201–210 of 699 posts
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…
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…
It's such a weird attitude, especially considering that 1) it's readily available on AI Studio 2) Anthropic models were not always available the moment they got released either. (It also shows that the internet isn't dead. Even people who are not aware of Google AI Studio can express their valuable opinions on LLMs!)
but the webui is currently offering 3.6 flash. the previous model still hasn't actually rolled out to it yet.
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…
Gemini 3.7 is my workhorse - fast and good enough for most tasks. Occasionally I go to GPT Sol or Claude to improve Gemini's output or for more complex tasks, but more than of my work usage is Gemini 3.7. Quite happy to test 3.8 now.
The biggest problem with Gemini is that its performance degrades the longer you use it for coding. Is it just me?
But a good agents.md, starting from a clean slate, and specifying which key files to look into and follow the standards allows me to build gigantic projects even I struggle to keep in my head structurally.
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.
Funnily enough you really do need a great prompting and SKILLS setup to use antigravity effectively in contrast to other providers which actually started benefiting from less detailed prompts over time. But I like it this way, its more customizable and much cheaper especially with a sub.
The reality is that if you optimise a harness for a family of tasks[1], then most of these models give successful output. And there, gemini flash's speed shines.
For general coding assistant, you want it to be well, general, and you use a harness without too much customisation to something specific. Here you need deeply post trained coding assistants and implementors like codex/sol or claude/opus. Gemini flash in its current form will be too happy-go-lucky if you try using it the way we all use codex and is better used in a constrained setting.
tl;dr gemini flash for "LLM-aided workflows in production" is super good today. Cheap as well.
[1] Stuff like this: https://antigravity.google/blog/teamwork-when-ai-becomes-a-r...
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…
But yeah, they really dgaf about gemini.google.com -- I dropped that sub in April when it was clear OAI and Anthropic had lapped them
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.
Crushing it on DeepSWE is a very big deal. Excited to give this a try.
It's clearly been "dealt with" already. When it launched we had interesting gaps and definitely differences. Now every new release is "crushing it".
They're apparently evolving slower than most SOTA models but "slow and steady wins the race" is probably still a thing.
And since Google doesn't depend exclusively on AI models, they can probably afford to "wait and see" where all this craze is heading.
Hopefully before they release 4.0 Flash we will finally get Gemini 3.5 Pro.
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…