How Google got its groove back and edged ahead of OpenAI
wsj.com
wsj.com
Maybe on Benchmarks... but I'm forced to use Gemini at work everyday, while I use Opus 4.5 / GPT 5.2 privately every day... and Gemini is just lacking so much wit, creativity and multi-step problem solving skills compared to Opus.
Not to mention that Gemini CLI is a pain to use - after getting used to the smoothness of Claude Code.
Am I alone with this?
Model may be the same but the agent on aistudio makes it much better when it comes to generating code.
Still jules.google.com is far behind in terms of actual coding agents which you can run in command line.
Google as always has over engineered their stuff to make it confusing for end users.
But, after using Claude Code with Opus 4.5, it's IMHO not worth it anymore. I mean it IS competitive, but the experience of Claude Code is so nice and it slightly edges out Gemini in coding even. If gemini cli were as nice as claude code, I'd have never subscribed to the claude max plan though.
I was paying for storage and its included.
You likely have access too depending in your account.
Most users on it are using it free, and they almost certainly give free users bottom priority/worst compute allocation.
But hey, it's cheapish, and competition is competition
ChatGPT has been atrocious for me over the past year, as in its actual performance has deteriorated. Gemini has improved with time. As for the comment about lacking wit, I mean, sure I guess, but I use AI to either help me write code to save me time or to give me information - I expect wit out of actual humans. That shit just annoys me with AI, and neither ChatGPT nor Gemini bots are good at not being obnoxious with metaphors and floral speech.
Is using these same models but with GitHub Copilot or Replit equally capable as / comparable to using the respective first-party CLIs?
I too have found Codex better than Copilot, even for simple tasks. But I don't have the same models available since my work limits the models in copilot to the stupid ones.
Maybe there's more going on at inference time with Claude Code cli?
I do think it is not as bad as it was 4-6 months ago. Still not as good as CC for agentic workflows.
So, why does it feel all so fragile and like a gacha game?
I feel like its been trained only tiktok content and youtube cooking or makeup podcasts in the sense that it tries to be super casual and easy-going to the point where its completely unable to give you actual information.
still early but happy to share: tla[at]lexander[dot]com if interested (saw your email in bio)
happy to share if anyone wants to try it
So every single time I (forget and) voice prompt chatGPT it starts by saying "OK, I'll get straight to the point and answer your question without fluff" or something similar. ie it wastes my time even more than it would normally.
No idea which version of their models I was using.
On the other hand, Gemini failed BADLY when I tried to give it a "summarize the data in this CSV" task. Every response was completely wrong. When pressed about which rows the answers were based on, 100% of the rows were made-up, not present in the source file (interestingly, after about 10 rounds of pointing this out, Gemini suddenly started using the actual data from the uploaded file). GPT's answers, on the other hand, matched manual verification with Excel.
That said, I use Opus4.5 for coding through Cursor.
Gemini is for planning / rubber ducking / analysis / search.
I seriously find it a LOT better for these things.
ChatGPT has this issue where when it's doesn't know the explanation for something, it often won't hallucinate outright, but create some long-winded confusing word salad that sounds like it could be right but you can't quite tell.
Gemini mostly doesn't do that and just gives solid scientifically/ technically grounded explanations with sources much of the time.
That said it's a bit of a double edged sword, since it also tends to make confident statements extrapolating from the sources in ways that aren't entirely supported but tend to be plausible.
And then there is pricing too…
I fully switched to Gemini 3 Pro. Looking into an Opus 4.5 subscription too.
My GF on the other side prefers ChatGPT for writing tasks quite a lot (school teacher classes 1-4).
This is just hallucinating.
But then of course you get that at the end of every message instead.
You could also use a uBlock rule I guess.
Gemini often just throws in the towel and goes "yeah, the other one is right", whereas 5.2 will often go "I agree with about 80% of that, but the other 20% I don't, and here's why ..."
And I'm always impressed with the explanation for "here's why" as it picks apart flat out bad output from Gemini.
But, as with everything, this will very much be use-case dependent.
What worked was rebuilding the Ubuntu kernel with a disabled flag enabled, but it took too long to get that far.
Still using Claude Pro / GitHub Copilot subs for general terminal/VS Code access to Claude. I consider them all top-tier models, but I prefer the full IDE UX of Antigravity over the VS Code CC sidebar or CC terminal.
Opus 4.5 is obviously great at all things code, tho a lot of times I prefer Gemini 3 Pro (High) UI's. In the last month I've primarily used it on a Python / Vue project which it excels at, I thought I would've need to switch to Opus at some point if I wasn't happy with a particular implementation, but I haven't yet. Few times it didn't generate the right result was due to prompt misunderstanding which I was able to fix by reprompting.
I'm still using Claude/GPT 5.2 for docs as IMO they have a more sophisticated command over the English language. But for pure coding assistance, I'm a happy Antigravity user.
That said I still use Cursor for work and Antigravity sometimes for building toy projects, they are both good.
It has spec driven development, which in my testing yesterday resulted in a boat load of passing tests but zero useful code.
It first gathers requirements, which are all worded in strange language that somehow don’t capture specific outcomes OR important implementation details.
Then it builds a design file where it comes up with an overly complex architecture, based on the requirements.
Then it comes up with a lengthy set of tasks to accomplish it. It does let you opt out if optional testing, but don’t worry, it still will write a ton of tests.
You click go on each set of tasks, and wait for it to request permissions for odd things like “chmod +x index.ts”.
8 hours and 200+ credits later, you have a monstrosity of Enterprise Grade Fizzbuzz.
I am trying to test bunch of these IDEs this month, but I just cant suffer their planning and have to outsource it.
With SDD the spec should be really well thought about and considered, direct and clear.
- It is too machine like in its definition and requirements and misses the spirit of the ask.
- It very much waterfalls it, without asking for feedback midway, or revisiting the original goals after things have been built. You have such an opportunity to adjust and learn as you go, especially if you keep revisiting your goals and values and re-evaluating your original requirements which may have been flawed.
Just like with human development, it's rare that your spec is well thought out at the beginning, and impossible that it was comprehensive enough to define a working system.
I think having goals, vision, and hard requirements make sense, with some guiding principles along the way, but it's very much a journey that requires constant feedback loops and adjustments along the way.
But I actually find Gemini Pro (not the free one) extremely capable, especially since you can throw any conversation into notebooklm and deep thinking mode to go in depth
Opus is great, especially for coding and writing, but for actual productivity outside of that (e.g. working with PDF, images, screenshots, design stuff like marketing, tshirts, ...,...) I prefer Gemini. It's also the fastest.
Nowhere do I feel like GPT 5.2 is as capable as these two, although admittedly I just stopped using it frequently around november.
This has happened enough times now (I run every query on all 3) that I'm fairly confident that Gemini suits me better now. Whereas it used to be consistently dead last and just plain bad not so long ago. Hence the hype.
Is anyone doing this for high stake questions / research?
The argument against is that the models are fairly 'similar' as outlined in one of the awarded papers from Neurips '25 - https://neurips.cc/virtual/2025/loc/san-diego/poster/121421
I hope you just use the API and can switch easily to any other provider.
I would love to try antigravity out some more, but last I don't think it is out of playground stage yet, and can't be used for anything remotely serious AFAIK.
As for wit, well, not sure how to measure it. I've mainly been messing around with Gemini 3 Pro to see how it can work on Rust codebases, so far. I messed around with some quick'n'dirty web codebases, and I do still think Anthropic has the edge on that. I have no idea where GPT 5.2 excels.
If you could really compare Opus 4.5 and GPT 5.2 directly on your professional work, are you really sure it would work much better than Gemini 3 Pro? i.e. is your professional work comparable to your private usage? I ask this because I've really found LLMs to be extremely variable and spotty, in ways that I think we struggle to really quantify.
Claude Code isn't actually tied to Claude, I've seen people use Claude Code with gpt-oss-120b or Qwen3-30b, why couldn't you use Gemini with Claude Code?
It just feels like OpenAI puts a lot of effort into creating an actually useful product while Gemini just targets benchmarks. Targeting benchmarks to me is meaningless since every model, gpt, Gemini, Claude, constantly hallucinate in real workloads anyways.
Everyone has to find what works for them and the switching cost and evaluation cost are very low.
I see a lot of comments generally with the same pattern “i cancelled my LEADER subscription and switched to COMPETITOR”… reminiscent of astroturf. However I scanned all the posters in this particular thread and the cancellers do seem like legit HN profiles.
Having said that, Google are killing it at the image editing right now. Makes me wonder if that’s because of some library of content and once Anthropocene acquires the same they’ll blow us away there too.
How's the RoI on that?
I go api directly after i hit those limits. That’s where it gets expensive.
Really? Are you using many multiple agents a time? I'm on Microsoft's $40/mo plan and even using Opus 4.5 all day (one agent at a time), I'm not reaching the limit.
I am currently testing different IDEs including Antigravity, and I avoid that model at all cost. I will rather pay to use different model, than use Geminy 3.
It sucks at coding compared to OpenAI and Anthropic models and it is not clearly better as chat-bot (I like the context window). The images are best part of it as it is very steerable and fast.
But WTF? This was supposed to be the OpenAI killer model? Please.
If you hand an iPhone user an Android phone, they will complain that Android is awful and useless. The same is true vice versa.
This is in large part why we get so many conflicting reports of model behavior. As you become more and more familiar with a model, especially if it is in fact a good model, other good models will feel janky and broken.
There needs to be a greater distinction between models used for human chat, programming agents, and software-integration - where at least we benefitted from gemini flash models.
Most of my projects are on GPT at the moment, but we're nowhere too far gone that I can't move to others.
And considering just the general nonsense of Altman vs Musk, I might go to Gemini as a safe harbour (yes, I know how ridiculous that sounds).
So far, I've also noticed less ass-kissing by the Gemini robot ... a good thing.
Are you talking strictly about the respective command line tools as opposed to differences in the models they talk to?
If so, could you list the major pain points of Gemini CLI were Claude Code does better ?
It does need a solid test suite to keep it in check. But you can move very fast if you have well defined small tasks to give it. I have a PRD then breakdown epics, stories and finally the tasks with Pro first. Works very well.
Today, I asked Gemini 3 to find me a power supply with some spec; AC/DC +/- 15V/3A. It did a good job of spec extraction from the PDF datasheets I provided, including looking up how the device performance would degrade using a linear vs switch-mode PSU. But then it comes back with two models from Traco that don't exist, including broken URLs to Mouser. It did suggest running two Meanwell power supplies in series (valid), but 2/3 suggestions were BS. This sort of failure is particularly frustrating because it should be easy and the outputs are also very easy to test against.
Perhaps this is where you need a second agent to verify and report back, so a human doesn't waste the time?
Ah, that explains the silly name for such an impressive tool. I guess it's more a more Googley name than what would have otherwise been chosen: Google Gemini Image Pro Red for Workspace.
Google, OpenAI, and Microsoft all have a very confusing product naming strategy where it’s all lumped under Gemini/ChatGPT/Copilot, and the individual product names are not memorable and really quite obscure. (What does Codex do again?)
Nano Banana doesn’t tell you what the product does, but you sure remember the name. It really rolls off the tongue, and it looks really catchy on social media.
My mom is not gonna use Claude Code, it doesn’t matter to her. We, on Hacker News, don’t represent the general population.
In terms of economic value, coding agents are definitely one of the top-line uses of LLMs.
Coding agents are important, they matter, my comment is that this article isn’t about that, it’s about the other side of the market.
I actually for for ChatGPT and my company pays for Copilot (which is meh).
Edit: Given other community opinions, I don't feel I'm saying anything controversial. I have noted HN readers tend to be overly bullish on it for some reason.
Are you using Claude as an agent in VSCode or via Claude Code, or are you asking questions in the web interface? I find Claude is the best model when it’s working with a strongly typed language with a verbose linter and compiler. It excels with Go and TypeScript in Cursor.
I seriously question any revenue figures that tech companies are reporting right now. Nobody should be believing anything they say at this time. Fraud is rampant and regulation is non-existent.
Whether there's also fraud, misreporting of revenue, or other misbehaviour of weird and wonderful classifications that will keep economics history professors in papers for decades is a separate question. I just find that people get fixated on this one structural feature and I think it's a distraction. It might be smoke, but it's not the fire.
The biggest is FOMO. So many orgs have a principle-agent problem where execs are buying AI for their whole org, regardless of value. This is easier revenue than nickle-and-diming individuals.
The second factor is the circular tech economy. Everyone knows everyone, everyone is buying from everyone, it's the same dollar changing hands back and forth.
Finally, AI coding should be able to produce concrete value. If an AI makes code that compiles and solves a problem it should have some value. By comparison, if your product is _writing_, AI writing is kind of bullshit.
Depends if the cost to weed out the new problems it introduces outweighs the value of the problems solved.
I think LLM writing replacing actual authors or AI "art" is fundamentally worthless though, so at least coding is worth more than "worthless"
I'd have to guess that competition and efficiency gains will reduce the cost of AI coding tools, but for now we've got $100 or $200/mo premium plans for things like Claude Code (although some users may exceed this and pay more), call it $1-2K/yr per developer, and in the US there are apparently about 1M developers, so even with a 100% adoption rate that's only $1-2B revenue spread across all providers for the US market.... a drop in the bucket for a company like Google, and hardly enough to create a sane Price-to-Sales ratio for companies like OpenAI or Anthropic given their sky-high valuations.
Corporate API usage seems to have potential to be higher (not capped by a fixed size user base), but hard to estimate what that might be.
ChatBots don't seem to be viable for long-term revenue, at least not from consumers, since it seems we'll always have things like Google "AI Mode" available for free.
If consumers refuse to pay for it, let alone more than $20 for it, coding agent costs could explode. Agent revenue isn’t nearly enough to keep the system running while simultaneously being very demanding.
I just helped a non-technical friend install one of these coding agents, because its the best way to use an AI model today that can do more than give him answers to questions
The amount of random fucking subscriptions this senile old dude was paying is mind boggling. We're talking nearly $10k/month in random shit. Monthly lingerie subscription? Yup, 62 year old dude. Dick pill subscription? Yup. Subscription to pay his subscriptions? Yup.
It makes me really wonder how much of the US economy is just old senile people paying for shit they don't realize.
We also found millions in random accounts all over the place. It's just mind boggling.
Ouch, that's not nice. My grandmother has been in care since 2020 and no idea who anyone is (forgot kids, husbands, etc), but at least she was in her 90s when it started going bad.
Besides the cost of serving an LLM request - using someone else’s infrastructure and someone else’s search engine is magnitudes higher than a Google search.
Besides defaults matter. Google is the default search engine for every mobile phone outside of China and the three browsers with the most market share
That is obviously because they can't figure out any other value of the product that's sellable.
That’s why you see people here mention Claude Code or other CLI where Gemini has always fallen short. Because to us, we see more than a 5% difference between these models and switching between these models is easy if you’re using a CLI.
It’s also why this article is generated hype. If Gemini was really giving the average consumer better answers, people would be switching from ChatGPT to Gemini but that’s not happening.
If it is so clear, then investors will want to pull their money out.
It's not about who's the best, it's about where the market is. Dogpiling on growing companies is a proven way to make a lot of money, so people do it, and it's accelerated by index funds. The REAL people supporting Google and Nvidia isn't wallstreet, it's your 401K.
That means responses can be far more tailored - it knows what your job is, knows where you go with friends, knows that when you ask about 'dates' you mean romantic relationships and which ones are going well or badly not the fruit, etc.
Eventually when they make it work better, open ai can be your friend and confident, and you wouldn't dump your friend of many years to make another new friend without good reason.
It creeps me out when a past session poisons a current one.
Perhaps it'll be easy to migrate memories indeed (I mean there are already plugins that sort of claim to do it, and it doesn't seem very hard), but it certainly is a very differentiating feature at the moment.
I also use ChatGPT as my daily "chat LLM" because of memory, and, especially, because of the voice chat, which I still feel is miles better than any competition. People say Gemini voice chat is great, but I find it terrible. Maybe I'm on the wrong side of an A/B test.
I get the impression that most non-techies have either never tried "AI", or regard it as Google (search) on steroids for answering questions.
Maybe more related to his (sad but true) senility rather than lack of interest, but I was a bit shocked to see the physicist Roger Penrose interviewed recently by Curt Jaimungal, and when asked if he had tried LLMs/ChatGPT assumed the conversation was about the "stupid lady" (his words) ELIZA (fake chatbot from the 60's), evidentially never having even heard of LLMs!
I didn't tell her to download the app, nor she is a tech-y person, she just did on her own.
The real challenge for Google is going to be using that information in a privacy-conscious way. If this was 2006 and Google was still a darling child that could do no wrong, they'd have already integrated all of that information and tried to sell it as a "magical experience". Now all it'll take is one public slip-up and the media will pounce. I bet this is why they haven't done that integration yet.
Many people slowly open up to an LLM as if they were meeting someone. Sure, they might open up faster or share some morally questionable things earlier on, but there are some things that they hide even from the LLM (like one hides thoughts from oneself, only to then open up to a friend). To know that an LLM knows everything about you will certainly alienate many people, especially because who I am today is very different from who I was five years ago, or two weeks ago when I was mad and acted irrationally.
Google has loads of information, but it knows very little of how I actually think. Of what I feel. Of the memories I cherish. It may know what I should buy, or my interests in general. It may know where I live, my age, my friends, the kind of writing I had ten years ago and have now, and many many other things which are definitely interesting and useful, but don't really amount to knowing me. When people around me say "ChatGPT knows them", this is not what they are talking about at all. (And, in part, it's also because they are making some of it up, sure)
We know a lot about famous people, historical figures. We know their biographies, their struggles, their life story. But they would surely not get the feeling that we "know them" or that we "get them", because that's something they would have to forge together with us, by priming us the right way, or by providing us with their raw, unfiltered thoughts in a dialogue. To truly know someone is to forge a bond with them — to me, no one is known alone, we are all known to each other. I don't think google (or apple, or whomever) can do that without it being born out of a two-way street (user and LLM)[1]. Especially if we then take into account the aforementioned issue that we evolve, our beliefs change, how we feel about the past changes, and others.
[1] But — and I guess sort of contradicting myself — Google could certainly try to grab all my data and forge that conversation and connection. Prompt me with questions about things, and so on. Like a therapist who has suddenly come into possession of all our diaries and whom we slowly, but surely, open up to. Google could definitely intelligently go from the information to the feeling of connection.
Do people want an LLM to "know them"? I literally shuddered at the thought. That sounds like a dystopian hell to me.
But I think Google has, or can infer, a lot more of that data than people realize. If you're on Android you're probably opted into Google Photos, and they can mine a ton of context about you out of there. Certainly infer information about who is important to you, even if you don't realize it yourself. And let's face it, people aren't that unique. It doesn't take much pattern matching to come up with text that looks insightful and deep, but is actually superficial. Look at cold-reading psychics for examples of how trivial it is.
https://cdn.openai.com/pdf/a253471f-8260-40c6-a2cc-aa93fe9f1...
Note that since 2024, Google no longer has your location history on their servers, it's only stored locally: https://www.theguardian.com/technology/article/2024/jun/06/g...
Their 'memory' is mostly unhelpful and gets in the way. At best it saves you from prompting some context, but more often than not it adds so much irrelevant context that it over fits responses so hard that it makes them completely useless, specially in exploratory sessions.
This sounds like first-mover advantage more than a moat.
That may seem minor, but it compounds over time and it's surprising how much ChatGPT knows about me now. I asked ChatGPT to roast me again at the end of last year, and I was a bit taken aback that it had even figured out the broader problem I'm working on and the high level approach I'm taking, something I had never explicitly mentioned. In fact, it even nailed some aspects of my personality that were not obvious at all from the chats.
I'm not saying it's a deep moat, especially for the less frequent users, but it's there.
I’m not saying it’s minor. And one could argue first-mover advantages are a form of moat.
But the advantage is limited to those who have used ChatGPT. For anyone else, it doesn’t apply. That’s different from a moat, which tends to be more fundamental.
For instance, I've been struggling against a specific problem for a very long time, using ChatGPT heavily for exploration. In the roast, it chided me for being eternally in search of elegant perfect solutions instead of shipping something that works at all. But that's because it only sees the targeted chats I've had with it, and not the brute force methods and hacks I've been piling on elsewhere to make progress!
I'd bet with better context it would have been more right. But the surprising thing is what it got right was also not very obvious from the chats. Also for something that has only intermittent existence when prompted, it did display some sense of time passing. I wonder if it noticed the timestamps on our chats?
Notably, that roast evolved into an ad-hoc therapy session and eventually into a technical debugging and product roadmap discussion.
A programmer, researcher, computer vision expert, product manager, therapist, accountability partner, and more all in a package that I'd pay a lot of money if it wasn't available for free. If anything I think the AI revolution is rather underplayed.
Branding isn't a moat when, as far as the mass market is concerned, you are 2 years old.
Branding is a moat when you're IBM, Microsoft (and more recently) Google, Meta, etc.
In the onboarding flow, I can ask you, "Do you use another LLM?" If so, give it this prompt and then give me the memory file that outputs.
The harnessing in Google's agentic IDE (Antigravity) is pretty great - the output quality is indistinguishable between Opus 4.5 and Gemini 3 for my use cases[1]
1. I tend to give detailed requirements for small-to-medium sized tasks (T-shirt sizing). YMMV on larger, less detailed tasks.
I don't know how much secret sauce is in CC vs the underlying model, but I would need a lot of convincing to even bother with Gemini CLI again.
Claude Code is much better than Gemini CLI though.
Gemini 3 feels like Google’s “Windows 3 / IE4 moment”: not necessarily everyone’s favorite yet, but finally solid enough that the default placement starts to matter.
If you are the incumbent you don't need to be all that much better. Just good enough and you win by default. We'll all end up with Gemini 6 (IE 6, Windows XP) and then we'll have something to complain about.
Here is a report (whether true or not) of it happening:
https://www.reddit.com/r/GeminiAI/comments/1q6ecwy/gemini_30...
Google can afford to run Gemini for a looong time without any ads, while OpenAI needs necessarily to bring in some revenue: So OpenAI will have to do something (or they believe they can raise money infinitely)
Google can easily give Gemini without Ads to the users for the next 3 - 4 years, forcing OpenAI to cripple their product earlier with Ads because of the need for any revenue
I think Google & Antropic will be one of the two winners; not sure about OpenAI, Perplexity & Co - maybe OpenAI will somehow merge with Microsoft?
How long will they do it? Id expect investors to roar up some day? Will MS fund them infinitely just for sake of "staying in the game"? According to the public numbers of users, investments, scale etc., OpenAI will need huge amounts of money in the next years, not just "another 10 billion", thats my understanding?
(Unless it is dead if we could see DAUs…)
Yeah sure ChatGPT can spam a bunch of search queries through their search tool but it doesn't really come close to having Perplexity's search graph and index. Their sonar model is also specifically built for search
My most recent experiment:
How many Google CEOs there have been?
Followed by the question
So 3 CEOs for 27 years. How does that number compare to other companies of this size
ChatGPT just completely hallucinates the answer -- 5 Microsoft CEOs over 50 years, 3 Amazon CEOs over 30 years, 2 Meta CEOs over 20 years which are just obviously wrong. You don't need to do a search to know these numbers -- they are definitely in the training dataset (barring the small possibility that there has been a CEO change in the past year in any of these companies, which apparently did not happen)
But Perplexity completely nailed it on first attempt without any additional instructions.
Google has proved it doesn’t want to be the next IBM or Microsoft.
Actually Microsoft has also shown it doesn't want to be the next IBM. I think at this point Apple is the one where I have trouble seeing a long-term plan.
https://lmarena.ai/leaderboard
Google also leads in image-to-video, text-to-video, search, and vision
People are surprised because Google released multiple surprisingly bad products and it was starting to look like they had lost their edge. It’s rare for a company their size to make such a big turnaround so quickly.
Their real mote is the cost efficiency and the ad business. They can (probably) justify the AI spend and stay solvent longer than the market can stay irrational.
The transition to using GPU accelerated algorithms at scale started happening pretty early in Google around 2009/2010 when they started doing stuff with voice and images.
This started with Google just buying a few big GPUs for their R&D and then suddenly appearing as a big customer for NVidia who up to then had no clue that they were going to be an AI company. The internal work on TPUs started around 2013. They deployed the first versions around 2015 and have been iterating on those since then. Interestingly, OpenAI was founded around the same time.
OpenAI has a moat as well in terms of brand recognition and diversified hardware supplier deals and funding. Nvidia is no longer the only game in town and Intel and AMD are in scope as well. Google's TPUs give them a short term advantage but hardware capabilities are becoming a commodity long term. OpenAI and Google need to demonstrate value to end users, not cost optimizations. This is about where the many billions on AI subscription spending is going to go. Google might be catching up, but OpenAI is the clear leader in terms of paid subscriptions.
Google has been chasing different products for the last fifteen years in terms of always trying to catch up with the latest and greatest in terms messaging, social networking, and now AI features. They are doing a lot of copycat products; not a lot of original ones. It's not a safe bet that this will go differently for them this time.
Google is almost an order of magnitude cheaper to serve GenAI compared to ChatGPT. Long term, this will be a big competitive advantage to them. Look at their very generous free tier compared to others. And the products are not subpar, they do compete on quality. OpenAI had the early mover advantage, but it's clear the crowd who is willing to pay for these services, is not very sticky and churn is really high when a new model is release, it's one of the more competitive markets.
Terminal Bench supports my findings, GPT-5.2 and Opus 4.5 are consistently ahead. Only Junie CLI (Jetbrains exclusive) with Gemini 3 Flash scores somewhat close to the others.
It’s also why Ampcode made Gemini the default model and quickly back tracked when all of these issues came to light.
I'm naturally inclined to dislike Google from what they censor, what they consider misinformation, and just, I don't know, some of the projects they run (many good things, but also many dead projects and lying to people)
Antigravity was also painful to use at launch where more queries failed then succeeded, however they've basically solved that now to the point where it's become my most used editor/IDE where I've yet to hit a quota limit, despite only being on the $20/mo plan - even when using Gemini 3 Pro as the default model. I also can't recall seeing any failed service responses after a month of full-time usage. It's not the fastest model, but very happy with its high quality output.
I expected to upgrade to a Claude Code Max plan after leaving Augment Code, but given how good Antigravity is now for its low cost, I've switched to it as my primary full-time coding assistant.
Still paying for GitHub Copilot / Claude Pro for general VS Code and CC terminal usage, but definitely getting the most value of out my Gemini AI Pro sub.
Note this is only for development, docs and other work product. For API usage in products, I primarily lean on the cheaper OSS chinese models, primarily MiniMax 2.1 for tool calling or GLM 4.7/KimiK2/DeepSeek when extra intelligence is needed (at slower perf). Gemini Flash for analyzing Image, Audio & PDFs.
Also find Nano Banana/Pro (Gemini Flash Image) to consistently generate the highest quality images vs GPT 1.5/SDXL,HiDream,Flux,ZImage,Qwen, which apparently my Pro sub includes up to 1000/day for Nano Banana or 100/day for Pro?? [1], so it's hard to justify using anything else.
If Gemini 3 Pro was a bit faster and Flash a bit cheaper (API Usage), I could easily see myself switching to Gemini for everything. If future releases get smarter, faster whilst remaining aggressively priced, in the future - I expect I will.
> kind of surprised it was even offered and marketed given how painful it is to use. I thought it'd have to be damaging to the Gemini brand to get people to try it out, suffer painful UX then immediately stop using it.
is immediately explain by your second point
> Antigravity was also painful to use at launch where more queries failed then succeeded, however they've basically solved that now to the point where it's become my most used editor/IDE
Switching tools is easy right now. Some people pick a tool and stick with it, but it's common to jump from one to the other.
Many of us have the lowest tier subscriptions from a couple companies at the same time so we can jump between tools all the time.
I retried Antigravity a few weeks after launch after Augment Code's new pricing kicked in, and was pleasantly surprised at how reliable it became and how far I got with just the free quota, was happy to upgrade to Pro to keep using it and haven't hit a quota since. I consider it a low tier sub in cost, but enables a high/max tier sub workflow.
I really think people are sleeping on how generous the current limits are. They are going to eat Cursor alive if they keep it this cheap.
The IDE itself remains a buggy mess, however.
Beeing able to use natural processing my mail and calendar make me switch to gemini (app), there’s no way to achieve that with chatgpt (app)
Gemini is now good enough, even if i prefer chatgpt.
I only care about what i can do in the app as paying customer, even if, aside from that, i am working in IT with the SDK openrouter & MCP intégration & whatever RAG & stuff for work
Then there is the CLI; I always got "model is overloaded" errors even after trying weekly for a while. I found Google has this complex priority system; their bigger customers get priority (how much you spend determines queue prio).
Anybody did some serious work with gemini-cli? Is it at Opus level?
It's these kinds of details that cab really set your yet another emulator apart
correct location: https://news.ycombinator.com/item?id=46544042
Wasn't the consensus that 3.0 isn't that great compared to how it benchmarks? I don't even know anymore, I feel I'm going insane.
Gemini 2.5 Pro 3-25 benchmark was by far my favorite model this year, and I noticed an extreme drop off of quality responses around the beginning of May when they pointed that benchmark to a newer version (I didn't even know they did this until I started searching for why the model degraded so much).
I noticed a similar effect with Gemini 3.0: it felt fantastic over the first couple weeks of use, and now the responses I get from it are noticeably more mediocre.
I'm under the impression all of the flagship AI shops do these kinds of quiet changes after a release to save on costs (Anthropic seems like the most honest player in my experience), and Google does it more aggressively than either OpenAI or Anthropic.
If you want stability you go local.
Gemini 3 feels even worse than GPT-4o right now. I dont understand the hype or why OpenAI would need a red alert because of it?
Both Opus 4.5 and GPT-5.2 are much more pleasant to use.
This might be part of what you meant, but I would point out that the supposed underwhelmingness of GPT-5 was itself vibes. Maybe anyone who was expecting AGI was disappointed, but for me GPT-5 was the model that won me away from Claude for coding.
It’s less about it having to be a Google product personally, it just needs to be better, which outside of image editing in Gemini pro 3 image, it is not.
Also they have plenty of money, and talented engineers, and tensor chips, etc.
Doesn't WSJ even blush when publishing these kind of things?
https://www.amediaoperator.com/news/wsj-subs-rise-as-pricing...
Before this gpt nonsense they were such an aspiration for a better world. They quickly turned around, slayer core people from its structure and solely focus on capitalising that they seem to be stuck on dead waters.
I dont see any reasons to use gpt5 at all.
It’s like Microsoft and Internet Explorer in the 90s but on a much larger scale both in the breadth (number of distribution channels) and depth (market share of those channels in their respective verticals).
Google has recently received regulatory pressure, for instance, just like Microsoft had trouble in the late 90s.
In point of fact money to throw at AI development is essentially free, not one of the big players sustains itself on income. Investors are throwing every dollar they have at everyone with a usable pitch.
Whatever advantages Google had, financial stability is way, way down the list. For better theories, look to "Proven Leader at Scaling Datacenters" and "Decoupled from the CUDA Cartel via being an early moving on custom AI hardware".
Google taxes every brand and registered trademark.
The URL bar is no longer a URL bar. It's a search bar. Google used monopoly power to take over 90% of them.
Now every product, every brand, every trademark competes in a competitive bidding process for their own hard-earned IP and market. This isn't just paying a fee, it's a bidding war with multiple sides.
If you want to strike Google at their heart, make it illegal to place ads against registered trademarks.
I'm going to launch "trademark-extortion.org" (or similar) and run a large campaign to reach F500 CEOs and legislators. This needs to end. This is the source that has allowed Google to wreak incredible harm on the entire tech sector. Happy to send this to Sam Altman and Tim Sweeny as well.
[1] Rug-pulling web installs; leveraging 3rd party vendors to establish market share and treating them like cattle; scare walls and defaults that ensure 99.99% of users wind up with ads, Google payment rails, etc. ; Google ads / chrome / search funnel ; killing Microsoft's smartphone by continually gimping YouTube and Google apps on the platform ; etc. etc. etc. The evilest company.
Google isn't exposed in such a way.
Hundreds of billions of dollars are being deflected to a single entity, adding to customer costs.
This turns into a game of who has the bigger ad budget.
Companies can compete on product and win in the court of public opinion. TikTok marketing and reviews showcase this masterfully. Even Reddit reviews.
Yet when you go to search for those things, the Google tax bridge troll steps in and asks for their protection money.
They're a cancer on capitalism and fair competition.
We tell business people it's illegal to perform bribery. Yet that's exactly what this is. It's zero sum multi-party bidding, so it's even more lucrative to the single party receiving the bribes.
Does this apply to [Google, Apple] App Store advertising?
ChatGPT on the other hand was able to reformulate the explanation until I understood the part I was struggling with, namely what prevents a proxy from simply passing its own public key as the website's public key. It did so without citing anything.
Just like the Disney movie, no touchy the Gemini.