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GPT-4.5

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Re: GPT-4.5

#501
post #26

GPT 4.5 pricing is insane: Price Input: $75.00 / 1M tokens Cached input: $37.50 / 1M tokens Output: $150.00 / 1M tokens GPT 4o pricing for comparison: Price Input: $2.50 / 1M tokens Cached input: $1.25 / 1M tokens Output: $10.00 / 1M tokens It sounds like it's so expensive and the difference in usefulness is so lacking(?) they're not even gonna keep serving it in the API for long: > GPT‑4.5 is a very large and comput…

Did they already disable it?

When using `gpt-4.5-preview` I am getting: > Invalid URL (POST /v1/chat/completions)

Re: GPT-4.5

#502
post #467

Earlier quoted context omitted.

They are pretty useful tools. Do yourself a favor and get a $100 free trial for Claude, hook it up to Aider, and give it a shot. It makes mistakes, it gets things wrong, and it still saves a bunch of time. A 10 minute refactoring turns into 30 seconds of making a request, 15 seconds of waiting, and a minute of reviewing and fixing up the output. It can give you decent insights into potential problems and error messag…

> a $100 free trial What?

A free trial of an amount of credits that would otherwise cost $100, I'm assuming.

Re: GPT-4.5

#503
post #26

GPT 4.5 pricing is insane: Price Input: $75.00 / 1M tokens Cached input: $37.50 / 1M tokens Output: $150.00 / 1M tokens GPT 4o pricing for comparison: Price Input: $2.50 / 1M tokens Cached input: $1.25 / 1M tokens Output: $10.00 / 1M tokens It sounds like it's so expensive and the difference in usefulness is so lacking(?) they're not even gonna keep serving it in the API for long: > GPT‑4.5 is a very large and comput…

I wonder if the pricing is partly to discourage distillation, if they suspect r1 was distilled from gpt 4o

Mainly to prevent you from using it

Re: GPT-4.5

#504
post #26

GPT 4.5 pricing is insane: Price Input: $75.00 / 1M tokens Cached input: $37.50 / 1M tokens Output: $150.00 / 1M tokens GPT 4o pricing for comparison: Price Input: $2.50 / 1M tokens Cached input: $1.25 / 1M tokens Output: $10.00 / 1M tokens It sounds like it's so expensive and the difference in usefulness is so lacking(?) they're not even gonna keep serving it in the API for long: > GPT‑4.5 is a very large and comput…

I suppose this was their final hurrah after two failed attempts at training GPT-5 with the traditional pre-training paradigm. Just confirms reasoning models are the only way forward.

> Just confirms reasoning models are the only way forward.

Reasoning models are roughly the equivalent to allow Hamiltonian Monte-Carlo models to "warm up" (i.e. start sampling from the typical set). This, unsurprisingly, yields better results (after all LLMs are just fancy Monte-carlo models in the end). However, it is extremely unlikely this improvement is without pretty reasonable limitations. Letting your HMC warm up is essential to good sampling, but letting "warm up more" doesn't result in radically better sampling.

While there have been impressive results in efficiency of sampling from the typical set seen in LLMs these days, we're clearly not making the major improvements in the capabilities of these models.

Re: GPT-4.5

#506

Earlier quoted context omitted.

Further confirmation, IMO, that the idea that any of this leads to anything close to AGI is people getting high on their own supply (in some cases literally). LLMs are a great tool for what is effectively collected knowledge search and summary (so long as you are willing to accept that you have to verify all of the 'knowledge' they spit back because they always have the ability to go off the rails) but they have been…

I'd put myself on the pessimistic side of all the hype, but I still acknowledge that where we are now is a pretty staggering leap from two years ago. Coding in particular has gone from hints and fragments to full scripts that you can correct verbally and are very often accurate and reliable.

I'm not saying there's been no improvement at all. I personally wouldn't categorize it as staggering, but we can agree to disagree on that.

I find the improvements to be uneven in the sense that every time I try a new model I can find use cases where its an improvement over previous versions but I can also find use cases where it feels like a serious regression.

Our differences in how we categorize the amount of improvement over the past 2 years may be related to how much the newer models are improving vs regressing for our individual use cases.

When used as coding helpers/time accelerators, I find newer models to be better at one-shot tasks where you let the LLM loose to write or rewrite entire large systems and I find them worse at creating or maintaining small modules to fit into an existing larger system. My own use of LLMs is largely in the latter category.

To be fair I find the current peak model for coding assistant to be Claude 3.5 Sonnet which is much newer than 2 years old, but I feel like the improvements to get to that model were pretty incremental relative to the vast amount of resources poured into it and then I feel like Claude 3.7 was a pretty big back-slide for my own use case which has recently heightened my own skepticism.

Re: GPT-4.5

#507

Earlier quoted context omitted.

> "Early testing shows that interacting with GPT‑4.5 feels more natural. Its broader knowledge base, improved ability to follow user intent, and greater “EQ” make it useful for tasks like improving writing, programming, and solving practical problems. We also expect it to hallucinate less." "Early testing doesn't show that it hallucinates less, but we expect that putting that sentence nearby will lead you to draw a c…

That's some top-tier sales work right there. I suck at and hate writing the mildly deceptive corporate puffery that seems to be in vogue. I wonder if GPT-4.5 can write that for me or if it's still not as good at it as the expert they paid to put that little gem together.

Yes, an AI that can convincingly and successfully sell itself at those prices would be worthy of some attention.

Re: GPT-4.5

#508

Earlier quoted context omitted.

> AI as it stands in 2025 is an amazing technology, but it is not a product at all. Here I'm assuming "AI" to mean what's broadly called Generative AI (LLMs, photo, video generation) I genuinely am struggling to see what the product is too. The code assistant use cases are really impressive across the board (and I'm someone who was vocally against them less than a year ago), and I pay for Github CoPilot (for now) but…

I think search and chat are decent products as well. I am a Google subscriber and I just use Gemini as a replacement for search without ads. To me, this movement accelerated paid search in an unexpected way. I know the detractors will cry "hallucinations" and the ilk. I would counter with an argument about the state of the current web besieged by ads and misinformation. If people carry a reasonable amount of skeptici…

speaking of search without ads, I wholeheartedly recommend https://kagi.com

Re: GPT-4.5

#509

It significantly improves upon GPT-4o on my Extended NYT Connections Benchmark. 22.4 -> 33.7 ( https://github.com/lechmazur/nyt-connections ).

I ran three more of my independent benchmarks:

- Improves upon GPT-4o's score on the Short Story Creative Writing Benchmark, but Claude Sonnets and DeepSeek R1 score higher. (https://github.com/lechmazur/writing/)

- Improves upon GPT-4o's score on the Confabulations/Hallucinations on Provided Documents Benchmark, nearly matching Gemini 1.5 Pro (Sept) as the best-performing non-reasoning model. (https://github.com/lechmazur/confabulations)

- Improves upon GPT-4o's score on the Thematic Generalization Benchmark, however, it doesn't match the scores of Claude 3.7 Sonnet or Gemini 2.0 Pro Exp. (https://github.com/lechmazur/generalization)

I should have the results from the multi-agent collaboration, strategy, and deception benchmarks within a couple of days. (https://github.com/lechmazur/elimination_game/, https://github.com/lechmazur/step_game and https://github.com/lechmazur/goods).

Re: GPT-4.5

#510

Earlier quoted context omitted.

> "Early testing shows that interacting with GPT‑4.5 feels more natural. Its broader knowledge base, improved ability to follow user intent, and greater “EQ” make it useful for tasks like improving writing, programming, and solving practical problems. We also expect it to hallucinate less." "Early testing doesn't show that it hallucinates less, but we expect that putting that sentence nearby will lead you to draw a c…

The usage of "greater" is also interesting. It's like they are trying to say better, but greater is a geographic term and doesn't mean "better" instead it's closer to "wider" or "covers more area."

2 is greater than 1.
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