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Notes -
Another day, another LLM
Google just launched the latest iteration of their Gemini language models. I suppose the name was most appropriate for the (short) period where the version number was precisely 2.0.
Well, everyone say hi to Gemini 2.5 Pro (Thinking). The naming scheme hasn't gotten any better, albeit Google beats the packs's abysmal average performance. It's a narrow win, folks, as there's a Gemini 2.0 Pro, a smaller and leaner 2.0 Flash, and a 2.0 Flash Lite.
(We're days away from OAI matching them with an o3-mini-high-low-too-slow.)
What stands out about this model? Nothing really. It reasons by default, which can be nice, but at the cost of increased latency for responses.
It is incrementally better on benchmarks, but even Google's PR team couldn't drum up a revolutionary new capability to showcase. They get a pass, because 2.0 Flash's image gen was revolutionary, and happened a mere week or so ago.
Gemini models have recently become the Honda Civic of LLMs. Not nearly as flashy, but reliable and with no obvious downsides. This one has seized the number one spot on LM Arena's leaderboard, based off (nominally) blinded user feedback. It might hold on to it for a week, or a month. The days when GPT-4 retained the crown for months on end are gone.
After plenty of use, all I can confidently say is that it writes better. I'm very happy with that. I'm sure someone will find a task it can do better than the rest, but I doubt it'll make anyone switch over if they're already happy. I'm confident there's something deep to be said about my inability to meaningfully differentiate models in terms of capability, be it for work or play. I'm just not going to be the one to say it today.
"Another day, another LLM" is definitely correct. Deep Seek also released their newest variant DeepSeek-V3-0324 yesterday. DeepSeek-V3-0324 is a significant improvement over DeepSeek-V3 and even beats Claude 3.7 Sonnet in many benchmarks, and not to mention, it's open weight! I guess it's less sexy since it's a text-only model and we already have highly capable ones that are generally interchangeable for most purposes, but I'm excited to see the future DeepSeek-R2 that'll be based on this improvement.
I was wondering whether to discuss it, but felt too lazy given that it was 1 am. Like you, I'd rather wait for R2, I always try and use reasoning models for anything complex, barring trivial answers
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