[ethanpil]

What's Google's business case for releasing open models? Don't get me wrong, I am grateful and appreciative of these releases. I'm trying to understand how it fits into their bigger picture as a for profit company? Are they not helping competitors build on the novel technology they have developed?

Is it simply goodwill and/or marketing? Or am I missing something strategic?

[gen220]

A big part of the frontier labs abilities to charge 80% gross margins on inference is having the cornered resource of frontier models.

If that inference becomes popular and valuable enough that those companies make billions of dollars in profit, those companies could use that profit to fund the building of alternative products and platforms that dis-intermediate google's relationship with the customer.

Google already has an 80% gross margin business, the biggest one in the world. Everybody wants a slice of it.

By offering frontier inference closer to cost and open-sourcing everything that's sub-frontier, they're commoditizing frontier labs' models, which inhibits their ability to durably make high gross margins on inference.

It's a strategic play.

[zozbot234]

A 12B-sized model is a far cry from "frontier inference". That's more like DeepSeek V4 Pro territory which is a 1.6T model. Or for multi-modal models, Kimi 2.6 which is 1T.

[gen220]

at risk of quoting myself... :)

> By offering frontier inference closer to cost *and* open-sourcing everything that's sub-frontier

It's two prongs! One prong is that their frontier inference pricing is significantly cheaper/closer-to-at-cost as Anthropic's.

The subject of this thread is the other prong: offering compelling models that are sub-frontier and self-hostable.

Self-hosting models and at-cost frontier models are the high-end and low-end disruptions, respectively, to Ant/OAI/etc.'s business models.

[echelon]

Google needs an anti-trust breakup about 10 years ago.

They need one more than ever now.

This is ridiculously anti-competitive.

[airstrike]

This is literally competition

[echelon]

1. Google is dumping on the market to weaken OpenAI and Anthropic.

2. Every time you search for Claude or ChatGPT, you get presented with an AdWords bidding war.

3. Google is deploying its models in Search, Docs/Drive/Office, YouTube, Chrome, ...

[boutell]

You're right that it's not literally frontier. But like recent Qwen releases, it is a lot more capable than anybody thought models of this size could be a year ago, like capable enough to set a ceiling on what you can charge for AI for certain applications. Others still clearly justify a stronger model, but this trend may continue, etc.

[ActorNightly]

Don't think its that.

Basically with upcoming spark laptops, the smaller models will likely get fine tuned to interface with google services. Then, Google can essentially make Chromebook software include those models, which is the same use case as android.

And you better believe that they will be collecting user data and building advertising models.

[browningstreet]

This won't replace commercially viable, revenue generating alternatives of their own devising, but it does enable development activity and initiate conversations with enterprises who start with this model but want to do slightly more.

That's my experience right now... my company is all in on a plethora of platform products. Also, Microsoft just yesterday said their goal was "Unmetered intelligence". There's a lot of things that can be enabled by small local models, and those things are part of stacks that can generate revenue in other layers.

[johnnyApplePRNG]

re "Unmetered intelligence" goal of Microshaft.

Of course it is...

This is Windows-Licensing-Level Money Opportunity 2.0.

[browningstreet]

I said they “said” that.

And Google releases another free local model. As did Microsoft.

The actual facts of the day belie your snort take. At least a little bit.

[Mr_P]

Android and Chrome need on-device AI capabilities. Google can't lock down those weights like it can with server-side ML.

So it's easier to just release those models as open source and make it official, since someone would inevitably hack the weights out anyway.

[Aachen]

Could say the same for camera processing in the Pixel Camera app or any other binary someone wants to re-use that comes included in a software distribution (seemingly for 'free'). They can't lock the instructions up on the server so they might as well make the binary be freely distributable?

Companies don't commonly give away executable binaries "just because", why'd they start now for these binary blobs that are the models?

Not that I'm unhappy about it! Yay for open data any day, I'm just not understanding why, at least beyond PR in nerd circles

[lukeschlather]

Binaries are source code outputs, they are copyrightable and patentable. Weights are not copyrightable so people can freely extract the weights and run them. If Google patents any of the novel algorithms here releasing it all freely isn't an impediment to making people license it.

[Aachen]

Weights are not copyrightable?!

Are you sure that isn't about LLMs' outputs? There I know there have been some court cases that say this, but the model itself is a work created in intricate and somewhat creative ways (I hesitate to use the word "creative" here, but would similarly hesitate to label a routine picture of the moon creative whereas pictures basically always have copyright; the bar for creativity is basically an epsilon amount above zero, afaik)

[jack_pp]

Because a model like this can't be as easily obfuscated as image processing. Image processing is a bundle of many moving parts, a lot of functions each with it's own inputs and outputs. A model is a single function which can be easily extracted and reused, in comparison

[Aachen]

Arguably, but that's not the point. Take image (e.g. png) files on a CD-ROM shipped by a game vendor, which can be trivially copied even by my grandma. That doesn't move the game vendor to release them as freely distributable under the Apache license

[jack_pp]

Good point but still, why would Google police this model? If they had a restrictive licence on it do you think it would be worth it for them to enforce it? This way they at least buy some good will and mindshare

[Aachen]

That makes sense to me. Guess one might say the same for game icons and other such files that lay around in disks, but yeah maybe it's as simple as that

[panarky]

> can't lock down those weights

They could lock them down legally which would prevent commercial use, but they choose not to, and they boast about how many tens of millions of times Gemma models have been downloaded by developers.

So there must be more to the rationale than just local model weights getting hacked out of devices.

[goobatrooba]

But these can't be the same model - the model is far too demanding to be part of regular chrome for most people.

[rootusrootus]

Neutering OpenAI and Anthropic would be my guess. Commoditized LLMs won't hurt Google nearly as much as it hurts the LLM-only companies, and so accelerating the inevitable just helps knock out potential future competition in areas where Google -does- make a lot of money now.

[literalAardvark]

I think this plays a part, but the truth is that Google doesn't need to do that, Chinese open models are already doing that by themselves.

So perhaps another part is just Google showing that they can indeed play at the big boys table.

[gdiamos]

There is demand for US open models.

[literalAardvark]

I sincerely wonder why. Chinese censorship is only really relevant if you're doing anti China stuff, which is to say never, while the Western kind of model censorship ( a combination of copyrights and general fairness ) are something everyone's had to work around at least once, even if just for writing an interesting story.

[gdiamos]

It’s about enterprises who care about supply chain risk and having a throat to choke if they have a problem.

Here’s a real example.

I’m in a design meeting talking about a model use case. We have a question about the data pipeline or the prompt format that would benefit from knowing about how the model was trained. The enterprise team lead calls the dev tech engineer from the company who produced the model. He is already in the office and walks into the meeting to answer the question.

[beambot]

Google is one of the few verticalized options in AI: Data, models, cloud services, low-level silicon (TPUs), internal use cases, retail use cases, B2B uses, distribution (browser & mobile), etc.

They rise with the tide of AI adoption. But they gain ground if people opt into Google solutions. And any token sent to a Google model (free or paid) actively punishes their competitors that are then required to spend vast sums to remain bleeding edge.

[onlyrealcuzzo]

If you're an AI lab, you definitely want research teams in this space - as this is where you can most easily iterate and make improvements which you'll then bake into larger, frontier models.

The question is: do you want to release your models, or use them purely for R&D?

Since everyone else is already releasing models of similar qualities, it's hard to say you're shooting yourself in the foot if you join the chorus.

The added cannibalization of releasing them is effectively zero, so the reputational benefits are likely to be worth it.

[hadlock]

>The added cannibalization of releasing them is effectively zero, so the reputational benefits are likely to be worth it.

Nobody would be looking at Qwen if their ~30b class models weren't fantastically good, it's great advertising and builds significant goodwill with developers, who are going to be your biggest advocates.

The other thing is, all these models are already disposable grade, and in a year they'll all be outclassed by The Next Big Thing. "Open" models are less than 18 months behind SOTA right now and I can't imagine that will slow down much over the next two years, they may even begin to close the gap. Nobody even talks about llama 4 anymore despite only being a year old.

[staticman2]

As long as Chinese firms are releasing good open models I imagine there isn't a huge downside for Google to release state of the art small models to compete in the "free" space.

[schipperai]

Demis at YCombinator said that they think its best their edge models are open cause once they are put on device they are vulnerable anyways

https://youtu.be/JNyuX1zoOgU?is=PdzCILyi8SP6cfDr

[baq]

Demis is on record saying they need models on the edge and if they’ll be there they might as well be properly open as they’ll be dumped anyway.

[estearum]

It's to destroy possible footholds for competitors and prevent them from making money in segments that Google doesn't care too much about, but can trivially commoditize.

[mchusma]

I think its even more puzzling because you can't even run Gemma 31b on google cloud, they only let you test it with a rate limit. No way (I can find) to actually pay them to use it.

We saw great results in our usecase using google direct. Moved to Openrouter because google wouldn't let us use it beyond a test.

Then Openrouters performance looked worse, not sure if there was a quantized version or something. So we instead looked at Deepseek v4 Flash, and opted to go for that.

This model would probably be great for a super low cost cloud model, would love to use it in the cloud, Google makes you go elsewhere.

[__mharrison__]

I'm using it for one of my use cases (ocr) on openrouter right now.

[mchusma]

It’s on openrouter. We just noticed performance was worse in a specific agentic app usecase. It’s possible we made an implementation mistake, my main point though is Google is really silly not hosting their own models.

[staticman2]

I tested Gemma 4 31b for OCR and it's very good at it. This makes sense because I also get the best OCR results from Gemini compared to Claude or ChatGPT in my use case.

[XzAeRosho]

Google's MO since always has been to release great products or services for free, position themselves high and then abandon them or just find uses for Enterprise sales.

I'm pretty sure they are doing it because they get some research experience by shrinking and improving these models, and because they know that by doing this they get some good PR among the dev community.

[Aachen]

Google's "free" is and was ad-supported, even if some products now have a paid tier. These models don't include ads. Doesn't seem like the same underlying reason

[ismailmaj]

Gemini is a huge team while Gemma is relatively small. They can totally do this at a loss with no ulterior motive.

They remind me a bit of HuggingFace, create something great then make money … maybe.

[bachmeier]

A strong business case for Gemma includes fine tuning, adding AI to apps that run in the cloud, strengthening Android, shifting unprofitable small AI compute to devices, and harming competitors. The first two would be done using Google's cloud services due to integration with Gemma. I think Google is currently the best positioned company to profit from AI sales to businesses over the next few years, and Gemma is a critical part of the story.

[cknoxrun]

Google is actively, and directly helping companies continuously train use-case specific models based on Gemma 4 foundation. The company gets a model they fully own, trained on internal, sensitive data, and Google scoops up the profits from the training and ongoing compute spend to keep the model up-to-date.

[ppeetteerr]

Isn't Apple about to license some variation of this from google for on-device AI? Maybe it’s their sales pitch to Apple and then they will lock it down.

[moffkalast]

The complete Chinese worldwide domination in this sector would be the alternative, since nobody else is releasing anything meaningful.

Plus every open model undermines their local competition by furthering open research and reduces moats, especially since Gemini as a frontier model isn't really competitive with GPT nor Claude for most applications.

[dist-epoch]

Evangelism for AI. Google is one of the big AI providers.

Eventually the local model is not enough, and you'll upgrade to the big ones.

[theturtletalks]

Maybe they are hedging against a future where local models are just as good as cloud models? Or maybe they can go the Taalas route and start hardcoding Gemma on a chip and hardware manufacturers can use it for local private AI.

[verdverm]

Competition from Chinese alternatives hopefully forces more openness and efficient models. DeepSeek for example is nearly on par and far more resource efficient, good for the planet imo

[CuriouslyC]

They're trying to capture the segment of the market that wants to control the model, with the intent of getting you to run them on Vertex.

[stevenhubertron]

My guess is testing for Apple’s Siri replacement and partnership but that’s a total SWAG

[mmarian]

Marketing + Pro Serv if I had to take a guess.

[re-thc]

On-device, e.g. Android.

[accountrequired]

edge compute

[superchicken099]

Gemma overtakes and kills real open-source AI projects, pushing people who would support them towards enterprises like Google