announce new things right now. If…
> We don't really know what this is good for Oh come on. Think how long of a gap there was between the first microcomputer and VisiCalc. Or between the start of the internet and social networking. First of all, it's going to take us 10 years to figure out how to use LLM's to their full productive potential. And second of all, it's going to take us collectively a long time to also figure out how much accuracy is neces…