we found something interesting and wanted to share it with this community. we wanted to know how google's gemma 4 e2b-it — 2 billion parameters, bfloat16, apache 2.0 — stacks up against gpt-3.5 turbo. not in vibes. on the same test. mt-bench: 80 questions, 160 turns, graded 1-10 — what the field used to grade gpt-3.5 turbo, gpt-4, and every major model of the last three years. we ran gemma through all of it on a cpu.…
Grading by hand was done fully blinded? (Also this comment is ai generated so I’m not sure who I’m even asking.)
CPUs Aren't Dead. Gemma2B Out Scored GPT-3.5 Turbo on Test That Made It Famous
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Re: CPUs Aren't Dead. Gemma2B Out Scored GPT-3.5 Turbo on Test That Made It Famous
#42Earlier quoted context omitted.
I know that's one of the tells of AI-generated text, but if anything there's too much of it on this page. The article barely has any complete sentences. I think a human learned "sentence fragments == punchy" and then had too much fun writing at least some of this article.
My guess is they used the 2b model to write the article as a proof of concept. Which did not prove the concept.
Re: CPUs Aren't Dead. Gemma2B Out Scored GPT-3.5 Turbo on Test That Made It Famous
#43> The model does not need to be retrained. It needs surgical guardrails at the exact moments where its output layer flinches. > With those guardrails — a calculator for arithmetic, a logic solver for formal puzzles, a per-requirement verifier for structural constraints, and a handful of regex post-passes — the projected score climbs to ~8.2. Surgical guardrails? Tools, those are just tools.
>It needs surgical guardrails at the exact moments where its output layer flinches. This article is very clearly shitty LLM output. Abstract noun and verb combos are the tipoff. It's actually quite horrible, it repeats lines from paragraph to paragraph.
Re: CPUs Aren't Dead. Gemma2B Out Scored GPT-3.5 Turbo on Test That Made It Famous
#44This really shows the power of distillation. One thing I find amusing: download the Google Edge Gallery app and one of the chat models, then go into airplane mode and ask it about where it’s deployed. gemma-4-e2b-it is quite confident that it is deployed in a Google datacenter and that deploying it on a phone is completely impossible. The larger 4B model is much subtler: it’s skeptical about the claim but does seem t…
Re: CPUs Aren't Dead. Gemma2B Out Scored GPT-3.5 Turbo on Test That Made It Famous
#45Earlier quoted context omitted.
>It needs surgical guardrails at the exact moments where its output layer flinches. This article is very clearly shitty LLM output. Abstract noun and verb combos are the tipoff. It's actually quite horrible, it repeats lines from paragraph to paragraph.
I don't care anymore, if it happens to violate HN guidelines: Please, authors. Please write your own damn articles. We can absolutely tell that you're using Claude, I promise. (I mean, it might not be Claude specifically this time, but frankly I'd be willing to bet on it.) The AI writing is like nails on a chalkboard to me.
Re: CPUs Aren't Dead. Gemma2B Out Scored GPT-3.5 Turbo on Test That Made It Famous
#46I'm very surprised at the quality of the new Gemma 4 models. On my 32 gig Mac mini I can be very productive with it. Not close to replacing paid AI by a long shot, but if I had to tighten the belt I could do it as someone who already knows how to program.
Re: CPUs Aren't Dead. Gemma2B Out Scored GPT-3.5 Turbo on Test That Made It Famous
#47Can you run the same tests on Qwen3.5:9b? that's also a model that runs very well locally, and I believe it's even stronger than Gemma2B
We may beat you to it and we will share if we do lol
Re: CPUs Aren't Dead. Gemma2B Out Scored GPT-3.5 Turbo on Test That Made It Famous
#48Can you run the same tests on Qwen3.5:9b? that's also a model that runs very well locally, and I believe it's even stronger than Gemma2B
It's almost like Qwen 3.5 9B is 4 times larger.
Re: CPUs Aren't Dead. Gemma2B Out Scored GPT-3.5 Turbo on Test That Made It Famous
#49But, Gemma really is very impressive. The premise that people are paying for GPT-3.5 or using it for serious work is weird, though? GPT-3.5 was bad enough to convince a lot of folks they didn't need to worry about AI. Good enough to be a chatbot for some category of people, but not good enough to actually write code that worked, or prose that could pass for human (that's still a challenge for current SOTA models, as this article written by Claude proves, but code is mostly solved by frontier models).
Tiny models are what I find most exciting about AI, though. Gemma 2B isn't Good Enough for anything beyond chatting, AFAIC, and even then it's not very smart. But, Gemma 31B or the MoE 26BA4B probably are Good Enough. And, those run on modest hardware, too, relatively speaking. A 32GB GPU, even an old one, can run either one at 4-bit quantization, and they're OK, competitive with frontier models of 18 months ago. They can write code in popular languages, the code works. They can use tools. They can find bugs. Their prose is good, though still obviously AI slop; too wordy, too flowery. But, you could build real and good software using nothing but Gemma 4 31B, if you're already a good programmer that knows when the LLM is going off on a bizarre tangent. For things where correctness can be proven with tools, a model at the level of Gemma 4 31B can do the job, if slower and with a lot more hand-holding than Opus 4.6 needs.
The Prism Bonsai 1-bit 8B model is crazy, too. Less than 2GB on disk, shockingly smart for a tiny model (but also not Good Enough, by my above definition, it's similarly weak to Gemma 2B in my limited testing), and plenty fast on modest hardware.
Small models are getting really interesting. When the AI bubble pops (or whatever happens to normalize things, so normal people can buy RAM and GPUs again) we'll be able to do a lot with local models.