u/Pure_Tradition3761

In my experience, it still makes the kind of errors typical of "flash" models. It lies to your face without hesitation and only admits the truth when confronted. For instance, I asked if it had applied a tweak exactly according to the documentation I provided as a reference, and it said yes. Upon testing, I discovered it had taken a lazy approach, using Regex and heuristics; it worked in some cases but failed in most. It only admitted it hadn't done the job correctly after I questioned it.

This is classic behavior for models that devote very little time to thinking and verification. I don't understand why models like this exist. In my opinion, it would be better to focus on a single high-performance model with adjustable "reasoning" levels, or, better yet, a system where the reasoning process automatically adapts to the task at hand. It’s a shame that almost all companies are focusing on the wrong things. I feel there is a need for an intelligent, demand-based routing system. Antigravity and Codex really ought to have this by now.

I notice a worrying trend of Google releasing yet another "Flash" model soon. The main issue is that these models can't beat the 3.1 Pro. The lack of extended reasoning capabilities really holds the Flash models back. Because of this, I would much prefer they release an intermediate model a "3.7 Think," for instance. Since it looks like the 3.5 Pro won't be happening (likely due to a lack of compute power to handle the demand without severely crippling the model after all, the idiots have made Gemini free across almost all their platforms), they should at least launch an intermediate model that offers better stability than the 3.1 Pro. Right now, Gemini models lack stability.

I've been working on a large Python project for about a month and a half now. Initially, I started using GPT 5.5, and then I tested out Grok 4.5 and GPT 5.6. Right around the launch of GPT 5.6, I got stuck on an execution issue that just wouldn't get resolved no matter what. Not even GPT 5.6 sol high could handle it: it could identify the flaw, but wouldn't provide the solution.

That's when I noticed an issue with these ultra-powerful models: they have a tendency to overcomplicate the architecture. In some scenarios, this is highly valuable, but in others, it just gets in the way. After racking my brain for a while, I decided to throw the problem at Gemini, and it actually solved it.

The impression I get is that Gemini acts in the exact opposite way, prioritizing code simplicity. When properly prompted, it keeps things simple, yet remains highly efficient and delivers a great final result.

I see a lot of people here disappointed, thinking Google isn't delivering 'more powerful' models, but you should know that raw power isn't always the best solution. I've been noticing this bad trend of super robust models becoming overly complex and, in practice, less efficient. Have you guys noticed this too?

I don’t exactly hate this “Tech House,” but it really bothers me that 90% of the tracks in this genre have a great build-up and a wonderful pre-drop, but the drop itself lacks energy. It’s way too underwhelming it’s frustrating because of the anticipation the pre-drop builds up. I miss those high-energy sets. I’ll say something I said back in 2022, and I still stand by it: Garrix needs to make some techno or new big room tracks to really set his sets on fire and not just rely on the old ones. He plays the old ones a lot obviously because the crowd loves them but even today, he hasn’t come up with any worthy replacements. Maybe he doesn’t really want to replace the old tracks, but there’s a lack of new material. For comparison, SHM completely changed his style, but some of his new tracks like “Omen” are just as good as “Greyhound” when it comes to setting the set on fire. What do you guys think?

Thx Axwell

This new version is better than the previous ones. The drop from the 2015 version is iconic, almost a classic, but this new version is beautiful, something the other one wasn't quite. The new drop is more melodic, more beautiful. Many here love the others for nostalgia, they've been listening to those versions for over 10 years. It's not a judgment, it just seems that way. It's not so much about quality but about how the music makes you feel. The 2015/16 versions bring a good sense of nostalgia, but in terms of quality, this new one is better, more polished, and much more beautiful. For me, it easily makes it into my top 10 Garrix songs.