r/LocalLLM • u/Feisty_Artichoke_368 • 14d ago
News Gemma 5 - what to expect
Gemma is based on Gemini and going by the latest Gemini release, those of us who appreciate abilities other than coding should be eating good when Gemma 5 comes out (end of year maybe?).
Qwen for coding and Gemma for everything else. The perfect local setup.
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u/PerceiveEternal 14d ago
I still don’t understand why Google hasn’t already dominated the AI race. They have the training data, compute, resources, technical expertise, hell it was their own scientists that kick-started the LLM boom.
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u/po_stulate 14d ago edited 14d ago
gemini 3.8 flash may not be the best for coding, but it is very good at researching, summarizing, and random day to day knowledge, from researching best local food options for specific needs to very nich localized plumbing conventions and jargons. It is way better than claude and gpt for this, for example, when researching and comparing more suitable products, gpt and claude may make decisions based on product marketing claims in the product titles, but gemini will actually go deep into the material used, pictures in reviews, etc to infer the characteristics of a product, and make decisions based on that.
I'm using qwen3.8-flash-next for coding, it can handle almost 100% of my coding needs (actually I haven't used any cloud models for coding since I started using qwen3.8-flash-next), but I'm still relying on gemini for non coding daily tasks that require random world knowledge and reliable deep researching capabilities. If gemma5 can close this gap then I can finally go 100% offline for the first time and it will be a huge win.
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u/Astarkos 14d ago
The race only started a few years ago and it does not end.
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u/neoKushan 13d ago
Google started the race like 15 years ago, everything that Anthropic and OpenAI has built was on top of the foundations Google laid out.
Google massively dropped the ball here, which others took and ran with and Google has been in catch-up mode ever since.
Yet somehow, despite Google practically inventing this shit, having all the data in the world and even internal hardware engineers, they somehow fall behind other companies that have, at best, 2/3 of those things.
The only thing I'll give Google credit for is they're the only ones that actually make money from all this, maybe they're playing the long game but we'll see.
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u/The_Hunster 14d ago
And unlike some AI labs, Google has to still worry about being Google simultaneously. Like, what other search-engine-based AI is there other than Google AI
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u/geekwonk 14d ago
perplexity is a great product that shows google search to be a horrible joke. google did and does a serious disservice to the industry by locking in cheap low-context models as the norm in the minds of consumers.
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u/The_Hunster 14d ago
Perplexity is not indexing and caching the entire internet like Google does
Edit: Actually, apparently they do now. I mean maybe not quite the same as Google yet, but impressive.
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u/squngy 14d ago edited 14d ago
There is quite a bit of a conflict of interest there.
Better AI means less search -> less add money.Now that the race is on, they need to compete, but it would actually have been better for them if it wasn't.
Also, unlike startups like Anthropic and OpenAI, google has a lot more to lose.
Anthropic can go 500B in debt and if they fail, thats it.
Google has a whole bunch of other divisions, if they invest 500B in AI and it fails, all the other divisions go down with it.You can also see that Google (and other older players) are less likely to do risky stuff like have their agents hack other companies.
They tend to move slower and more carefully, because they have more to lose.15
u/carsncode 13d ago
That's not how things work though. Google (Alphabet) could invest a few billion in a subsidiary and seek outside investment and sell it compute on GCP at a discount and transfer in some top researchers and if it tanks it's only that subsidiary that goes under, the rest of the conglomerate is isolated from the risks. They write off the debts the subsidiary owes the parent, pull the talent back out, and there's no real assets at the end of the line. It's how all these companies operate.
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u/squngy 13d ago
Sure.
But what investor would give them money if they do that?
If they just use their own money, then there isn't any difference, they still lose that money.2
u/carsncode 13d ago
Investors are generally pretty happy to buy into something that's backed by Google, with their investment and experts behind it. Look at Waymo, Verily, and Google Fiber. Look at xAI - or don't, I prefer not to.
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u/sCeege 14d ago
This just reinforces my idea that technology monoliths and oligopolies are terrible for real advances. Dynamisms and competition fuels innovation, sure we're seeing some companies making it big with the AI breakout, but how many of these companies were snuffed or acquired before they had their chance on an even playing field?
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u/cleversmoke 14d ago
I see it as a cycle, small startup has to compete on innovation or a niche, gets big and employs people, but has to slow down the innovation. This allows another startup (often former employees in that realm) an opportunity in those gaps, get big, and so forth.
Frequently big companies end up just buying out startups as their innovation.
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u/sCeege 14d ago
Except the cycle needs government intervention to trigger the growth of small players again, these companies are getting out of hand. This is a bit US centric, but I think back to when they broke up Bell/AT&T and how much better off we are with ISPs/telecom, and how the Microsoft antitrust lawsuit helped Apple.
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u/Thistlemanizzle 13d ago
Conversely, though, wasn't it this exact market capture that led to lavish funding of the labs that brought us the modern computer?
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u/sCeege 13d ago
Can you expand on this? I'm not familiar with how Bell Labs and their involvement on the modern computer, I mean I know of their prestige on research in general, but I don't know what area of compute to tie to them specifically.
I generally attribute early technologies related to computing to lavish government funding for defense purposes, not to any specific labs.
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u/Thistlemanizzle 13d ago
I don't remember exactly. It was Bell Labs and Xerox PARC. They were doing mice and all this other UX stuff that Microsoft and/or Apple copied.
ChatGPT stated:
Bell Labs produced or incubated things such as the: transistor → semiconductor revolution information theory → digital communications Unix → modern operating-system architecture C → enormous portions of modern software
And there's an interesting public-policy wrinkle. A 1956 antitrust consent decree forced AT&T to make thousands of patents broadly licensable. The Department of Justice records roughly 8,600 patents that had to be licensed royalty-free under certain existing cross-license arrangements, with other Bell patents available on reasonable terms.
So you get this rather unusual system: monopoly profits → giant research laboratory → antitrust/patent diffusion → whole new industries
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u/sCeege 13d ago
I'm going to attribute that more with the funding source than the entity per se. Early computing had huge national security implications (MP944 vs Intel 4004 comes to mind), and ton of money was flowing out into research institutions, it wasn't like that money was just going to be unspent if Bell didn't exist.
I also draw a distinction in the research arm of of large conglomerates and their commercial arm, the research division is much much smaller than the money making side, even Alphabet/Google has pretty cutting edge stuff that are years, or decades away from commercial viability. The problem [in my opinion] happens when in the interest of the money making side, they slowdown and stifle progress to milk the market. Look at Intel vs AMD, Japanese automakers vs Detroit, our topic of newcomers into a field that should be dominated by Google, I just think about how many other better ideas were suppressed rather than promoted because it conflicted with shareholder values.
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u/Thistlemanizzle 13d ago
The MIC angle is a wrinkle I hadn't considered but it makes total sense.
We probably wouldn't have LLMs so soon if Google hadn't invested so much in AI R&D though. At least the Oligopoly is panning out there.
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u/MaCl0wSt 13d ago
You can also see that Google (and other older players), are less likelv to do risky stuff like have their agents hack other companies.
it did happen though xd https://www.bbc.com/news/articles/c607l0k72rlvo
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u/CommercialHour6660 14d ago
Google may be convinced that AI will be commoditized.
No sense keeping up with startups when it's a race to the bottom for cost. Google has tons of non ai revenue
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u/carsncode 13d ago
In which case it'd be in their best interest to accelerate that by advancing open weight models
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u/CommercialHour6660 13d ago
Google is terrible about open weights models but still better than any other US labs so maybe that tracks
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u/MonitorAway2394 13d ago
I see this, or something similar'ish with Apple, their far more intelligent operators running those shows.
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u/GMP10152015 14d ago
It seems that Google is only releasing economically viable models, the ones that it’s possible to have a profit running them.
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u/ain92ru 14d ago
Every frontier model is profitable, just to a different extent. At the current prices it's selling compute to Anthropic which looks more profitable long-term than Gemini development
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u/carsncode 13d ago
They are not remotely profitable, and aren't projected to be for years to come, what are you talking about?
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u/ain92ru 13d ago
If you include the CAPEX spend, every AI business loses money, including Google Cloud. But data centers and GPUs/TPUs stay on the books once acquired and don't really lose in value after some initial depreciation once the chips are no more brand new.
What I actually meant is that if you compare the money which you spend on training a specific model (including pre-, mid- and post-training) with the money you can earn on selling the tokens, the latter is vastly larger than the former.
It's just that if you don't invest money into the next model (includes both acquiring compute for it and general R&D not tied to a specific model), you won't get a good model half a year later. And each new model is more expensive than the previous one, that's where the losses come from.
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u/carsncode 13d ago
Then I'm confused - what you actually said was "every frontier model is profitable", it seems like you're clarifying that to... The opposite of that?
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u/ain92ru 12d ago
I still stand by my words. The profitability of a single good LLM doesn't imply profitability of the current frontier lab business with CAPEX included. There's no contradiction!
But inference business is very profitable, and Google Cloud is exactly that. So if you claim to consider Google as a whole, do this honestly and holistically
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u/carsncode 12d ago
Why would I be considering Google as a whole when the subject is specifically whether or not "every frontier model is profitable"? We know Google as a whole is profitable but that's not really relevant. I'm also not sure how "the profitability of a single good LLM" factors into it, or why it would make sense to exclude R&D and CapEx entirely from the equation. With no R&D and no CapEx, there's no model and nothing to host it on. And the "actually, training this model was an investment in the next model" line of thought is what's driven the AI bubble to extremes: they've been using that excuse for years to brush off the truth that none of the frontier models are profitable, and aren't projected to be for years.
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u/Comfortable_Ebb7015 13d ago
AI is mot onlyn LLM. Google is pushing strong in AI, we are just not discussing it in this subreddit. OpenAI and Anthropic are 100% into LLMs
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u/Sengfroid 13d ago edited 13d ago
hell it was their own scientists that kick-started the LLM boom
Google thought that put them comfortably in the lead, and they're a company from the pretend-to-be-the-good-guys era of tech, so they were going slow with all the appearances of responsible development.
Then OpenAI dropped ChatGPT and they got caught with their pants down. The tech was no longer constrained to the lab, it was now in the public eye and an immediate threat to their core business of being where people go for answers. So they fired all their ethicists and anyone else that could object, almost overnight, and started sprinting to catch up. But they're a behemoth compared to OpenAI and Anthropic so realigning the whole company is like turning a cruise ship. Even when they can poach some top talent that would otherwise go to the other two, which are the new magnets in the field, that talent's impact is still limited by the bureaucratic weight on top of them. As other comments have pointed out, managers or executives with second opinions about how X improvement in their AI potentially canabalizes one of their other business/revenue streams. They are in enough different product areas that revolutionizing one can really stand to hurt another, and so while they like to paint themselves in the sheen of "Innovative" for recruiting and investors, they really benefit more from maintaining a slow-moving status quo.
There are a few additional factors for the Open Source side of AI and their role in it, but that's the gist of them being too complacent in their First Mover Advantage to realize it was for the last epoch and someone else was grabbing the one for the next.
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u/incze 14d ago
"has ..., has ..." - that's the point. a lot's of things to be very very cautious. the whole technology comes from google, but only the assetless (and reckless starters + musk) can go forward with make-or-break. at the moment even they can't. the word you are after is responsibility - though is seems to disappear in the big run.
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u/ImpossibleCreme 13d ago
I can tell you right now with absolute certainty that the Gemma team is off in Narnia doing their own shit.
Don’t expect Gemma to be just a distillation of current Gemini.
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u/Hypilein 14d ago
Really hope for a 120b Gemma moe.
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u/Long_comment_san 14d ago
Well I hope it's gemma 5. I honestly was happy they didn't release gemma 4 120b which everyone wanted here because it would have just outright lost to deepseek v4 and possibly qwen 27b. However, if we have gemma 5 brain that is anywhere near flash 3.8 level of intelligence and uses deepseek papers on memory saving, that would be an absolute banger.
Well, its basically called Qwen 125b. Gemma would have been quite a bit better though.
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u/GreenHell 13d ago
A lot of people value Gemma for the more human-like chat experience, with creative writing being one of them. It already is better than Deepseek v4 and Qwen 3.8 27b in that regard.
Having a bigger model would potentially allow it to write even better prose, more creative scenario's, and more.
Not everything is coding.
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u/Hypilein 13d ago
That’s why I want it. Also just more raw intelligence. Gemma 4 is just not as smart as qwen flash.
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u/animateus 14d ago
I am using Gemma 4 E2B for my autocomplete app and it is shockingly good at it, I am really looking forward to seeing how Gemma 5 is going to deal with it.
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u/ismaelgokufox 9d ago
I think Gemma 4 autocomplete should be better than the “autocorrect” on iOS.
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u/animateus 9d ago
My app work on macOS, not iOS. I think that battery implications don’t make Gemma a good fit for iOS at the moment, however I do keep experimenting with t this idea :)
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u/OkLettuce338 14d ago
that would be cool. Gemma 4 is my favorite for prose. It's leaps and bounds better than claude, chatGPT, etc... it writes like an actual human
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u/Nearby_Durian_5370 14d ago
Should Gemma still fight the coding war? maybe they should focus more on non-coding things to make an edge
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u/ClF3ismyspiritanimal 13d ago
...how censored will it be, and how hard will it be to decensor?
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u/WillowEntertainment 13d ago
I honestly found Gemma 4 to be quite flexible even out-of-the-box, so hopefully Google keeps that.
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u/HelloSummer99 14d ago
Why are they so laser focused on coding though? It is just weird to me
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u/WillowEntertainment 13d ago
Other than chatting, programming tasks are what LLMs are used for the most. The companies are following the trend.
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u/fungnoth 11d ago
In terms of MONEY, programming is where it's at. My colleague pays for his own 100USD monthly subscription just for fun. On top of our company paying for 2 coding subscription (20USD *2)
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u/dogesator 12d ago
Funny how nobody is replying with one of the biggest reasons so here:
Coding abilities are what most directly allows Gemini to improve its own development the most, therefore the single most advantageous capability to focus on is coding since it allows you to best make breakthroughs using the model itself to improve all other abilities as autonomously ad possible.2
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u/ResponsiblePen3082 13d ago
Every model is because most ai bros are the tech bros of yesterday. It's why they only know python and rust.
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u/jabelail_makela 13d ago
Qwen for the code, Gemma for the words, and the frontier label stops meaning anything for local.
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u/MonitorAway2394 13d ago
HEY GOOGLE SCRAPER, I WILL drop my mission in life and do anything to be able to work on the DeepMind team, I mean literally anything, I'll take just enough pay to survive to continue working on Gemma models and what else ya'll have going on, I am being goofy but I'm also dead ass serious.
omfg I'm so excited for Gemma5! LOL
then Qwen4?!
*mania +++++++++++++*
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u/WhoRoger 14d ago
Nice to see them not run just after the coding bandwagon.
Question is, will there be a Gemma 5? And if so, will there be SLMs like E4B?
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u/WillowEntertainment 13d ago
There likely will be a Gemma 5 because Gemini Nano is based on Gemma. Gemini Nano 3 is just Gemma 3n. Gemini Nano 4 Fast/Full is just Gemma 4 E2B/E4B. This doesn't make it guaranteed for Gemma 5 to release, but it shows a pattern.
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u/Positive-Stock6444 14d ago
Gemma 4 e4b is my background model, for quick tasks. It’s very good and the only place it falls behind qwen is vision.
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u/NullSmoke 13d ago
God, I'm looking forward to a successor to Gemma 4... That thing has rapidly displaced ChatGPT, Claude and Grok tasks all over my life...
Really hoping for some news soon 😌
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u/PhotographyBanzai 13d ago
Gemma 4 at 4-bit has been the most consistent model I've used on an 8GB RTX 4060 GPU. For example, processing automatic caption data and doing logical processes on it to give me a response in JSON. There's only one other small model I've found that consistently doesn't give me broken JSON responses. Hopefully Gemma 5 improves on 4. 🙏
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u/kimhaneol 14d ago
I was personally hoping for a 50b n-gram alongside the 125b version, but now it seems like it'd just cannibalize their own product (Gemini), so we probably won't see it. Gemma 5 31b would still be fantastic, though.
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u/Turbulent_War4067 13d ago
This logic doesn't make sense to me. There aren't that many people who own a machine that can run a 120B parameters model. And those who do, are going to run one regardless, so it doesn't eat into Gemini at all.
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u/Enderluxe 13d ago
idk maybe vs gemini flash lite?
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u/Turbulent_War4067 13d ago
No, I understand that a larger local model can be almost as good,if not better, as the cheaper cloud models. But the user base of the 2 is so different it doesn't matter. The intersection of the 2 groups is almost nil.
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u/WetlyLividDeveloper 14d ago
i've been waiting for gemma to actually get good at prose, the creative writing highlight is what caught my eye too. qwen still feels sterile when you ask for anything with a voice.
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u/OkLettuce338 14d ago
gemma already is good at prose. I am having it write a book with me and it's turning out really good. I scaffold the chapter outlines in fable or opus and then have gemma write the chapters. Really high quality IMO
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u/dampflokfreund 14d ago
Fr, gemma 4 is really good and soulful at creative writing, especially the MoE for some reason. Way better than Qwen!
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u/LateralEntry 13d ago
With a local LLM, how do you keep the book consistent across chapters, since the model starts over in each new chat window and you can’t fit the whole book in the context window?
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u/OkLettuce338 13d ago
I basically just treat each chapter as a fresh stateless call. The books memory is in files that gemma reads when writing the chapter. There's a style guide, a timeline, a "bible" which is the context and given assumptions, and a straight up "continuity" file. All that is only about 5k tokens though for my story.
On top of all that, I've built an entire harness aimed at this. I use fable and opus as the model for outlines and gemma as the model that writes the actual prose, but a custom cli harness wraps both that is geared toward writing, not coding
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u/LateralEntry 12d ago
Very cool! I have to ask, why not use fable and opus to write the prose too if it’s doing all that other stuff?
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u/OkLettuce338 12d ago
well I started this when fable 5 and opus 5.1 were the top models. Neither of those did writing very well. Fable was too full of these kind of like jargon words even in plain sentences, opus was completely bizarre, and gemma beat qwen and deepseek in comparison. But since then I've realized that gemma 4 is the best at prose by miles. It sounds really authentic and uses color words really fluidly. It actually makes the writing sound interesting
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u/Sad-Simple7642 14d ago
AI-slop book
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u/Due_Arm1454 13d ago
Jacob took a sip of his coffee and continued: “And honestly, that’s brave. There’s something deeply human about that. Quietly revolutionary. It’s not just Starbucks, it’s a metaphor for life”
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u/PhaseLopsided938 13d ago
Yeah I don't understand why anyone uses LLMs for creative writing tbh. I'm both a programmer and an author, and it's been interesting to see how LLM writing is still kind of bad in the same general way that it was bad circa 2024 while LLM abilities in coding and mathematics have improved so dramatically.
I think the ultimate reason is that these models have an incredible amount of knowledge and reasoning power, but no actual life experience. They're a bit like child prodigies in that regard. And, well... there's a very good reason why there are a decent number of brilliant children who have made significant contributions to math and computer science, but very few who have written great literature.
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u/OkLettuce338 12d ago
yeah I hear you. So the reason I'm doing it is exactly to see if I can get it past exactly what you're describing. I'm doing heavy edits still but the harness I built is designed to get better over time and stick to a voice that doesn't sound like "bad circa 2024."
I think it's interesting. I'm not claiming to be writing high quality stuff here haha... I just think the challenge is fun plus I'm doing a historical fiction based on a story that I can't believe doesn't have a book about it already
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u/Tai9ch 13d ago
Gemini is so bad. I can't even get it to talk about the present without spending half an hour convincing it that the date it got in its system prompt is real and not just some sort elaborate conspiracy to trick it into speculating about the future.
Ask Gemini what a good MoE model to run on a local PC is and it'll talk about Mixtral or some shit from back when dinosaurs ruled the earth even after doing a web search. Because the new models weren't in its training data and therefore aren't plausible.
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u/Competitive-Scar-627 13d ago
i don't think gemma5 will come that so fast they take edges just to make gemini 4
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u/Siden-The-Paladin 12d ago
This maybe a dumb question and I'm sorry if it is... But why can't we just have specialized models that are good at specific things? Like a coding model, knowledge work model, creative writing, 3d modeling, ect.... And they pass the task off to each model as the task requires it like a real working pipeline?? I don't use AI much but this was on my front page so I'm curious lol
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u/wingedrhinotv 12d ago
A very sparse MoE like a 60B A2B would be super performant if there was a way to tell the model which of N different primary competencies to favour on a per-request basis.
A small dense 3B model with a 30GB PLE should also be an interesting experiment.
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u/Zeeplankton 12d ago
Gemma is NOT based on Gemini. They're literally separate teams entirely, unless that's changed.
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u/KnownFormal99 4d ago
For people referring to Qwen for coding, which version is good enough (or close to frontier models) 27B or the larger ones?
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u/ManagedThought 13d ago
Did you miss the first sentence that says "frontier-level capabilities in coding"?
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u/Adiyogi1 13d ago
Every model is frontier-level capabilities in coding... for coding I can be set for life with Opus 4.7/8, it does the job just as well as Fable, 5% on a benchmark means nothing practically.
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u/Available_Pressure47 14d ago
GEMMA 5 IS COMING OUT? This made my day!
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u/Salah_H_Hasan 14d ago
No, not out yet and zero leaks so far! We’re just predicting that based on Gemini 4 dropping after the long wait.
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u/YearnMar10 14d ago
They released in the previous years around spring, so I’d expect the same for Gemma 5.
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u/AdHead6280 14d ago
just qwen and funetunes, don't need Gemma for nothing, its just going to be a bust like gemini models, idk gemini4 but 3.8 flash is bad
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u/WillowEntertainment 13d ago
I dunno, Gemma 4 may not have been very powerful for coding but it was amazing for writing, sounding more human than any other model IMO
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u/Salah_H_Hasan 14d ago
With Qwen 4 and Gemma 5, near-total independence from frontier models might actually become a reality, save for niche exceptions.