Looks like it is already available on VSCode Copilot. Just tried a prompt that was not returning anything good on Sonnet 4.5. (Did not spend much time though, but the prompth was already there on the chat screen so I switched the model and sent it again)
Gemini 3 worked much better and I actually committed the changes that it created. I don't mean its revolutionary or anything but it provided a nice summary of my request and created a decent simple solution. Sonnet had created a bunch of overarching changes that I would not even bother reviewing. Seems nice. Will probably use it for 2 weeks until someone else releases a 1.0001x better model.
Well, I tried a variation of a prompt I was messing with in Flash 2.5 the other day in a thread about AI-coded analog clock faces. Gemini Pro 3 Preview gave me a result far beyond what I saw with Flash 2.5, and got it right in a single shot.[0] I can't say I'm not impressed, even though it's a pretty constrained example. > Please generate an analog clock widget, synchronized to actual system time, with hands that upd…
The subtle "wiggle" animation that the second hand makes after moving doesn't fire when it hits 12. Literally unwatchable.
A nice Easter egg in the Gemini 3 docs [1]: If you are transferring a conversation trace from another model, ... to bypass strict validation in these specific scenarios, populate the field with this specific dummy string: "thoughtSignature": "context_engineering_is_the_way_to_go" [1] https://ai.google.dev/gemini-api/docs/gemini-3?thinking=high...
It's an artifact of the problem that they don't show you the reasoning output but need it for further messages so they save each api conversation on their side and give you a reference number. It sucks from a GDPR compliance perspective as well as in terms of transparent pricing as you have no way to control reasoning trace length (which is billed at the much higher output rate) other than switching between low/high but if the model decides to think longer "low" could result in more tokens used than "high" for a prompt where the model decides not to think that much. "thinking budgets" are now "legacy" and thus while you can constrain output length you cannot constrain cost. Obviously you also cannot optimize your prompts if some red herring makes the LLM get hung up on something irrelevant only to realize this in later thinking steps. This will happen with EVERY SINGLE prompt if it's caused by something in your system prompt. Finding what makes the model go astray can be rather difficult with 15k token system prompts or a multitude of MCP tools, you're basically blinded while trying to optimize a black box. Obviously you can try different variations of different parts of your system prompt or tool descriptions but just because they result in less thinking tokens does not mean they are better if those reasoning steps where actually beneficial (if only in edge cases) this would be immediately apparent upon inspection but hard/impossible to find out without access to the full Chain of Thought. For the uninitiated, the reasons OpenAI started replacing the CoT with summaries, were A. to prevent rapid distillation as they suspected deepSeek to have used for R1 and B. to prevent embarrassment if App users see the CoT and find parts of it objectionable/irrelevant/absurd (reasoning steps that make sense for an LLM do not necessarily look like human reasoning). That's a tradeoff that is great with end-users but terrible for developers. As Open Weights LLMs necessarily output their full reasoning traces the potential to optimize prompts for specific tasks is much greater and will for certain applications certainly outweigh the performance delta to Google/OpenAI.
> The Gemini app surpasses 650 million users per month, more than 70% of our Cloud customers use our AI, 13 million developers have built with our generative models, and that is just a snippet of the impact we’re seeing Not to be a negative nelly, but these numbers are definitely inflated due to Google literally pushing their AI into everything they can, much like M$. Can't even search google without getting an AI re…
This is benefit of bundling, I've been forecasting this for a long time - the only companies who would win the LLM race would be the megacorps bundling their offerings, and at most maybe OAI due to the sheer marketing dominance. For example I don't pay for ChatGPT or Claude, even if they are better at certain tasks or in general. But I have Google One cloud storage sub for my photos and it comes with a Gemini Pro app…
Has anyone who is a regular Opus / GPT5-Codex-High / GPT5 Pro user given this model a workout? Each Google release is accompanied by a lot of devrel marketing that sounds impressive but whenever I put the hours into eval myself it comes up lacking. Would love to hear that it replaces another frontier model for someone who is not already bought into the Gemini ecosystem.
At this point I'm only using google models via Vertex AI for my apps. They have a weird QoS rate limit but in general Gemini has been consistently top tier for everything I've thrown at it.
Anecdotal, but I've also not experienced any regression in Gemini quality where Claude/OpenAI might push iterative updates (or quantized variants for performance) that cause my test bench to fail more often.
Well, I tried a variation of a prompt I was messing with in Flash 2.5 the other day in a thread about AI-coded analog clock faces. Gemini Pro 3 Preview gave me a result far beyond what I saw with Flash 2.5, and got it right in a single shot.[0] I can't say I'm not impressed, even though it's a pretty constrained example. > Please generate an analog clock widget, synchronized to actual system time, with hands that upd…
It looks quite nice, though to nitpick, it has “quartz” and “design & engineering” for no reason.
I've been so happy to see Google wake up. Many can point to a long history of killed products and soured opinions but you can't deny theyve been the great balancing force (often for good) in the industry. - Gmail vs Outlook - Drive vs Word - Android vs iOS - Worklife balance and high pay vs the low salary grind of before. Theyve done heaps for the industry. Im glad to see signs of life. Particularly in their P/E whic…
> Drive vs Word You mean Drive vs OneDrive or, maybe Docs vs Word ?
I'm not a mathematician but I think we underestimate how useful pure mathematics can be to tell whether we are approaching AGI. Can the mathematicians here try ask it to invent new novel math related to [Insert your field of specialization] and see if it comes up with something new and useful? Try lowering the temperature, use SymPy etc.