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.
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.
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)
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.
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.
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).
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.
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.
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.
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.
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.
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.
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
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!
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.
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.
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.
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.
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.
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).
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.
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'm worried in their push to catch up on the SOTA front, it's going to lose that natural sounding touch it currently has.
Meanwhile Claude and Astra like to couch all their agreements with caveats and provisos.
Sometimes that's what being smart sounds like.
Lately it became load-bearingly-reality-difficult to not only read, but to comprehend the Claude output
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.
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).
People use text with LLMs but it's great to have a high fidelity "analyze this image"
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.
Excited to try this out! Shame on Google for not releasing Gemini 3.8 for Google AI Plus users yet, though.
Nothing but constant errors with cryptic messages.
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.
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.
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.
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 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.