Will a 15 billion parameter LLM match or outperform GPT4 in 2024?
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GPT-4's benchmark results as of its release in march 2023.

Acceptable upto 17 billion.

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I reviewed the Yes claim from Jonathan for Gemini 1.5 8b and Gemma 2 9b.

I found a website called docsbot.ai which has a comparison feature between models that includes a benchmark comparison table:

First, it looks like gemma-2-9b comes up short in ALL benchmarks, I don't think this reaches "match or outperform":

https://docsbot.ai/models/compare/gemma-2-9b/gpt-4-0314

Next, gemini-1.5-flash-8b only has one benchmark in common with gpt-4-0314, but it does win on that benchmark:

https://docsbot.ai/models/compare/gemini-1-5-flash-8b/gpt-4-0314

I think this is enough to resolve Yes because it matched or outperformed on a benchmark. If I have terribly misunderstood things, maybe you can make an argument the other way. No one made any progress on this when Nathan Young looked at it 4 months ago and I am eager to resolve it.

I'll resolve this in 24-48 hours if no one has any complaints.

@mods can this resolve yes? According to LMSYS, the March 2024 version of GPT-4 is currently ranked 40th and is outclassed by Gemini 1.5 8b in 31st and Gemma 2 9b in 25.

@JonathanMilligan Closing while I try and understand.

@JonathanMilligan Wait, why should LMSYS count? That isn't a benchmark, right?

@NathanpmYoung Yeah LMSYS is a benchmark of how people rank the output of LLM models.

@JonathanMilligan Currently it seems to be the best benchmark of real “in the wild” use.

@JonathanMilligan Okay but it isn't a "benchmark" see "GPT-4's benchmark results as of its release in march 2023." Right?

@mods what do you think?

Sebastian Bubeck (Microsoft research) recently said that he thinks a 13 billion parameter model could do this. There've been reports of others working at similar sized models for similar performance.

@firstuserhere Source? Interesting speculation there

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