171–180 of 699 posts
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I asked Claude to fix the grammar of my comment, and it changed "I am using 3.7 for" to "I've been using Claude 3.7", so they sneaked their own name on it.
you didn’t even read your comment before you posted it?
2. I'd wager the majority of HN commenters don't read their own comment before posting (pre-LLM days).
Currently top at https://deepswe.datacurve.ai - beating Opus 5! https://artificialanalysis.ai/models/gemini-3-8-flash shows an intelligence score of 59, the same as Opus 5 medium! Wow - for a flash model this seems to benchmark powerfully. Remains to be seen what it is like to use.
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A fifth of the cost of Opus 5! Google is certainly pushing the completion with this.
Gemini hasn't failed me for personal usage yet. I haven't had the opportunity to use it at work.
Yesterday I asked for food stop on my road trip 45 minutes from the current time and it gave me some options, but then I changed my mind and specifically asked for Asian restaurants and it completely forgot about the 45 minutes and gave me the closest Asian restaurant to me.
I've been using Gemini 3.7 for my personal trip planning app. Across multiple benchmarks, it ranks higher on everything I tried: - Real world knowledge (when a thing opens and closes, the geographic region, historical facts). It's also the best at taking a cluster of places and working out a visiting order. - Photo ranking (which photo should be the hero). Gemini can tell whether a photo is of the thing or of the vie…
One thing in your comment surprised me: "when a thing opens and closes" Why you would rely on the model's weights to know opening hours, instead of having the model call a web search tool to verify it on the official site?
It was right on every nit, so it was surprising how well the model knows these things. If I ever release this I'll probably need the SERP API or Google Maps SDK (which I've heard is very expensive now), but for a personal trip where I will verify manually, using the LLM is okay for now.
They've interestingly left out any mention of speed. I have been testing 3.7 flash against 3.5 flash and it seems to lose every time in overall latency. Every benchmark I've seen seems to suggest the opposite[1] - that 3.7 flash is significantly (at times 2x) faster than 3.5 flash - but I have never been able to prove this out in real world use cases. Has anyone found their latency numbers to actually be accurate? Is…
It depends on how you're querying Gemini models. OpenRouter is the fastest by far. I'm guessing they bought the dedicated pipe from Google. Gemini via VertexAI and consumer API has pretty bad latency.
After struggling with Gemini for months, I think the trick to getting the most out of the model is writing a really solid personal intelligence/instructions prompt. The results are night and day in terms of performance.
I don't use Gemini, but I thought `cool, let's give this new model a try`. Opened gemini.google.com, and I'm not even surprised. The drop down gives me the following options: - Flash-Lite - 3.6 Flash [new] - 3.1 Pro The above is why i don't use LLM products from Google. If the model is not available right this minute (heck, hours before the release!), then I'm not gonna bother getting back to it tomorrow, because tom…
So frustrating and confusing.
Meanwhile Anthropic and OpenAI simply release a model everywhere (Fable on Pro only as a somewhat mild exception).