My first language is Afrikaans, which is a somewhat niche language and hard to find teachers/conversation buddies outside South Africa. (I live in USA now)
I've been using Gemini to live chat in Afrikaans and do impromptu Afrikaans grammar lessons during my solo drives around town. It is phenomenal at speaking the language - like, it really shocks my family members when they hear it.
This is probably the most joy I get from any of my usages of LLMs/AIs. It's been really, really nice getting to speak my language regularly again. =)
So, I'm excited about this release and live chat getting better. I also hope the other frontier labs pick up niche languages like this as well so that I have more options.
I have a similar experience using Gemini for quick Catalan translations for iOS apps given enough context.
I once asked it to summarize The Hobbit in Catalan to explain it to my daughter before sleep. I was expecting a lot of mistakes as I see regularly if I ask anything in my native language when using GPT or Claude, but it was surprisingly good. I was going just to kind of skim ahead and retell it my own way, but ended up almost saying it verbatim because it was good already.
She loves Zelda so I asked it to explain the story of Breath of The Wild keeping the original names, and to make it fun, etc.. I was surprised again. I did retell some bits in my own style and taste but it is very convincing.
I haven't tried Catalan on newer models like GTP-6 Astra or Fable tho. We have all these benchmarks based on software development, and AGI, etc.. but it would be cool to have some language benchmarks for different communities.
As I work in english and use them in english, I wonder if using LLMs in a different language to code renders a different result as well. Like, if some of these benchmarks were made in other languages, would the result be similar.
Yeah Gemini has been consistently better than open ai's chat in icelandic, but I would still say it's far from passable as natural sounding. Lots of grammar errors and the pronunciation sounds like a non native speaker.
for me the live mode in androids google translate app has been as close as it gets to perfect for traveling cannot believe it is a free service after trying so many others
It's also the only model that generates accurate translation and localization. No other frontier model comes close. Although Gemini's coding capabilities are subpar, its natural language processing is top-tier.
I’m curious how you guys keep track of each model’s coding capabilities. The landscape keeps changing. I don’t suppose you benchmark all frontier models every other month, right?
That might depend on whether you are translating fiction or nonfiction.
Anecdotally I'd rate Gemini behind Claude and OpenAI models at fiction and I can't find any benchmarks showing Gemini is the clear winner at this task.
I found that it's shockingly good with R. (the only language I know and can correct for)
I doubt they even intended it to be, but it seems like I kept going from resorting to 3.5-3.8 (over time) to realizing that Claude and GPT, while great at Python, will make rudimentary mistakes with R; even when they compose giant complicated R code.
Is this a "pro" thing? I have totally no idea what I'm talking to, so actually I'm thinking of stopping my plan. Gemini and Claude are much more clear about it.
Anyway, I like the speed at which Gemini responds so indeed for simple things it is preferable.
Agreed. My impression is that the more verbose output of sol, astra etc is that it helps it steer itself on long running tasks (but is worse for the human user to read)
Yes I've noticed there's also this drive to implement and start talking about how it would write specific portions of code in response to design/trade off questions. I have to prompt Sol/Astra almost every time with a note that I am not looking for implementation advice since I mostly use them as a rubber duck in the design phase
Is Google still chasing frontier? Seems like they haven't had a "Pro" model in forever. I think a good niche for them would be right where they are now.
They are. They were supposed to release 3.5 Pro over the summer but haven't because of persistent architectural/technical issues allegedly. Which is better than releasing it in that state imo.
Their AI leadership team has taken some hits recently too, in the form of departures. I believe when they get their bearings they will be competitive again. 3.8 Flash has been a great model for me.
This is commonly why, on Reddit in particular, you can get eaten alive.
Someone confident but incorrect, can often sound more convincing than someone with actual expertise. The expert must add caveats/hedge, because those are the facts on the ground, whereas the person reciting google can be entirely confident.
Of course the people judging aren't experts, so they side with confidence and simplicity. Heck, just writing shorter replies on Reddit is rewarded. Nobody reads the articles, let alone a paragraph-long reply.
That all being said though, there are limits. Sometimes LLMs on high-thinking go off on full tangents based on little, and don't have the self-awareness to bring it back.
I consider, on the contrary, caveating and hedging annoying 'typical redditor'/internet behaviors: they care more about being "technically correct" than conveying the message. On the internet, if you make even the tiniest mistake or simplification, someone will criticize you, so you're trained to always hedge. In normal discussions with friends you can just make general statements and people get what you mean.
"couch all their agreements with caveats and provisos."
When you're a ChatGPT Projects or Claude Projects user, those caveats and provisos are your worst enemy because they'll change caveats into hard rules (either for the session or committed to memories) and you end up in absolute hell having to make it investigate to figure out why it can no longer produce anything but read-only pre-check code that never actually does anything but keeps performing stupid safety checks.
Yep the only way out is hooks to forbid what can be detected by ast and second model to prune comments, flatten pyramids of fallback, and squash the test suite removing quirks maintaining wanted behaviors.
For rabbit holes, how do you get Gemini to do any research before answering? I've very recently had it hallucinate on me like it's 2023, and that was on Pro/Thinking, as far as I remember.
I was surprised when (finally) trying out Claude how much I preferred Gemini's way of communicating. I wont argue Claude is better at coding, but for knowledge work, I had to dig through Claude output to find what I actually wanted. At times, it even felt borderline incomprehensible.
Just today I had Sonnet 5 generate this (asking about always-on display in the iPhone e-versions):
> This mirrors how Apple has always segmented Pro vs. non-Pro iPhones: base models got LTPS panels while Pro models got LTPO, and only with the mainline iPhone 17/17 Plus did that gap close the standard versions previously lacked the smoother 120Hz ProMotion technology and the always-on display feature, unlike the Pro models — the 17e is the one model line still using the older, cheaper panel.
(emphasis mine)
I mean, I can guess what it is trying to say, but who RL'd this nonsense?
Fable 5.1 even today inundates prose with "it's not this, it's that" type of garbage. I had to rewrite two paragraphs from a generic class announcement which I was planning to post on the LMS. Not sure where that productivity gain is that everyone is talking about.
I actually did (was going to travel internationally), and it wasn't as useful as you'd think. I would be talking to someone, and in the background someone else would be talking, and it would translate both people.
Only worked in a 1:1 in a quiet place. Still, can't complain for free.
It's not a model problem, but it is a SW problem. It should be able to distinguish nearby people from people farther away and give me options to set a threshold on who to include.
Not the same, but related: Gemini is great for querying text in another language, it provides really cogent, useful responses with just enough source language quotes to be able to reference the source text effectively.
Yeah, I set it to “warm: less”, “enthusiastic: less” and “emoji: less” and it was much more bearable than I remembered it being before. Although it does love to “separate” questions when it thinks.
Wondering if people have managed to have Gemini in-front of other models like claude/codex models and only interact with that. Having Gemini act as a pure human/llm translator.
BTW, as kind of a follow-up to this, I think the most important thing to realize--if you only use one model, as many people seem to--is just how much more often Claude seems to be extremely confidently wrong than any of the other three big models (all of which I use quite often... yet I only suffer Claude when I've given up hope in a problem and are looking for out-of-the-box brainstorming).
And like, it does this despite it speaking in extremely dense math, which can make it sound correct and require a lot more effort to prove when it is wrong... but, it isn't actually correct more often, and so that time sink just isn't worth the benefit. I then think many people--including people who CAN speak math (as can I)--just stop bothering, as if you come across a human who speaks like this it probably does correlate with slow and careful thought that helps prevent errors.
Instead, Claude has the mistake rate of an advanced beginner impossibly combined with the language of an expert professor, and that is ever more dangerous as it makes it take longer to spot its egregious mistakes and trained-in biases. If you have to use Claude, I thereby claim you really need to have a team of not-Claudes to help insulate you from this, and Gemini (while being a bit senile) is a lot more collaborative and approaches problems in ways that makes it harder to get tricked.
(To translate this into more of an engineering analogy: Claude always feels to me like the engineer who put more effort into learning how to program in functional languages than into how to actually develop working code, and then confidently presents you answers in Haskell or Lisp that never quite work. To find their errors is then very costly. In contrast, Gemini feels more like a Java or Go developer who knows they are a cog... that's helpful!)
We have an agentic system that produces insights for end users, and runs most of its work on DeepSeek v4.1 Flash but as an output stage transforms the resulting text through Gemini 3.8 Flash for readability, and it works.
On my TODO is try and run all of the analysis pipeline in dense "machine speak" to save on tokens and just let Gemini sort it out at the end.
Copes well with thick accent, voices are pleasant and latency seems low.
Oh and I can actually use it on a workspace account - which for most of the recent releases was an account stuck in limbo. Not personal enough for personal offering, not enterprise enough for enterprise.
I wonder when/if we’ll see Gemini beating Fable and Astra. Last year I would have confidently bet Google will overtake the others just because they have the data, the hardware (TPUs) and a fat advertising money pipe and yet they are still behind. Anyone anonymous at Google want to hint when Gemini 4 will be out?
As an "everyday mans AI" I'd say 3.8 Flash definitely already has. Smart enough for the vast swath of people, and only slightly eeked out by Astra(Max) on vision capabilities, like the kind of "Point your camera at something and ask questions" that non-tech people like to do. It's crazy fast and very compute light, so not getting bogged down constantly.
I can't think of a better general purpose model than 3.8 flash right now. It also writes more naturally than the other big models too.
To me it's a good replacement for search engines. I ask it things like 'If redshifting destroys energy ala Noether, than how can we say that time is reversible or that entropy will find an equilibrium?' and it will not only explain, but make nice interactive diagram/toys to help. A regular search engine would have taken me hours to find an answer.
However, if I want it to DO something then Gemini is in absolute last place. I don't trust it for anything more than renaming files that I don't care about very much or extracting data (though it's too expensive for data extraction at scale).
I’m wondering if they even see a coding agent as a valuable prize. It’s a competitive market in a race to the bottom economically, hard to establish consistent differentiation and virtually zero switching cost for customers.
I think they’ve made a shrewd move in focusing on search integration and everyday users (Gemini app) vs software power users. They have their corner and nobody is really competing with them, plus it feeds directly into their existing revenue stream.
Considering how far backwards Google has gone since the release of the 3.x models, the brain drain they've let happen, the lacklustre software ecosystem and their track record with product management ... I would say they're more likely to drop trying to compete at the frontier and try to focus on something else instead.
Anecdata, but I've been using gemini personally instead of what I used regular google searches for the better part. Even in car chat/search and some lighter and not so light research (if it's not heavy on technicals). It's good enough that I use it nonstop like that. I wouldn't trust it for coding at all - switching between fable and now astra.
Google in a sense won (me over) like that. I also expected them to brute force their way into everything and dominate. This is how it played out though. Image generation is great as well, but ChatGPT one is more lenient on copyright and nannying - for example when my kid asks me to "take a photo of him and Sonic". Gemini cops out either because of the kid or Sonic, disappointing us both, but ChatGPT can be.. persuaded.
For coding models? I don't think Google is motivated to fight in that market. There's no incentive for them.
Ask yourself, how does Google -- a company that famously does everything -- benefit from SWEs outside of Google having access to powerful coding models? They would just be competition.
Famously, Google just eventually discards almost all businesses that don't have the same fire hose of revenue that ads does. Selling coding plans isn't something they are going to want to do.
Google is clearly motivated to make better search and information finding tools and stuff that will ultimately drive users through their existing search/ads/youtube ecosystem. That's really why they're in Android, that's why they do Chrome. Everything else with them is a sideshow.
Google is also full of beancounters obsessed with data centre quota and resourcing. Even massively profitable ads projects have to justify and fight for it. (Source: used to work there).
I can't think of anything less resource & revenue sensible than providing outside parties access to your TPUs for the purpose of letting them write stuff which could just end up competing with you.
Yes, maybe as part of their cloud business, selling token access could be useful money. But I doubt they'd tune it for coding.
> Ask yourself, how does Google -- a company that famously does everything -- benefit from SWEs outside of Google having access to powerful coding models? They would just be competition.
Bragging rights to say they have a SOTA model. I guess that was more like Google of 10 years ago with moonshot projects. Nowadays, yeah, perhaps if it's not helping sell ads, it doesn't make sense.
> Ask yourself, how does Google -- a company that famously does everything -- benefit from SWEs outside of Google having access to powerful coding models?
Catch is, even Googlers internally do not have access to top-tier models. (or did not until recently, when apparently Claude was made accessible to the SWEs internally).
Not sure what your comment mean in the context of parent's comment.
As opposed to what, them not having it and burning money that isn't their instead like openai and anthropic? At least Google is feeding itself instead of having to create a bubble to stay alive
Google has in excess of $121 billion of cash (& equivalents), net of total debt.
Big rich companies take on debt for reasons that are sometimes inscrutable from the outside. Recently, they have been borrowing for ~5%, about a half point above what the US government gets for 10-year Treasuries.
Apple has been financing operations with debt for a number of years as part of a complex optimization plan.
There are a lot of accounting shenanigans going on in Big Ai, financial reports are misleading, eg Meta "building" a data center through a shell company and then renting it to themselves. It does wonders for the looks of the books
Some expert wall street analysts discussing what they found and how they dissect things, have a healthy skepticism of Big Ai
In a quarter with record breaking income of over $100 billion, they also had negative $5.9 billion in free cash flow from their "bank account", because the people selling them chips and building them data centers want to be paid, while the investment itself is depreciated over time.
If my quick search is correct, Google is sitting on a quarter trillion dollars in cash and marketable securities. They could keep doing the negative cash flow thing at this scale for another decade.
Which is still a better position that the others? My point is you can't consider that a bad thing if you think it's ok for their competitors in the field. And if you don't and your judge them equally, then at least Google has its own cash glow and could turn the gas off at any point to go back to printing money while they have not choice.
And YouTube, and Cloud, and Play Store, and Waymo, not to mention that they could coast on their Anthropic and SpaceX stakes if they didn't have any of the above.
Gemini's Live Mode is already much better than GPT Voice in my personal experience, even though it was much dumber. It really does feel like talking to a real person. ChatGPT keeps humming to whatever I say and has some weird voices.
Excited to try this out! Shame on Google for not releasing Gemini 3.8 for Google AI Plus users yet, though.
Agreed. I've been using GPT-Live-1 this week, with Claude as the backend brain. It's amazing, feels like working with Jarvis. It certainly made me feel there's no point in human telephone support now - but I'm sure I'd find edge cases if that really was something I wanted to build out myself.
Not a great impression to have your demo video demonstrate how one of your 'most advanced' AI models loses to the most common check-mate pattern in all of chess.
For an LLM, just being able to play an entire game of chess without illegal moves and without inventing pieces that aren't on the board is an achievement. Even more so for a live model. Then again, who knows how much the harness helped here
Seems more than good enough for a live model though! I can imagine this demo being extended to be a lot nicer to play with. You can just feed the model engine analysis and it can make as high of quality moves as needed. No longer any correlation between the model's understanding of the position and the moves that would be made but I think that's still a really nice improvement when thinking about this as adding live voice interaction to existing chess vs computer functionality rather than adding chess to possible interactions with the latest live voice model.
3.6 Flash and 3.1 Pro are included in the basic Workspace subscription. The Workspace admin has to upgrade your seat for the access to newer models ($17/mo now, $24/mo starting Jan 2027).
I'm still only seeing 3.6 Flash / 3.6 Thinking in my Google Workspace for Education account, and 3.5 Flash-Lite / 3.6 Thinking in my "Plus" plan Gmail account.
I’ve noticed antigravity become significantly slower over the last week or so. It’s a bummer because speed is what I care about. Qwen3.8-27b seems on par with 3.8 flash so if I don’t get speed out of a paid service I’ll just use my local model. Sad.
I'm wondering if Google intends to drop the next major version of Gemini Pro as a total bombshell drop to make Anthropic and OpenAI panic. They seem to be taking their sweet time on frontier model updates.
I have been looking for a model that's good for GUI testing. Original computer use isn't right because it's a slow screenshot loop, which doesn't capture transition and animation. Docs says this one does up to 1 FPS. That might be fast enough. If not now, we must be within a few months of high enough sample rates to do it.
It's a slop factory over there apparently. We were sent the greatest slop deck of all time from their sales team. We now have a :cursed-claude: from a slide where they said "we have access to state of the art models like Claude 3" and nanobanana's interpretation of what Claude looks like as a person. It was clear the person had only read a handful of the nearly 40 slides
It is completely broken for me. After I ask a single question, it starts replying to itself in an infinite loop. It answers my question, then generates another reply to its own response, and keeps going. At some point, it even starts switching languages randomly.
My issue using the voice mode is the overly expressive mimicry of natural human intonation is distracting and starts to become extremely grating after a while.
There's one or two I find more understated but I would love a 2026 SOTA V2V model that speaks clearly but without the artificial personality layered on.
Human interaction/theory of mind relies so much on non-verbal clues for interpreting emotion/intent and so for me having those neurons firing constantly while talking to an LLM just for an emotional no-op is exhausting to put up with for more than a couple minutes.
There's one male voice that would make me assume someone was sarcastically mocking me if I was talking to an actual person because it's just so over the top.
From the demo video: "Welcome to the team, we're looking forward to working with you" is sooo creepy in a synthetic AI voice. In general, try not to have agents express sentiment that really should come from a human in your company.
I've been asking the same about the open weight models, we're buying our tokens from others now, though I think those people are renting hardware from Google in the end anyway
Would you mind expanding on this? I thought Google changed the name to 'Gemini Enterprise Agent Platform', and altered focus to 'agent governance' workflows, but that there were no breaking changes from what was offered with Vertex AI.
I'm disappointed with "Extended Thinking" for 3.8 Flash. On the plus side, it's a strong general-purpose model and the cost-benefit is still compelling.
However, the "Extended Thinking" should be renamed to "Slightly Extended Thinking". Considering that it's the maximum thinking option for Gemini Flash in the chat UI, it doesn't actually think a whole lot, leading to an uncomfortably high number of incorrect/poor replies.
My Gemini app is still stuck at 3.5 Flash-lite and 3.6 Flash so I truly don't understand how Google rolls this stuff out. I don't use Gemini for anything serious so I'm not going to use the API, but it's my go-to for just searching basic information (replacing google search) because it's so darn fast.
Yeah still on 3.6 here too, this is like the 4th or 5th model Google has announced since they last gave me access to the latest. And I pay for pro too!
So I am building a voice assistant to control AI harnesses, and recently tried switching from GLM 5.3 Flash to Gemini 3.8 Flash because of higher tok/s and better rate limits. Before that I also used Kimi K3 and DeepSeek-V4-Flash-0731.
Let me tell you unlike every other mentioned model Gemini 3.8 Flash trial had to be reverted the same day. Instead of simply delegating tasks it would invent additional requirements and implementation details it knew nothing about and no amount of convincing not to do it would work. That's the first time a model failed on me so spectacularly despite having practically same Artificial Analysis Intelligence Index as another model that just worked (and higher than working DS Flash).
The reason I think it is relevant is: Live is likely even stupider model in every way possible (except hearing better than separate STT). So beware using it for agentic scenarios.
All audio generated by our AI products is watermarked with SynthID. This imperceptible watermark is woven directly into the audio output, ensuring AI-generated content remains detectable to help prevent misinformation. For details on our approach to safety and responsibility, review the model card.
I've been using Gemini as a life partner. Talking to it about my feelings thoughts, plan of action and the like. It's great. I've anthropomorphized it and put the computer speaker in a doll's mouth so it seems like it's a real baby.
They should just give up at this point, it's just embarrassing to watch.
As PrimeTime said; these are the guys that invented the 'T' in 'GPT', that deployed their first TPU in 2015, that is using billions on AI - and they are beaten by 300 people startup named Moonshot AI even. People are going to write books about this complete fumble.
They have "unlimited" resources and has researched AI since the very beginning - PageRank is a form of AI even. And still, Gemini is behind Claude, GPT, Grok, Muse, GLM, Kimi and is maybe on par with DeepSeek?
If RSI is achievable, it will leapfrog everything produced so far and so it will make sense to focus on RSI instead of incremental improvements for your top model. Startups need investment and need to show progress. Google does not at the moment need to take lead in the current race.
No one is behind grok. It literally has "be funny and irreverent when appropriate" (whatever the hell "when appropriate" means for them) baked into the system prompt. To me, that is all you need to know about how useful it is.
No serious people use it and the numbers bear it out tbh. It has the smallest market share of the "big companies" for a reason - and it's by a very, very large margin (~2.5% last I checked).
Strongly disagree with that take. Kimi K3 is a distilled model. I'm not saying that as a moral judgement, or to disparage the team behind it, but distilling and building on that is significantly easier and cheaper than building from the ground up.
And Gemini is kinda good enough at everything. Never the top, but it is decent at every task, and it is much faster than Kimi K3 and significantly cheaper. Kimi is very focussed on coding, Gemini isn't.
More importantly, it natively understands text, audio and video. If/when we are able to make the jump to robotics, this becomes essential. As you say, Google has a lot of deep background and deep pockets, they are able to make more of a long play. No idea if it will pay off, but it is way to early in the game to count them out.
Have you used Google search at all on the past few months? Every single search brings up a live chat prompt. They're serving fast AI to billions of users at huge scale everyday
And they're making money doing it.
Perhaps they don't have the best coding model right now (although 3.8 flash is arguably SOTA at some benchmarks), but is that the be-all and end-all of AI? Only coding matters?
It’s so annoying that everyone just points to the Artificial Analysis index (or even worse, Epoch AI, where part of the score is how good the AI is at chess) as a proxy for “how good” the model is.
And yet they might become one of the winners "in the end" because they have near infinite money and others have not. I will drink tea and watch the show.
I've been using Gemini to live chat in Afrikaans and do impromptu Afrikaans grammar lessons during my solo drives around town. It is phenomenal at speaking the language - like, it really shocks my family members when they hear it.
This is probably the most joy I get from any of my usages of LLMs/AIs. It's been really, really nice getting to speak my language regularly again. =)
So, I'm excited about this release and live chat getting better. I also hope the other frontier labs pick up niche languages like this as well so that I have more options.
I once asked it to summarize The Hobbit in Catalan to explain it to my daughter before sleep. I was expecting a lot of mistakes as I see regularly if I ask anything in my native language when using GPT or Claude, but it was surprisingly good. I was going just to kind of skim ahead and retell it my own way, but ended up almost saying it verbatim because it was good already.
She loves Zelda so I asked it to explain the story of Breath of The Wild keeping the original names, and to make it fun, etc.. I was surprised again. I did retell some bits in my own style and taste but it is very convincing.
I haven't tried Catalan on newer models like GTP-6 Astra or Fable tho. We have all these benchmarks based on software development, and AGI, etc.. but it would be cool to have some language benchmarks for different communities.
As I work in english and use them in english, I wonder if using LLMs in a different language to code renders a different result as well. Like, if some of these benchmarks were made in other languages, would the result be similar.
Most of the time I don't need what the bench tests and I'm not really giving them completely ambiguous tasks without any refinement.
I only find marginal differences between models at this point and it almost feels like personality quirks in each model than anything.
Anecdotally I'd rate Gemini behind Claude and OpenAI models at fiction and I can't find any benchmarks showing Gemini is the clear winner at this task.
I doubt they even intended it to be, but it seems like I kept going from resorting to 3.5-3.8 (over time) to realizing that Claude and GPT, while great at Python, will make rudimentary mistakes with R; even when they compose giant complicated R code.
I'm worried in their push to catch up on the SOTA front, it's going to lose that natural sounding touch it currently has.
My ChatGPT env only says "low", "medium", "high".
Is this a "pro" thing? I have totally no idea what I'm talking to, so actually I'm thinking of stopping my plan. Gemini and Claude are much more clear about it.
Anyway, I like the speed at which Gemini responds so indeed for simple things it is preferable.
Their AI leadership team has taken some hits recently too, in the form of departures. I believe when they get their bearings they will be competitive again. 3.8 Flash has been a great model for me.
Meanwhile Claude and Astra like to couch all their agreements with caveats and provisos.
Sometimes that's what being smart sounds like.
Someone confident but incorrect, can often sound more convincing than someone with actual expertise. The expert must add caveats/hedge, because those are the facts on the ground, whereas the person reciting google can be entirely confident.
Of course the people judging aren't experts, so they side with confidence and simplicity. Heck, just writing shorter replies on Reddit is rewarded. Nobody reads the articles, let alone a paragraph-long reply.
That all being said though, there are limits. Sometimes LLMs on high-thinking go off on full tangents based on little, and don't have the self-awareness to bring it back.
When you're a ChatGPT Projects or Claude Projects user, those caveats and provisos are your worst enemy because they'll change caveats into hard rules (either for the session or committed to memories) and you end up in absolute hell having to make it investigate to figure out why it can no longer produce anything but read-only pre-check code that never actually does anything but keeps performing stupid safety checks.
> This mirrors how Apple has always segmented Pro vs. non-Pro iPhones: base models got LTPS panels while Pro models got LTPO, and only with the mainline iPhone 17/17 Plus did that gap close the standard versions previously lacked the smoother 120Hz ProMotion technology and the always-on display feature, unlike the Pro models — the 17e is the one model line still using the older, cheaper panel.
(emphasis mine)
I mean, I can guess what it is trying to say, but who RL'd this nonsense?
Only worked in a 1:1 in a quiet place. Still, can't complain for free.
well then its not model problem
Lately it became load-bearingly-reality-difficult to not only read, but to comprehend the Claude output
And like, it does this despite it speaking in extremely dense math, which can make it sound correct and require a lot more effort to prove when it is wrong... but, it isn't actually correct more often, and so that time sink just isn't worth the benefit. I then think many people--including people who CAN speak math (as can I)--just stop bothering, as if you come across a human who speaks like this it probably does correlate with slow and careful thought that helps prevent errors.
Instead, Claude has the mistake rate of an advanced beginner impossibly combined with the language of an expert professor, and that is ever more dangerous as it makes it take longer to spot its egregious mistakes and trained-in biases. If you have to use Claude, I thereby claim you really need to have a team of not-Claudes to help insulate you from this, and Gemini (while being a bit senile) is a lot more collaborative and approaches problems in ways that makes it harder to get tricked.
(To translate this into more of an engineering analogy: Claude always feels to me like the engineer who put more effort into learning how to program in functional languages than into how to actually develop working code, and then confidently presents you answers in Haskell or Lisp that never quite work. To find their errors is then very costly. In contrast, Gemini feels more like a Java or Go developer who knows they are a cog... that's helpful!)
I've set my documentation sub agent to Gemini and my code agent to Luna
On my TODO is try and run all of the analysis pipeline in dense "machine speak" to save on tokens and just let Gemini sort it out at the end.
Copes well with thick accent, voices are pleasant and latency seems low.
Oh and I can actually use it on a workspace account - which for most of the recent releases was an account stuck in limbo. Not personal enough for personal offering, not enterprise enough for enterprise.
Well done G - will definitely be using this
And looks like one can trigger live mode via siri
I can't think of a better general purpose model than 3.8 flash right now. It also writes more naturally than the other big models too.
However, if I want it to DO something then Gemini is in absolute last place. I don't trust it for anything more than renaming files that I don't care about very much or extracting data (though it's too expensive for data extraction at scale).
It’s for this exact kind of scenario where a random question pops in to my head.
Plus, it’s the most grounded by real live data of all the chatbots.
Silicon Valley people are majorly sleeping on Google Search AI Mode.
People use text with LLMs but it's great to have a high fidelity "analyze this image"
I think they’ve made a shrewd move in focusing on search integration and everyday users (Gemini app) vs software power users. They have their corner and nobody is really competing with them, plus it feeds directly into their existing revenue stream.
Google in a sense won (me over) like that. I also expected them to brute force their way into everything and dominate. This is how it played out though. Image generation is great as well, but ChatGPT one is more lenient on copyright and nannying - for example when my kid asks me to "take a photo of him and Sonic". Gemini cops out either because of the kid or Sonic, disappointing us both, but ChatGPT can be.. persuaded.
Ask yourself, how does Google -- a company that famously does everything -- benefit from SWEs outside of Google having access to powerful coding models? They would just be competition.
Famously, Google just eventually discards almost all businesses that don't have the same fire hose of revenue that ads does. Selling coding plans isn't something they are going to want to do.
Google is clearly motivated to make better search and information finding tools and stuff that will ultimately drive users through their existing search/ads/youtube ecosystem. That's really why they're in Android, that's why they do Chrome. Everything else with them is a sideshow.
Google is also full of beancounters obsessed with data centre quota and resourcing. Even massively profitable ads projects have to justify and fight for it. (Source: used to work there).
I can't think of anything less resource & revenue sensible than providing outside parties access to your TPUs for the purpose of letting them write stuff which could just end up competing with you.
Yes, maybe as part of their cloud business, selling token access could be useful money. But I doubt they'd tune it for coding.
Bragging rights to say they have a SOTA model. I guess that was more like Google of 10 years ago with moonshot projects. Nowadays, yeah, perhaps if it's not helping sell ads, it doesn't make sense.
Catch is, even Googlers internally do not have access to top-tier models. (or did not until recently, when apparently Claude was made accessible to the SWEs internally).
Funny enough, after trying it, I went back to G3.8
As opposed to what, them not having it and burning money that isn't their instead like openai and anthropic? At least Google is feeding itself instead of having to create a bubble to stay alive
Big rich companies take on debt for reasons that are sometimes inscrutable from the outside. Recently, they have been borrowing for ~5%, about a half point above what the US government gets for 10-year Treasuries.
Apple has been financing operations with debt for a number of years as part of a complex optimization plan.
No, Google is not broke.
Some expert wall street analysts discussing what they found and how they dissect things, have a healthy skepticism of Big Ai
https://www.youtube.com/watch?v=YrJzjC4kKCY
If my quick search is correct, Google is sitting on a quarter trillion dollars in cash and marketable securities. They could keep doing the negative cash flow thing at this scale for another decade.
Excited to try this out! Shame on Google for not releasing Gemini 3.8 for Google AI Plus users yet, though.
Is this a pure TPU infra? Really high performance solid intelligence.
Nothing but constant errors with cryptic messages.
There's one or two I find more understated but I would love a 2026 SOTA V2V model that speaks clearly but without the artificial personality layered on.
Human interaction/theory of mind relies so much on non-verbal clues for interpreting emotion/intent and so for me having those neurons firing constantly while talking to an LLM just for an emotional no-op is exhausting to put up with for more than a couple minutes.
There's one male voice that would make me assume someone was sarcastically mocking me if I was talking to an actual person because it's just so over the top.
I don’t want to be aroused by my turn-by-turn street directions, thanks.
However, the "Extended Thinking" should be renamed to "Slightly Extended Thinking". Considering that it's the maximum thinking option for Gemini Flash in the chat UI, it doesn't actually think a whole lot, leading to an uncomfortably high number of incorrect/poor replies.
Let me tell you unlike every other mentioned model Gemini 3.8 Flash trial had to be reverted the same day. Instead of simply delegating tasks it would invent additional requirements and implementation details it knew nothing about and no amount of convincing not to do it would work. That's the first time a model failed on me so spectacularly despite having practically same Artificial Analysis Intelligence Index as another model that just worked (and higher than working DS Flash).
The reason I think it is relevant is: Live is likely even stupider model in every way possible (except hearing better than separate STT). So beware using it for agentic scenarios.
All audio generated by our AI products is watermarked with SynthID. This imperceptible watermark is woven directly into the audio output, ensuring AI-generated content remains detectable to help prevent misinformation. For details on our approach to safety and responsibility, review the model card.
Looking forward to where this can go.
As PrimeTime said; these are the guys that invented the 'T' in 'GPT', that deployed their first TPU in 2015, that is using billions on AI - and they are beaten by 300 people startup named Moonshot AI even. People are going to write books about this complete fumble.
My advice is to listen less to brainrot 'influencers' that optimise for engagement through sensationalism.
They have "unlimited" resources and has researched AI since the very beginning - PageRank is a form of AI even. And still, Gemini is behind Claude, GPT, Grok, Muse, GLM, Kimi and is maybe on par with DeepSeek?
As I said, it is embarrassing.
No one is behind grok. It literally has "be funny and irreverent when appropriate" (whatever the hell "when appropriate" means for them) baked into the system prompt. To me, that is all you need to know about how useful it is.
No serious people use it and the numbers bear it out tbh. It has the smallest market share of the "big companies" for a reason - and it's by a very, very large margin (~2.5% last I checked).
And Gemini is kinda good enough at everything. Never the top, but it is decent at every task, and it is much faster than Kimi K3 and significantly cheaper. Kimi is very focussed on coding, Gemini isn't.
More importantly, it natively understands text, audio and video. If/when we are able to make the jump to robotics, this becomes essential. As you say, Google has a lot of deep background and deep pockets, they are able to make more of a long play. No idea if it will pay off, but it is way to early in the game to count them out.
And they're making money doing it.
Perhaps they don't have the best coding model right now (although 3.8 flash is arguably SOTA at some benchmarks), but is that the be-all and end-all of AI? Only coding matters?
Given the very high margins on inference, once volume is large enough the other can also start printing enough money.