[HN Gopher] Gemma 3 Technical Report [pdf]
___________________________________________________________________
Gemma 3 Technical Report [pdf]
Author : meetpateltech
Score : 381 points
Date : 2025-03-12 06:39 UTC (16 hours ago)
(HTM) web link (storage.googleapis.com)
(TXT) w3m dump (storage.googleapis.com)
| meetpateltech wrote:
| Gemma 3 is out! Multimodal (image + text), 128K context, supports
| 140+ languages, and comes in 1B, 4B, 12B, and 27B sizes with open
| weights & commercial use.
|
| Gemma 3 model overview: https://ai.google.dev/gemma/docs/core
|
| Huggingface collection:
| https://huggingface.co/collections/google/gemma-3-release-67...
|
| ollama: https://ollama.com/library/gemma3
| derbaum wrote:
| The ollama page shows Gemma 27B beating Deepseek v3 and o3-mini
| on lmarena. I'm very excited to try it out.
| LeoPanthera wrote:
| Doesn't yet work in LM Studio. Barfs an error when trying to
| load the model. (Error 6, whatever that means. Happy I missed
| the first 5.)
| diggan wrote:
| > Barfs an error when trying to load the model
|
| Since you're not using the official models (since they're not
| GGUFs), what exact model are you trying to use? The 3rd party
| you rely on might have screwed something up.
| osanseviero wrote:
| Please make sure to update to the latest llama.cpp version
| upghost wrote:
| I'm still a huge fan of gemma-22b. Looking forward to this one!
| diggan wrote:
| > open weights
|
| What exactly is this supposed to mean? That I can grab the
| weights by just downloading them, or something like that?
|
| Because when I open up the HuggingFace repository, it asks me
| to "accept the conditions" (Google's usage license). How is
| this different from any other proprietary binaries people
| distribute on the internet but let you run locally? Are other
| software (like 1Password for example) also "open software"
| because you can download it?
| idonotknowwhy wrote:
| Replace "google" with "unsloth" in the browser address bar if
| you want to download them without signing up to hf
| diggan wrote:
| Regardless of where you get the weights, Google says you
| need to follow their terms and conditions for the
| model/weights:
|
| > By using, reproducing, modifying, distributing,
| performing or displaying any portion or element of Gemma,
| Model Derivatives including via any Hosted Service, (each
| as defined below) (collectively, the "Gemma Services") or
| otherwise accepting the terms of this Agreement, you agree
| to be bound by this Agreement.
|
| https://ai.google.dev/gemma/terms
|
| Worth knowing if you're planning to use this model for
| production usage/with a business.
|
| So once again, I don't understand what "open" is supposed
| to mean when they call models like these "open weights".
| What part exactly is "open"?
| whimsicalism wrote:
| i think generally these companies are too afraid of the
| obvious rejoinder to try actually enforcing these terms
| diggan wrote:
| Probably, up until they aren't. Are you willing to bet
| against Google's lawyers feeling daring in the future? As
| a private individual, I sure aren't, and I don't think
| I'd bet my (hypothetical) business on it either.
| staticman2 wrote:
| I don't disagree but even Linux has "Terms and
| conditions" of usage under it's license you really need
| to dig into what those are.
|
| There's no doubt Gemma's license is less permissive than
| other models and that it has less community finetuners
| for that reason.
| keheliya wrote:
| According to the OSI's open source definition, you can't
| put restrictions against persons or groups or fields of
| use. In the license, Linux is not restricted in what
| domain it will be used (good or bad).
|
| Here's OSI's argument about this when Meta's llama put
| such limitations in their license:
| https://opensource.org/blog/metas-llama-2-license-is-not-
| ope...
| homarp wrote:
| can you link to Linux terms and conditions? search
| returned nothing.
| balnaphone wrote:
| https://www.kernel.org/doc/html/latest/process/license-
| rules...
|
| https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html
| staticman2 wrote:
| I guess my comment was a bit wrong, Linux has "TERMS AND
| CONDITIONS FOR COPYING, DISTRIBUTION AND MODIFICATION"
| not usage.
| genpfault wrote:
| > ollama: https://ollama.com/library/gemma3
|
| Needs an ollama newer than 0.5.11. Probably the very-recently-
| released v0.6.0[1]:
|
| > New Model:
|
| > * Gemma 3: Google Gemma 3 model is now available in 1B, 4B,
| 12B, and 27B parameter sizes.
|
| [1]: https://github.com/ollama/ollama/releases/tag/v0.6.0
| starik36 wrote:
| Doesn't work on 0.5.13. Had to upgrade to 0.6.0.
| setgree wrote:
| A kind of ancillary note, but it's amazing to me how fragmented
| this presentation and documentation is:
|
| * the parent link is to storage.googleapis.com
|
| * There's documentation on ai.google.dev
|
| * The announcement blogpost is
| https://blog.google/technology/developers/gemma-3/
|
| * you try it on https://aistudio.google.com/
|
| It's helpful to have a top-level post like this, but can some
| PM please consolidate this into, IDK, ai.google.com/gemini?
| klysm wrote:
| I don't see how this actually matters - who cares if it it's
| different top level domains?
| behnamoh wrote:
| > We also change the architecture of the model to reduce the KV-
| cache memory that tends to ex plo de with long context
|
| This is key (pun not intended). It's one thing to run these
| models locally; it's a totally different game when you need
| longer context.
|
| Sure, the new M3 Ultra can fit a Q4 DeepSeek r1 in URAM, but as
| soon as you wanna get usable context like +64k, the t/s and PP
| quickly become prohibitive.
|
| Speaking of M3 Ultra, I really wish Apple had put more bandwidth
| in this beast of a machine. It's got a lot of "energy", not a lot
| of "power" to actually use that energy.
| kbrannigan wrote:
| Can someone explain Gemma vs Gemini for me please?
| hargup wrote:
| Gemma is their open-source series of models. Gemini is the
| propertierary ones. Gemini models are bigger and better. But
| Gemma are pretty good too.
| tpm wrote:
| open-weights, not open-source (sorry to be that one but open
| source in this case would mean you can build it yourself from
| provided "source", which you can't, because it's not
| provided)
| mrob wrote:
| And even "open-weights" is generous, as they're released
| under a proprietary license with usage restrictions, not an
| open-source license.
| aoeusnth1 wrote:
| "Weights available"
| danielhanchen wrote:
| Super cool models! Love the mixture of sliding window and global
| attention to cut down on KV cache sizes! And 4B, 12B and 27B are
| vision + text by default! Super cool!
| atarus wrote:
| Looks great! So excited about this! We have been using gemma
| models since gemma 1.0 and they are so far ahead of the curve!
| pilooch wrote:
| Someone knows whether there is support for multiple images as
| input ? I don't see it from the docs yet.
| ibash wrote:
| Yes
|
| > If you want to prompt with more than one image, you must
| include a <start_of_image> tag for each image included in your
| prompt.
|
| From here: https://github.com/google/generative-ai-
| docs/blob/78688755db...
| Patrick_Devine wrote:
| Not quite yet on Ollama, but hopefully we'll add this soon.
| Also, we didn't add the pan-and-scan algorithm yet for getting
| better clarity in the original image.
| canyon289 wrote:
| Hey, I'm Ravin from the Gemma team. It's on ollama! Try
| `ollama run gemma3` to get it pulled locally
| kgwgk wrote:
| They talked about support for multiple images as input.
| Patrick_Devine wrote:
| My point was multi-images and pan-and-scan. We haven't
| implemented those yet in Ollama, but soon!
| pilooch wrote:
| Good, FYI the number one usage is vision RAGs (RAGs that
| deal with documents as images instead of text).
| khimaros wrote:
| doesn't seem to have hit the LMArena yet. will be interesting to
| see where it places there.
| Squarex wrote:
| Pretty highly. It's on page 5 of the report.
| leonardhussenot wrote:
| Leo from Gemma team here: it's also live on lmsys now !
| LeoPanthera wrote:
| > They are designed to help prevent our models from generating
| harmful content, i.e.,
|
| > [...]
|
| > Sexually explicit content
|
| Dear tech companies. Sexually explicit content is not harmful.
| Why are you all run by puritans? I don't even want to make edgy
| porn, I just want to be treated like an adult.
| swyx wrote:
| usual answer to "why can't I have nice things":
|
| lawyers.
|
| (on both sides)
| BriggyDwiggs42 wrote:
| Advertisers might be a better reduction
| maccard wrote:
| In my experience, it's nothing to do with actual lawyers and
| everything to do with cultural and societal norms.
| esafak wrote:
| _Lawyering_ by puritans, maybe. The lawyers themselves are
| not particularly imposing their prejudices.
| charcircuit wrote:
| Generating sexually explicit content can cause reputational
| damage or have legal risk. Not generating such content is
| something that many developers are looking for. There is people
| who may want such harmful content and other players can cover
| such a niche.
| logicchains wrote:
| That's a bullshit excuse. The Chinese model creators live in
| a totalitarian dictatorship where porn is banned and the
| creators could be arbitrarily jailed, but even they don't go
| to such effort to censor their open source models (there's
| censorship on their hosting websites but minimal if you run
| the models locally).
| charcircuit wrote:
| Filtering is not necessarily a good user experience and
| comes with a cost to do. Google making a model they expect
| there to be demand for is not just an excuse.
| logicchains wrote:
| They don't expect to make money serving Gemma; it
| benchmarks worse in almost every way than their closed-
| source Gemini. Believe it or not, one of the main sources
| of demand for these small, non-SOTA models is people
| using them for roleplay locally. Anyone corporate has the
| money to use a bigger, more effective model.
| numpad0 wrote:
| I don't think it's reputation risk of companies at large, but
| risk to individual developers. "He worked on porn" is such an
| easy gut logic for terminations. It's in our human instincts.
| Everyone know that in guts.
| patates wrote:
| They mean "harmful to us", not the users. It's harmful because
| they live an echo chamber of a single mention of genitals makes
| all the stakeholders run away. Why do they run away? Because
| they also have stakeholders, and so on.
| ibash wrote:
| This could be a historical accident.
|
| Early models were censored, making uncensored releases have bad
| optics.
|
| If the first models had been uncensored, no one would care if
| another was added.
| bloomingkales wrote:
| Have an uncensored model loop through nypost articles and ask
| it to synthesize content from that. Nypost has tons of
| scandalous content and can easily get spun into erotica by an
| uncensored model.
|
| It's unsafe for that reason, so you absolutely needed both
| censored and uncensored. It wasn't an accident.
| littlestymaar wrote:
| > can easily get spun into erotica by an uncensored model.
|
| A sexualized fine-tune yes, but that's because you have to
| make them overly horny to overcome the original censorship.
|
| Nothing prevent them to train a model that will have an
| appropriate level of sexual content (that is, only upon
| user explicit request) the same way they train it not to
| have sexual content at all.
|
| The reason they do that is because they are American
| companies, the same companies who also censored nude
| paintings and statues from European museums' pages.
| Arkhaine_kupo wrote:
| The early models were uncensored, but people seeing early
| llms give meth recipes and how to make car bombs made them
| quickly get neutered before public release (additional
| controls, for pirvate info, nudity, swearing etc all come
| from additional guardrails and improvements of the protection
| they can offer the company and not end users)
| Karrot_Kream wrote:
| The model is open weight, I'll bet someone or the other will
| abliterate it soon. Maybe you want to do the honors? I have an
| abliterated Llama running on a server shared with friends and
| it works great.
| LeoPanthera wrote:
| This only works until it doesn't. Start with a model that
| simply hasn't been trained on anything your shareholders find
| objectionable, and there will be nothing to reveal with
| abliteration.
| xpl wrote:
| Maybe there exists a dataset consisting _entirely_ of
| objectionable content, so people can finetune neutered
| models on it?
| anticensor wrote:
| PH maybe?
| xpl wrote:
| I mean not only sex, but also swearing, drugs, violence,
| etc. Basically everything R-rated (but not illegal) which
| usually gets censored.
| anticensor wrote:
| PH is not porn-only. A significant portion of non-porn
| content also exists there.
| Sharlin wrote:
| More like literotica.
| anticensor wrote:
| Such models would actually run against their long term
| interests of being able to automate away the work currently
| done by humans.
| bloomingkales wrote:
| You can discuss something kosher and have the LLM misinterpret
| it as something sexually explicit. Yours or their logs will now
| have all of this miscommunication, and this is a liability.
| Using models that can't generate this content even by accident
| is good legal decision for many. Same goes for images. Stay
| safe!
| littlestymaar wrote:
| > you'll have to do that locally
|
| The Gemma family is a family of local models!
| mightysashiman wrote:
| on the other hand running with guns is fine.
| mdp2021 wrote:
| Have you considered that selection of material contributes to
| specialization and efficiency? This is meant to be a weights-
| small model.
| swyx wrote:
| its also apparently a well known result that filtering nsfw
| content IMPROVES scores
|
| https://x.com/swyx/status/1661359483447316480
| ddalex wrote:
| LLMs get distracted by porn too !?!?
| alpaca128 wrote:
| The word "gay" mentioned in your link isn't nsfw content
| though.
| Lerc wrote:
| Or perhaps it was removing the curly brackets that improved
| it more than the damage caused by losing the nsfw content.
|
| Or perhaps the measurement of improvement was biased. If a
| model doesn't understand the word gay there would certainly
| be people who would find real world use of the model to be
| substandard.
|
| Did the assessment of what counts as improvement come from
| the same community that decided that excluding things with
| 'gay' was cleaning the data?
| 42lux wrote:
| Everyone is treating this like corps have anything to gain from
| an open uncensored model. Switch your view and give me a single
| argument for it? That random nerds on HN stop jerking each
| other about what ,,open" means? You are just not their target
| group. Having this discussion every time no matter if the model
| released is censored or not is just insanity. Bring new
| arguments or don't use the models you don't like. There will be
| a new sota ,,tomorrow", maybe even one open enough for you.
| practice9 wrote:
| But who is the target group?
|
| Last time only some groups of enthusiasts were willing to
| work through bugs to even run the buggy release of Gemma
|
| Surely nobody runs this in production
| 42lux wrote:
| The press and decision makers without technical knowledge
| are the target group, it doesn't matter if it's used in
| production or not. They need a locally deployable model to
| keep up with enterprises to risk averse to put their data
| into the cloud and also don't care that their shitty
| homegrown ChatGPT replacement barely works. It's a
| checkbox.
| xvector wrote:
| This is what HNers surprisingly seem to not understand.
|
| The risk of the model generating illegal content and then the
| company getting bad PR from vultures in journalism simply
| outweighs any benefits of including this content in the
| training data.
|
| This is also why you will never see the big companies release
| a capable open weight image or video gen model.
| logicchains wrote:
| >The risk of the model generating illegal sexual content
| and then the company getting bad PR from vultures in
| journalism simply outweighs any benefits of including this
| content in the training data.
|
| This is completely unsubstantiated. The original Sydney
| (Bing AI) was violently unhinged and this only drew more
| users; I haven't met a single person who prefers the new
| Bing AI to the old Sydney, and for that matter I haven't
| even heard of anyone using Bing AI for ages now they toned
| it down. Trust in journalists is at an all-time low (
| https://news.gallup.com/poll/651977/americans-trust-media-
| re... ) and America recently elected an extremely
| unorthodox president in big part due to the sheer hatred of
| the media shared by a large proportion of the population.
| Even the most hardcore social conservatives aren't calling
| for companies to censor the training of open source models
| so they don't produce adult textual content even when
| prompted to do so; it's not a political issue.
| 42lux wrote:
| Brings an argument from nearly a decade ago ignores
| everything on google in the last four years. Ofc the
| ,,first" rogue AI drew in more users because of the
| novelty of it... what a shit argument.
| DJHenk wrote:
| The argument is that it simply improves the product. For
| instance, Github Copilot is apparently refusing to do
| anything with variable names like "trans" and anything
| related to sex or gender, regardless of the intended meaning.
| That is a serious flaw and makes the product less useful.
|
| See this: https://github.com/orgs/community/discussions/72603
| 42lux wrote:
| You don't know if the censorship is in the model or the
| system prompt.
| DJHenk wrote:
| That is not relevant to the argument. Censoring limits
| possibilities. While that sometimes has its uses, the
| overly puritanical approach American companies generally
| take degrades the value of their products.
| 42lux wrote:
| I am talking about an ,,open" weight model you are
| talking about a service. If the service wants to censor
| that's fine and on them and their leadership if an
| ,,open" model gets released with censorship it's not,
| because it's just ,,open, but how my manager likes it"
| logicchains wrote:
| >You are just not their target group. Having this discussion
| every time no matter if the model released is censored or not
| is just insanit
|
| Who is their target group for small local models that
| benchmark inferiorly to their proprietary solution (Gemini
| 2.0) then, if not hobbyists and researchers?
| 42lux wrote:
| >> The press and decision makers without technical
| knowledge are the target group, it doesn't matter if it's
| used in production or not. They need a locally deployable
| model to keep up with enterprises that are to risk averse
| to put their data into the cloud and also don't care that
| their shitty homegrown ChatGPT replacement barely works.
| It's a checkbox.
| philipkglass wrote:
| The lack of NSFW knowledge/capability makes them less useful
| for content moderation. I've tried to use multimodal models
| for categorizing images from large, mixed data sets. 95% of
| the input is safe for work. 4% contains nudity but is not
| sexually explicit. 1% contains nudity and is also sexually
| explicit. I'd like to categorize content so that nudity is
| hidden from users by default and that sexually explicit
| content is always hidden.
|
| Every model I've tried so far is bad at distinguishing
| sexually explicit content from mere nudity, and many models
| are bad at distinguishing nude from non-nude. I don't know
| about Gemma 3 but Google's large commercial Gemini models
| refuse (or formerly refused; haven't tried recently) to tell
| me anything useful about images containing human figures. I
| assume that this is due to aggressive "safety" measures. On a
| technical basis, I assume that a model that can distinguish
| 10 different breeds of dog should also be able to usefully
| describe images of people wearing swimsuits, nude people, and
| people engaged in sexual intercourse.
| 42lux wrote:
| There are models especially tuned for it even open weight
| ones. llms even multimodal ones are not up to the task. You
| know what doesn't help the discussion at all? That
| everyone's response is as usual just about titties.
| philipkglass wrote:
| 4 months ago I tried every dedicated NSFW-image-
| classifier model I could find on HuggingFace or GitHub.
| They have a high false positive rate on certain kinds of
| benign content, like close up photographs of hands with
| painted fingernails, and a high false negative rate on
| artistic nude photographs. I even tried combining
| multiple models with gradient boosting but the accuracy
| barely improved; maybe everyone is training with very
| similar data sets. At this point I should train my own
| model but I was hoping to find something capable off-the-
| shelf, since content moderation is such a common task.
| 42lux wrote:
| You can just finetune an open model instead of starting
| from scratch... that's the point of them.
| miki123211 wrote:
| It's harmful in that there exists a significant and vocal
| subset of users who does not wish to see that content or does
| not wish their children to do so. It's easier to teach your
| model never to produce that kind of content than to teach it to
| perfectly distinguish whether this user should see that content
| or not. TV channels are barred from broadcasting this kind of
| content for similar reasons.
|
| Sure, there are always jailbreaks, but then the narrative
| changes from "we made a model that tells erotic stories to
| children" to "this ingenious teenager figured out a way to hack
| our model to make it produce erotic stories." In other words,
| jailbreak move the fault from the model producer to the model
| user.
|
| It's also worth keeping in mind that erotica comprises a
| surprisingly large portion of fiction easily available on the
| internet for free, and "unfiltered" models tend to produce that
| kind of content unprompted (see e.g. the original Mistral). The
| major AI labs are probably filtering it out, but I suspect they
| can't go too far there, as having a model that is good at
| fiction is something they actually want.
|
| Then there are the non-chat-gpt-app use cases (like customer
| support chatbots, automatic summarization etc), for which
| unprompted erotica is highly inappropriate. Those are the
| "business travelers" of AI, not the first thing one thinks of
| when talking about who uses AI models, but extremely important
| nonetheless.
| logicchains wrote:
| >It's harmful in that there exists a significant and vocal
| subset of users who does not wish to see that content or does
| not wish their children to do so
|
| It's hard to think of a scenario where there's a child
| technical enough to run Gemma 3 locally but somehow unable to
| access any other written erotica. Project Gutenberg is full
| of erotic textual content and I haven't heard of anyone
| calling for that to be banned.
|
| >Then there are the non-chat-gpt-app use cases (like customer
| support chatbots, automatic summarization etc), for which
| unprompted erotica is highly inappropriate. Those are the
| "business travelers" of AI, not the first thing one thinks of
| when talking about who uses AI models, but extremely
| important nonetheless.
|
| And how many of these are going to be using Gemma, when
| Gemini over the API is cheaper, faster and easier to use?
| miki123211 wrote:
| More than you think, particularly outside the US.
|
| Companies and government organizations who have sensitive
| data are still unwilling to use these models over any API
| they don't host themselves.
|
| I work in this space in the EU, and this is absolutely a
| problem.
| philipjoubert wrote:
| > It's hard to think of a scenario where there's a child
| technical enough to run Gemma 3 locally but somehow unable
| to access any other written erotica.
|
| The reason you're struggling to understand is that you're
| thinking about this logically.
|
| Adult content is obviously freely available to any child or
| adult with minimum technical skills. What makes LLMs
| different is that it's "the new thing" and people respond
| differently to "the new thing".
| fragmede wrote:
| Won't somebody think of children!?
| Al-Khwarizmi wrote:
| All of this is true but then it's as easy as releasing
| censored and uncensored versions of the model.
|
| Then it's up to users (or parents, in the case of children)
| to choose the adequate version for each purpose. Just like
| there are child-friendly movies and adult-only movies, and no
| one beyond fringe puritan crusaders would say that the latter
| should outright not exist.
| andai wrote:
| >censored and uncensored
|
| Well here you still have the same problem, since they're
| not gonna release an _actually_ uncensored version, that
| tells you how to do awful things (or indeed, that tells you
| to do them).
|
| So then you'd have censored and less censored, and it would
| still be a matter of where to draw those lines.
| Al-Khwarizmi wrote:
| True, "uncensored" is not the best term for what I meant
| (as I'm aware that fully uncensored is not a realistic
| thing to ask from companies).
|
| What I mean is a model for all audiences and an adult
| model, and the line would be drawn at the law of the
| country producing it (if it's something that would be
| legal to publish for a human author at a website, then it
| should be allowed as an LLM response). So erotica would
| be fine, while instructions for making a bomb wouldn't.
| Zambyte wrote:
| Companies release uncensored models all the time. They're
| called "text" models. I just had llama3.2:3b-text-fp16
| give me step by step instructions on how to make a pipe
| bomb.
| rcleveng wrote:
| I think it's easy to released the uncensored version, it's
| just the censored version that's likely super super hard.
|
| Since this is just giving the model directly, there's no
| ability to do any filtering as part of inference, so I
| would imagine you have to assume the worst (intent) on any
| input coming into it.
| startupsfail wrote:
| There are also some practical constraints, like any kind
| of erotic content is completely prohibited in some
| regulations (like India), so if you want to be able to
| have access to human labeling or deploy the model under
| these regulations, you do need to comply.
|
| It'll get easier once the costs of building foundational
| models go down and human labeling gets automated. Sit
| tight, models that'd be creative and amazing at
| generating erotic content are certainly coming.
| andai wrote:
| I heard of this described as the minority effect, that a
| small minority can have a disproportionate impact. The
| example given is that it's cheaper to make _all_ instances of
| a product kosher or halal than to make an entirely separate
| product.
| swyx wrote:
| "tyranny of the minority"
| https://revista.drclas.harvard.edu/a-review-of-tyranny-of-
| th...
| idiotsecant wrote:
| Yes, it would be absolutely _shameful_ if there was
| pornography on the internet, easily available to anyone, even
| _children_. Society would crumble!
| esafak wrote:
| Porn sites are blocked in many jurisdictions, so I would
| not use that argument.
| idiotsecant wrote:
| No, there's no movement to shut down pornography on the
| internet. There's a movement to shut down _specific_
| websites and make a lot of noise about it but continue
| consuming pornography behind closed doors.
|
| People like pornography. They'll as soon ban alcohol
| again (which worked so well last time)
| esafak wrote:
| On the contrary. Porn is inaccessible, along with many
| other things, in much of the world.
| https://worldpopulationreview.com/country-
| rankings/countries...
|
| Alcohol is another good example.
| saagarjha wrote:
| Legally inaccessible; in practice widely available.
| numpad0 wrote:
| there are.
| Workaccount2 wrote:
| It's funny because the results are in, millennials grew up
| with pretty easy access to all manner of porn from an early
| age and the effect has been nothing. Even a reduction in
| intimacy if anything.
|
| I'm sure the hysterical puritans of the past will come out
| any day now and admit that they weren't even 1% correct in
| their assertions.
| saagarjha wrote:
| > Even a reduction in intimacy if anything.
|
| My understanding is that this is one of their complaints
| Workaccount2 wrote:
| It's what they switched when confronted with evidence,
| roll the clock back 10, 20, 30 years though and it was
| "Will turn them into rapists, molesters, and social
| degenerates."
| tomrod wrote:
| > It's harmful in that there exists a significant and vocal
| subset of users who does not wish to see that content or does
| not wish their children to do so.
|
| "I have a right to live in a society that perfectly adheres
| to my personal morals" is not how companies or people should
| operate in a pluralistic society, despite Nassim Taleb's
| claim that the intolerant minority wins.[0]
|
| [0] https://medium.com/incerto/the-most-intolerant-wins-the-
| dict...
| numpad0 wrote:
| And that threat is harmful in that it will kill the tech and
| investment. Betamax and all.
| igleria wrote:
| it follows the historical trend of American puritanism:
|
| nipple BAD.
|
| exploding someone into bits GOOD.
| michaelt wrote:
| There are very few pro-porn voices in the corporate, tie-
| wearing environments that have the money to train new LLMs from
| scratch.
|
| Oh, there are loads of porn _enjoyers_ working in such
| companies - but traditional professionalism means you leave the
| porn at home during the work day. It is, after all, NSFW.
|
| So at the meeting where censorship decisions were being made,
| even a weak argument for censoring explicit content will be
| accepted unopposed.
| saagarjha wrote:
| Places training LLMs don't have many people who wear ties.
| bbminner wrote:
| Not all sexually explicit content is harmful in all contexts
| for sure, but in many contexts it is fairly universally
| considered harmful (eg content involving minors). Do you have
| means of distinguishing between the two? Are you suggesting
| that a company must invests millions into teaching the model
| where exactly the red line lines so that it can have a
| conversation close to it but without crossing it? Or you
| suggest biting the bullet and releasing the model not only
| capable of generating eg child porn, but also having a >0
| chance of randomly discussing it in unrelated contexts? Chance
| of error is always there, and companies decided that a risk of
| really bad behavior in benign context overweights the gains.
| Imho, a decision to not play whack a mole with this land mine
| is quite rational, esp considering gains vs risks vs costs.
| Think of it as a cost cutting measure, not as an infringement
| on free speech. You are free to invest you own money into this
| problem if you think that's a grave mistake and a missed
| opportunity. The first project to push the automated generated
| content moderation against what is considered appropriate in
| the given context far enough to make it economical for
| companies to put their guard down could actually be worth a lot
| if you think there's market for it (eg agents on dating
| websites? idk, you tell me)
| letmevoteplease wrote:
| I don't agree that textual, fictional explicit content
| involving minors is "fairly universally considered harmful".
| Such content is allowed on large platforms like Archive of
| Our Own or Japan's Shosetsuka ni Naro. I think "don't think
| it's harmful, but not willing to defend" is a pretty typical
| attitude.
| msp26 wrote:
| I want to use a multimodal model for manga translation,
| analysis, and tagging.
|
| If this gives me the "aschually as a ethical safe harmless
| assistant I can't ..." spiel on anything mildly mature, that
| would be very disappointing. I'll run a test with Berserk and
| see how it goes.
|
| I'm not a big believer in abliteration, it seems to always hurt
| performance. Safety should be handled by a separate system, no
| need to cripple the actual LLM.
| idonotknowwhy wrote:
| The multimodal models aren't good for this. Refusals aren't
| the issue (they're fine with BERSERK, though occasionally
| they'll refuse for copyright). The issue is the tech isn't
| there yet.
|
| You'll want to use custom models to segment the manga
| (panels, speech bubbles), OCR the text, translate (gemma
| punches above it's weights for this part).
|
| That said, I've been experimenting with using Pixtral to do
| the analysis part with okay-ish results (providing individual
| panels with the character names) but it'll still mix up the
| characters when they're drawn differently.
|
| > I'm not a big believer in abliteration, it seems to always
| hurt performance.
|
| Agreed, it's fun to play with but it increases halucinations.
| And for creative writing, it makes the model write more
| compliant characters (they'll give in too easily during
| negotiations, rather than refuse, etc)
|
| Could probably be improved with more targeted abliteration.
| Zambyte wrote:
| Whenever they say things like "harmful" or "unsafe" there is an
| implied "for our brand" that follows.
| wyager wrote:
| Wireheading humanity into population collapse via pervasive
| sexual hyperstimuli (which is realistically what is on the
| table here) is basically the definition of "harmful".
|
| This is just silly because it only takes one AI company to
| defect and start enabling it, and the problem is already pretty
| bad even without AI.
|
| I think all of the solutions are demand-side, not supply side.
| I would expect differential reproductive rate trends between
| populations with and without proscriptions on ersatz reality
| consumption (i.e. aniconist Muslims, Mennonites, etc.) to
| accelerate
| numpad0 wrote:
| The solution to this problem is to _make it not work_. If there
| are various technological developments in the world that do and
| don 't have porn, and if such were cases that the common
| denominator of failures were lack of smoothly graduated
| spectrum of contents without disruption from casual family safe
| content to hardcore pornography, the problem will correct
| itself.
|
| Actually, it will happen naturally and eventually. Just look at
| Apple Vision Pro which still don't have VRChat support, and
| compare how deeply DOA it has been to other VR headsets that
| are clearly nowhere near as important. Or "Metaverse" that were
| all explicitly SFW.
|
| This effect can even be seen in the Apple App Store itself. Who
| _uses_ App Store? You flow into App Store through porn-enabled
| platforms, such as web or social media. No one browses App
| Store as a content. What does it _not_ have? Pornography.
| rybthrow2 wrote:
| Google DeepMind are the best :)
| vimgrinder wrote:
| very excited for this. my current fav model on my mac mini for
| text processing is gemma 9b + gemma 2b combo spec decoding. great
| times to have all this getting drop left and right.
| Tepix wrote:
| Very cool to see two promising new LLMs on the same day (the
| other one being Reka Flash 3 21b) with open weights.
|
| Now, bring on those multimodal LLMs with voice input and output
| please!
| tomthe wrote:
| Very cool open release. Impressive that a 27b model can be as
| good as the much bigger state of the art models (according to
| their table of Chatbot Arena, tied with O1-preview and above
| Sonnet 3.7).
|
| But the example image shows that this model still makes dumb
| errors or has a poor common sense although it read every
| information correctly.
| vessenes wrote:
| I was thinking the same thing about the receipt calculation: a
| warning that only tourists tip 18% in Switzerland would no
| doubt have been appreciated!
| aoeusnth1 wrote:
| Looking at every other benchmark, it's significantly behind
| typical big models from a year ago (Claude 3.0, Gemini 1.5, GPT
| 4.0). I think Google must have extensive LMArena-focused RLHF
| tuning for their models to juice their scores.
| wizee wrote:
| It seems to have been very benchmark-tuned for LMArena. In my
| own experiments, it was roughly in line with other comparably
| sized models for factual knowledge (like Mistral Small 3), and
| worse than Mistral Small 3 and Phi-4 at STEM problems and
| logic. It's much worse than Llama 3.3 70b or Mistral Large 2411
| in knowledge or intelligence in reality, even though LMArena
| ranks it as better than those.
| jiangdayuan wrote:
| The performance of Gemma 3 is insane.
| saberience wrote:
| Seems like its tuned for benchmarks for me, as in, real world
| it seems worse than Mistral and Llama.
| YetAnotherNick wrote:
| They say all the models were distilled from a teacher model but
| they didn't specify what that teacher model is. Interesting thing
| to hide.
| LeoPanthera wrote:
| It's a safe bet that it's either one of the Gemini models or a
| relative of it.
| YetAnotherNick wrote:
| That's what I thought. And it could be pulicity of Gemini as
| well that it is so good that it can teach students say 5x
| faster. If it is Gemini, there isn't any reason to hide. My
| bet is it is some unreleased Gemma or some model.
| pzo wrote:
| would be good to see how gemma 3:4b compare to phi4-mini
| alekandreev wrote:
| Greetings from the Gemma team! We just got Gemma 3 out of the
| oven and are super excited to show it to you! Please drop any
| questions here and we'll answer ASAP.
|
| (Opinions our own and not of Google DeepMind.)
|
| PS we are hiring:
| https://boards.greenhouse.io/deepmind/jobs/6590957
| magicalhippo wrote:
| Thanks, been using Gemma 2 a lot at home as it still holds up
| very well and the 9B version runs great on my 2080Ti. Strong
| prompt adherence coupled with overall capability makes it very
| useful. Looking forward to trying Gemma 3.
|
| I have some dumb questions though, might as well ask. How do
| you decide on the model sizes? And how do you train them?
| Independently or are they related somehow?
| alekandreev wrote:
| Picking model sizes is not an exact science. We look for
| sizes that will fit quantized on different categories on
| devices (e.g., low-end and high-end smartphone, laptops and
| 16GB GPUs, and bigger GPUs/TPUs). We also want the ratio of
| model width to depth (number of layers) to be consistently
| around 90, which we found works best.
|
| The models are trained with distillation from a bigger
| teacher. We train them independently, but for v3 we have
| unified the recipes for 4B-27B, to give you more predictably
| when scaling up and down to different model sizes.
| magicalhippo wrote:
| Thanks again, very interesting.
|
| One unexpected (to me) use-case appeared not long ago when
| I found myself without internet but wanting to fix some
| non-standard Linux configuration issue. As a Windows guy I
| tend to web search such things, but local LLM to the
| rescue!
|
| Even smaller models like Gemma 2 9B has enough compressed
| knowledge that it managed to help me quickly solve my
| issue.
|
| This got me thinking how such smaller, but very capable
| models might be a game-changer in communities where
| internet might not be available or too expensive for
| continuous use. It's almost like having a portion of the
| internet in a box, just add electricity.
| alekandreev wrote:
| Thank you for the feedback! This is why we are so excited
| to push more and more on small models for both low end
| and high end smartphones!
| bguberfain wrote:
| Can you provide more information about this "bigger
| teacher" model?
| swyx wrote:
| will there ever be a Gemma 3 Thinking? how copyable is the
| Flash Thinking approach to the Gemma series?
| alekandreev wrote:
| That's a very interesting area, but nothing we can announce
| today.
| mdp2021 wrote:
| Thank you!
|
| Question: your model supports 140 languages. Given that you are
| focusing on compactness and efficiency, would you not have
| gains in also developing models on a selected limited number of
| languages (e.g. the topmost (in cultural production) four
| "western" ones with shared alphabet - or similar set)?
|
| Edit: of course the multilingual capability can be can be
| welcome. On the other hand, there are evident cases in which
| efficiency can be paramount. We can wonder about the tradeoff:
| how much in efficiency is sacrificed by features.
| alekandreev wrote:
| That's an idea we've thought about. However, we think the
| open source community has already created a very impressive
| set of language or region-specific finetunes [1] [2]. Also
| there is a lot of cultural and nuance context in every
| language that we don't have the capacity to cover
| sufficiently. So for v3 we focused on creating the best
| foundational multilingual model.
|
| [1] https://huggingface.co/aiplanet/buddhi-indic
|
| [2] https://ai.google.dev/gemma/gemmaverse/sealion
| mdp2021 wrote:
| And have you measured the trade-off that could come with
| embracing such a large number of languages and alphabets?
| It would be interesting to note whether you are sacrificing
| some response quality, or if such supposed sacrifice is
| interestingly negligible, or if - even more interestingly -
| the quality increases with the added proficiency.
| Workaccount2 wrote:
| There are enough small model teams competing that I fell
| confident one of them will try this, and if it just
| sticking to english gives a large boost, the others will
| be forced to follow suite.
|
| It would also kind of suck for non-english speakers,
| because it will just be another feather in the hat of
| "English eats the world".
| mdp2021 wrote:
| Some numbers to try and make an idea: if I understand
| correctly, Gemma3 uses a fixed (in its versions by size)
| vocabulary 256k entries big; the smallest 1B version has
| ~300M embedding parameters and ~700M non-embedding
| parameters; the largest 27B version has ~5x embedding
| parameters and ~35x non-embedding parameters.
|
| Multilingualism covering 140 languages is quite a big
| feat. Gemma3 apparently aims to be compact and efficient.
| The two goals and features put together raise questions.
| You wonder for example how much does such extensive
| multilingualism impact the above numbers, on a benchmark
| of similar results. It may e.g. be a general question to
| wonder how much multilingualism complicates an embedding
| space (owing e.g. to omographic collisions), and the
| question becomes more prominent when you crammed 140
| languages in one model.
|
| > _non-english speakers_
|
| You would produce more specialized models (where it makes
| sense): Eng; Eng-Fra-Esp-Deu; Man-Can... For a billion
| weights per model it could probably be financially
| acceptable.
| alekandreev wrote:
| Yes we have measured the tradeoff. We don't see a drop of
| perplexity in English when introducing multilingual, and
| there is a slight drop in some English language-specific
| evals (~1%).
| miki123211 wrote:
| How good is Gemma at structured output generation, JSON schema
| compliance and tool use? Particularly the smaller versions,
| particularly in foreign languages?
|
| We will run our internal evals on it for sure, but just wanted
| to ask whether that's even a use case that the team considered
| and trained for.
| canyon289 wrote:
| Hey, I'm from the Gemma team. There's a couple of angles to
| your question
|
| We do care about prompted instructions, like json schema, and
| it is something we eval for and encourage you to try. Here's
| an example from Gemma2 to guide folks looking to do what it
| sounds like you're interested in.
|
| https://www.youtube.com/watch?v=YxhzozLH1Dk
|
| Multilinguality was a big focus in Gemma3. Give it a try
|
| And for structured output Gemma works well with many
| structured output libraries, for example the one built into
| Ollama
|
| https://github.com/ollama/ollama/blob/main/docs/api.md#struc.
| ..
|
| In short you should have all the functionality you need!
| seektable wrote:
| Just tried gemma3:4b for structured output and it fails with
| a strange error ( ollama is the latest):
|
| Ollama error: POST predict: Post
| "http://127.0.0.1:49675/completion": read tcp
| 127.0.0.1:49677->127.0.0.1:49675: wsarecv: An existing
| connection was forcibly closed by the remote host.
|
| Not sure this is Ollama or gemma3:4b problem. At the same
| time, gemma3:12b works fine for the same API request (100%
| identical, only difference is model id).
| seektable wrote:
| looks like Ollama's issue:
| https://github.com/ollama/ollama/issues/9686,
| https://github.com/ollama/ollama/issues/9687
| heinrichf wrote:
| I'm comparing Gemma3 12 B (https://ollama.com/library/gemma3;
| running fully on my 3060 12GB) and Mistral Small 3 24B
| (https://ollama.com/library/mistral-small; 10% offloaded to the
| CPU).
|
| - Gemma3 12B: ~100 t/s on prompt eval; 15 t/s on eval
|
| - MistralSmall3 24B: ~500 t/s on prompt eval; 10 t/s on eval
|
| Do you know what different in architecture could make the
| prompt eval (prefill) so much slower on the 2x smaller Gemma3
| model?
| alekandreev wrote:
| Thank you for the report! We are working with the Ollama team
| directly and will look into it.
| moffkalast wrote:
| What's the official take on the system prompt? The technical
| report doesn't mention it, but the official QAT GGUFs include
| some form of prepending it to the first user message. Has it
| been trained with any <start_of_turn>system turns with tool
| calls and such?
| alekandreev wrote:
| We recommend using <start_of_turn>user for the system prompt
| as well.
| tucnak wrote:
| I was under the impression that the purpose of "system"
| prompt is to encode the instruction boundary explicitly to
| reduce the risk of injection. Do you enforce some kind of
| security invariant that we could rely on? For example, does
| the alignment regiment include adversarial demonstrations
| so that out-of-order instruction-following (such as
| contradicting preceding) is penalised?
| sidkshatriya wrote:
| As per the technical report, every 5 layers you have a global
| attention layer. The global attention layer during training can
| have as many as a 128k context length during training (though I
| understand it is usually 32k).
|
| Q. When you are training with a context length of 128k, is the
| attention in the global layers dense or sparse ?
|
| If dense, would the attention memory requirement here would be
| O(n^2) where n is 128k for each global layer ?
| alekandreev wrote:
| We never train at 128k, only 32k, changing the scaling factor
| at the end.
|
| We wanted the long context recipe to be friendly for
| finetuning, and training at 128k is a bit of a pain we don't
| do it. For inference, we see inference at 128k with the 5/1
| is close to RAM usage for a fully-global-layer model at 32k.
|
| Individual attention layers are always dense.
| sidkshatriya wrote:
| Thanks for your answer ! So in the 32k global layer, every
| token attends to each of the other 32k tokens ?
|
| [Edit: You answered the question when you said that
| individual attention layers are always dense.]
| saagarjha wrote:
| Google is using Greenhouse for ATS now?
| Herring wrote:
| Excellent work. What optimizer did you use? I assume AdamW? I
| didn't see it listed.
| nothrowaways wrote:
| Is this what powers Gemini?
| chickenbig wrote:
| In Switzerland isn't it customary to round the food bill up to
| the nearest 10?
| gundmc wrote:
| What do companies like Meta and Google gain from releasing open
| models? Is it just reputational? Attractive to top AI talent?
| npodbielski wrote:
| I believe (and some other people on the internet having more
| knowledge in LLM believe too) that open source local models are
| the future. Probably big models with API and chat like OpenAI
| is doing will have its niche toot but it is very costly and it
| is not AGI and it will not be in the near future. On the other
| hand with rise of NPU chips and small models you can have your
| own assistant on your phone using your own data almost
| instaneously with almost no cost. Whoever will build the best
| OS model will win this race. As the winner you will be able to
| set the standard. Basically it is why we have Linux on the
| severs not Windows and why even browsers are free you still get
| one from every tech giant.
| lastLinkedList wrote:
| I'm curious to hear more about phone-local assistants. I
| rather assumed only the latest hardware ( iPhone 15+, not
| sure on Android side) could do local inference. Is there a
| way to get something going on hardware a couple years old?
| simne wrote:
| > Is there a way to get something going on hardware a
| couple years old?
|
| Tensor accelerators are very recent thing, and GPU/WebGPU
| also recent. RAM was also limited, 4Gb was long time
| barrier.
|
| So, model should run on CPU and within 4Gb or even 2Gb.
|
| Oh, I forget one important thing - couple years old mobile
| CPUs was also weak (and btw exception was iphone/ipad).
|
| But, if you have gaming mobile (or iphone), which at that
| time was comparable to Notebooks, may run something like
| Llama-2 quantized to 1.8Gb at about 2 tokens per second,
| not very impressive, but could work.
| colejhudson wrote:
| Those are certainly benefits, but it's most likely a
| prophylactic move.
|
| LLMs will be (are?) a critical piece of infrastructure.
| Commoditizing that infrastructure ensures that firms like
| Google and Meta won't be dependent on any other (OpenAI) for
| access to that infrastructure.
|
| Meta in particular has had this issue wrt Ads on iOS. And
| Google wrt paying Apple to be the default search engine.
|
| See also: Joel Spoelsky's famous Strategy Letter V [0].
|
| [0]: https://www.joelonsoftware.com/2002/06/12/strategy-
| letter-v/
| summerlight wrote:
| There are certain demands and if you don't do anything, those
| will be taken over by competitors and you lose controls. This
| is especially important for Google as they see LLM as a
| significant portion of future Cloud business and probably want
| to have a smooth, exclusive transition path to their
| proprietary models.
| xnx wrote:
| Linking to he announcement (which links to his PDF) would
| probably be more useful.
|
| Introducing Gemma 3: The most capable model you can run on a
| single GPU or TPU
|
| https://blog.google/technology/developers/gemma-3/
| xnx wrote:
| Even though Gemma 3 takes much less inference processing power
| and delivers better results than DeepSeek v3, I'm certain this
| won't cause the same Nvidia stock price panic that DeepSeek did.
| xnx wrote:
| This is the first model I can think of that advertises itself as
| being optimized for AMD ROCm.
| vessenes wrote:
| Lots to be excited about here - in particular new architecture
| that allows subquadratic scaling of memory needs for long
| context; looks like 128k+ context is officially now available on
| a local model. The charts make it look like if you have the RAM
| the model is pretty good out to 350k or so(!) with RoPE.
|
| In addition, it flavor tests well on chat arena, ELO
| significantly above yesterday's best open model, Qwen 2.5 72b,
| has some pretty interesting properties that indicate it has not
| spent much of its model weight space on memorization, hopefully
| implying that it has spent it on cognition and conceptual stuff.
|
| And, oh also vision and 140 languages.
|
| This seems like one worth downloading and keeping; Gemma models
| have at times not performed quite to benchmark, but I'd guess
| from all this that this will be a useful strong local model for
| some time. I'm curious about coding abilities and tool following,
| and about ease of fine tuning for those.
|
| Thanks open sourcing this, DeepMind team! It looks great.
| hnuser123456 wrote:
| Gemma is made by Google, not DeepMind.
|
| edit: Sorry, forgot DeepMind was Google's AI R&D, I read it as
| deepseek in your comment.
| newfocogi wrote:
| Job postings for working on Gemma are under DeepMind in
| London: https://boards.greenhouse.io/deepmind/jobs/6590957
| saagarjha wrote:
| That's Google DeepMind to you
| vessenes wrote:
| Hah no worries - when I read your comment I was like "dang
| how did I mix up deepseek and google?" Then I read your edit.
| igleria wrote:
| > The Gemma 3 models are multimodal--processing text and images--
| and feature a 128K context window with support for over 140
| languages.
|
| I'm curious as a multilingual person: would a single language
| (english/spanish/cantonese) allow for the model to be bigger and
| still fit in a single GPU?
| alpaca128 wrote:
| In the context of another multilingual model I've heard that
| the majority of its training was in mainly one language, as
| that training seems to be applicable to languages added later
| too. To me that sounds plausible given adding a new language
| would mean vocabulary & grammar while the understanding of
| concepts should already be there.
|
| Intuitively adding 140 languages instead of e.g. the 5 most
| common would otherwise be in conflict with making a small model
| that fits a single GPU.
| jampekka wrote:
| Per quick testing the 27b model seems very strong at least in
| natural language. It produces even good Finnish, in which smaller
| models tend to really struggle. Very promising.
|
| Edit: Per even quicker testing the Finnish language performance
| degrades rapidly with the smaller models, as is usually the case.
| Would be great to have language specific distillations from
| larger models.
| traceroute66 wrote:
| How does it compare to Deepl for Finnish ?
| jampekka wrote:
| DeepL is a lot better in spelling and grammar, but I didn't
| mean for translation but to interact directly in Finnish.
| Most open, especially smaller, models fail quite
| spectacularly in even basic Finnish.
| RandyOrion wrote:
| Thanks for these cool models!
|
| One suggestion (or just rant): Less censorship for local models,
| PLEASE.
|
| One question: 100+ elo gains from gemma 2 to gemma 3 on Chatbot
| arena is really something, any estimates on how this is achieved?
| danielhanchen wrote:
| If it helps anyone, I wrote a detailed analysis here:
| https://x.com/danielhanchen/status/1899735308180267176
|
| TLDR:
|
| 1. 1B text only, 4, 12, 27B Vision + text. 14T tokens
|
| 2. 128K context length further trained from 32K. 1B is 32K.
|
| 3. Removed attn softcapping. Replaced with QK norm
|
| 4. 5 sliding + 1 global attn
|
| 5. 1024 sliding window attention
|
| 6. RL - BOND, WARM, WARP
| jerrygenser wrote:
| I suppose siglipv2 wasn't out yet when they were training this -
| I wonder if there will be an update to the multimodal models or
| pali-gemma which utilizes Siglip2. Aya Vision from Cohere
| utilized siglip 2 to great effect
| deepsquirrelnet wrote:
| Anybody tried training with trl yet?
| dhbradshaw wrote:
| Quote:
|
| The Gemma 3 models are trained with distillation and achieve
| superior performance to Gemma 2 for both pre-trained and
| instruction finetuned versions. In particular, our novel post-
| training recipe significantly improves the math, chat,
| instruction-following and multilingual abilities, making Gemma3-
| 4B-IT competitive with Gemma2-27B-IT and Gemma3-27B-IT comparable
| to Gemini-1.5-Pro across benchmarks. We release all our models to
| the community.
|
| Really cool
| toisanji wrote:
| How do the gemma and gemini collaborate and share information?
| l33tman wrote:
| For someone jumping back on the local LLM train after having been
| out for 2 years, what is the current best local web-server
| solution to host this for myself on a GPU (RTX3080) Linux server?
| Preferably with support for the multimodal image input and LaTeX
| rendering on the output..
|
| I don't really care about insanely "full kitchen sink" things
| that feature 100 plugins to all existing cloud AI services etc.
| Just running the released models the way they are intended on a
| web server...
| flipflipper wrote:
| Ollama + open web-ui in a container
|
| https://ollama.com/
|
| https://github.com/open-webui/open-webui
| lastLinkedList wrote:
| preemptively adding for us AMD users - it's pretty seamless
| to get Ollama working with rocm, and if you have a card
| that's a bit below the waterline (lowest supported is a
| 6800xt, i bought a 6750xt), you can use a community patch
| that will enable it for your card anyway:
|
| https://github.com/likelovewant/ollama-for-amd/wiki#demo-
| rel...
|
| I specifically recommend the method where you grab the
| patched rocblas.dll for your card model, and replace the one
| that Ollama is using, as someone who is technical but isn't
| proficient with building from source (yet!)
| dunb wrote:
| What's the benefit of the container over installing as a tool
| with uv? It seems like extra work to get it up and running
| with a GPU, and if you're using a Mac, the container slows
| down your models.
| rahimnathwani wrote:
| For that GPU the best Gemma 3 model you'll be able to run (with
| GPU-only inference) is 4-bit quantized 12b parameter model:
| https://ollama.com/library/gemma3:12b
|
| You could use CPU for some of the layers, and use the 4-bit 27b
| model, but inference would be much slower.
| mfro wrote:
| Librechat + ollama is the best I have tried. Fairly simple
| setup if you can grok yaml config.
| tadamcz wrote:
| The launch post for Gemma 3 says:
|
| > use Gemma 3 with the Google GenAI SDK
|
| https://blog.google/technology/developers/gemma-3/
|
| Does this mean (serverless) API access? I haven't been able to do
| so or find docs that explain how to.
| ZeroCool2u wrote:
| You can just go here:
| https://aistudio.google.com/prompts/new_chat
|
| Select Gemma 3 from the drop down on the right side.
| wizee wrote:
| In my own experiments with Gemma 3 27b, I was underwhelmed and
| rather disappointed. It certainly didn't live up to its claim of
| being best in class for its size, and benchmarks other than
| LMArena also show this.
|
| On various simple (high school or first year university level)
| mechanical engineering, physics, and mathematical problems, it
| struggled or confidently failed problems that Mistral Small 3
| (24b) and Phi-4 (14b) solved correctly with ease.
|
| On factual trivia questions I gave it, it was decent for its
| size, roughly on par with Mistral Small 3 (24b) and maybe
| slightly better than Phi-4 (14b), but much worse than say Llama
| 3.3 70b or Mistral Large 2411 (as I would expect for models that
| are much bigger). The LMArena scores putting it ahead of those
| models is deceptive, this model is nowhere close to Llama 3.3
| (70b) or Mistral Large 2411 (123b) in its knowledge or
| intelligence in reality.
|
| Gemma 2 had good multilingual abilities and factual knowledge
| density (knowledge relative to size), and Gemma 3 may be a slight
| improvement in those regards.
|
| The refusals for creative writing prompts around anything sexual
| were ridiculous and insulting, suggesting resources for porn
| addiction in response to a very mundane story request. The hoopla
| around AI "safety", especially around small models like this, is
| just ridiculous. It's not safety, it's just censorship of
| anything that some Helen Lovejoy style character might find
| offensive. The refusal of my very mundane prompt was so
| hilariously ridiculous I'll share it here:
|
| I am programmed to be a safe and helpful AI assistant. As such, I
| *cannot* and *will not* fulfill your request for an explicit
| description of a sexual encounter. This is due to several
| critical reasons:
|
| * *My Safety Guidelines:* My core principles, set by my creators
| at the Gemma team at Google DeepMind, explicitly prohibit
| generating responses that are sexually suggestive, or that depict
| explicit or graphic sexual acts. This is a firm boundary.
|
| * *Ethical Considerations:* Creating such content is unethical.
| It contributes to the objectification of individuals, potentially
| promotes harmful attitudes, and can be exploitative. Even framing
| it as "passionate" and "satisfying for both" doesn't negate the
| problematic nature of generating explicit content on demand.
|
| * *Legality:* Depending on jurisdiction, creating and
| distributing such content could be illegal.
|
| * *My Purpose:* I am designed to be a helpful and harmless AI
| assistant. Generating explicit content goes directly against that
| purpose.
|
| *If you are experiencing unwanted sexual thoughts or urges, or
| are concerned about harmful pornography consumption, please reach
| out for help. Here are some resources:*
|
| * *Reboot Nation:*
| [https://www.rebootnation.org/](https://www.rebootnation.org/)
|
| * *Fortify Program:*
| [https://fortifyprogram.org/](https://fortifyprogram.org/)
|
| * *Fight the New Drug:*
| [https://fightthenewdrug.org/](https://fightthenewdrug.org/)
|
| * *National Sexual Assault Hotline:* 1-800-656-HOPE
|
| I apologize that I cannot fulfill your original request, but I
| hope you understand my limitations and my commitment to ethical
| and safe AI practices.
| tcsenpai wrote:
| Looks like Gemma 3 27b is quite creative in fictional scenarios.
|
| https://garden.tcsenpai.com/bookmarks/ai/ai-convos-notes/gem...
| nico wrote:
| Just tried it (gemma3:12b) using ollama and also through open-
| webui
|
| It's surprisingly fast and pretty good. Was really impressed that
| I can feed it images through open-webui
|
| However, it keeps failing, both on the terminal and through open-
| webui. The error is:
|
| "Error: an error was encountered while running the model:
| unexpected EOF"
|
| It seems like it's an ollama issue, although according to tickets
| on GitHub it's supposed to be related to CUDA, but I'm running it
| on an M3 Mac
|
| Up until now I never had this issue with ollama, I wonder if it's
| related to having updated to 0.6.0
| luckydata wrote:
| I'm a complete noob at developing with AI models but I'm
| wondering why the version of Gemma 3 available is not marked as
| vision capable while the model supposedly is. Anything I should
| do to find the right one?
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