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Claude 3 model family

anthropic.com

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Re: Claude 3 model family

#31

Post by ethbr1 »

vermorel wrote: post #28

Does any of those LLM-as-a-service companies provide a mechanism to "save" a given input? Paying only for the state storage and the extra input when continuing the completion from the snapshot? Indeed, at 1M token and $15/M tokens, we are talking of $10+ API calls (per call) when maxing out the LLM capacity. I see plenty of use cases for such a big context, but re-paying, at every API call, to re-submit the exact sam…

How would that work technically, from a cost of goods sold perspective? (honestly asking, curious)

Re: Claude 3 model family

#35

Post by avereveard »

_sword wrote: post #14

At this point I wonder how much of the GPT-4 advantage has been OpenAI's pre-training data advantage vs. fundamental advancements in theory or engineering. Has OpenAI mastered deep nuances others are missing? Or is their data set large enough that most test-cases are already a sub-set of their pre-training data?

So far gpt is the only one able to answer to variations of these prompts https://www.lesswrong.com/posts/EHbJ69JDs4suovpLw/testing-pa... it might be trained on these but still you can create variations and get decent responses

Most other model fail on basic stuff like the python creator on stack overflow question, they identify Guido as the python creator, so the knowledge is there, but they don't make the connection.

Re: Claude 3 model family

#36

Post by declaredapple »

up6w6 wrote: post #22

The Opus model that seems to perform better than GPT4 is unfortunately much more expensive than the OpenAI model. Pricing (input/output per million tokens): GPT4-turbo: $10/$30 Claude 3 Opus: $15/$75

Yeah the output pricing I think is really interesting, 150% more expensive input tokens 250% more expensive output tokens, I wonder what's behind that?

That suggests the inference time is more expensive then the memory needed to load it in the first place I guess?

Re: Claude 3 model family

#39

Post by [deleted] »

avereveard wrote: post #35
_sword wrote: post #14

At this point I wonder how much of the GPT-4 advantage has been OpenAI's pre-training data advantage vs. fundamental advancements in theory or engineering. Has OpenAI mastered deep nuances others are missing? Or is their data set large enough that most test-cases are already a sub-set of their pre-training data?

So far gpt is the only one able to answer to variations of these prompts https://www.lesswrong.com/posts/EHbJ69JDs4suovpLw/testing-pa... it might be trained on these but still you can create variations and get decent responses Most other model fail on basic stuff like the python creator on stack overflow question, they identify Guido as the python creator, so the knowledge is there, but they don't make the connection…

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