4 ms·

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 f

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?

mmarian 4mo ago
Marketing + Pro Serv if I had to take a guess.
XzAeRosho 4mo ago
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 4mo ago
  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
theturtletalks 4mo ago
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.
onlyrealcuzzo 4mo ago
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 4mo ago
  >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.
estearum 4mo ago
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.
browningstreet 4mo ago
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 4mo ago
  re "Unmetered intelligence" goal of Microshaft. Of course it is... This is Windows-Licensing-Level Money Opportunity 2.0.
  - browningstreet 4mo ago
    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.
superchicken099 4mo ago
Gemma overtakes and kills real open-source AI projects, pushing people who would support them towards enterprises like Google
CuriouslyC 4mo ago
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.
accountrequired 4mo ago
edge compute
ppeetteerr 4mo ago
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.
rootusrootus 4mo ago
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 4mo ago
  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 4mo ago
    There is demand for US open models.
    - literalAardvark 4mo ago
      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.
      - deleted 4mo ago
        [deleted]
      - gdiamos 4mo ago
        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.
Mr_P 4mo ago
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 4mo ago
  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
  - jack_pp 4mo ago
    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 4mo ago
      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 4mo ago
        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
deleted 4mo ago
[deleted]
stevenhubertron 4mo ago
My guess is testing for Apple’s Siri replacement and partnership but that’s a total SWAG
beambot 4mo ago
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.
dist-epoch 4mo ago
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.
gen220 4mo ago
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 4mo ago
  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 4mo ago
    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 4mo ago
      Google needs an anti-trust breakup about 10 years ago. They need one more than ever now. This is ridiculously anti-competitive.
      - airstrike 4mo ago
        This is literally competition
staticman2 4mo ago
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.
re-thc 4mo ago
On-device, e.g. Android.
baq 4mo ago
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.
ismailmaj 4mo ago
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.
deleted 4mo ago
[deleted]
mchusma 4mo ago
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__ 4mo ago
  I'm using it for one of my use cases (ocr) on openrouter right now.
  - staticman2 4mo ago
    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.
  - mchusma 4mo ago
    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.
verdverm 4mo ago
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
bachmeier 4mo ago
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 4mo ago
  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.
schipperai 4mo ago
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 https://youtu.be/JNyuX1zoOgU?is=PdzCILyi8SP6cfDr
mugivarra69 4mo ago
[dead]
moffkalast 4mo ago
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.

mmarian 4mo ago

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

XzAeRosho 4mo ago

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 4mo ago
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

theturtletalks 4mo ago

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.

onlyrealcuzzo 4mo ago

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 4mo ago
>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.

estearum 4mo ago

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.

browningstreet 4mo ago

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 4mo ago
re "Unmetered intelligence" goal of Microshaft. Of course it is... This is Windows-Licensing-Level Money Opportunity 2.0.
- browningstreet 4mo ago
  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.

superchicken099 4mo ago

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

CuriouslyC 4mo ago

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.

accountrequired 4mo ago

edge compute

ppeetteerr 4mo ago

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.

rootusrootus 4mo ago

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 4mo ago
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 4mo ago
  There is demand for US open models.
  - literalAardvark 4mo ago
    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.
    - deleted 4mo ago
      [deleted]
    - gdiamos 4mo ago
      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.

Mr_P 4mo ago

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 4mo ago
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
- jack_pp 4mo ago
  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 4mo ago
    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 4mo ago
      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

deleted 4mo ago

[deleted]

stevenhubertron 4mo ago

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

beambot 4mo ago

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.

dist-epoch 4mo ago

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.

gen220 4mo ago

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 4mo ago
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 4mo ago
  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 4mo ago
    Google needs an anti-trust breakup about 10 years ago. They need one more than ever now. This is ridiculously anti-competitive.
    - airstrike 4mo ago
      This is literally competition

staticman2 4mo ago

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.

re-thc 4mo ago

On-device, e.g. Android.

baq 4mo ago

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.

ismailmaj 4mo ago

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.

deleted 4mo ago

[deleted]

mchusma 4mo ago

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__ 4mo ago
I'm using it for one of my use cases (ocr) on openrouter right now.
- staticman2 4mo ago
  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.
- mchusma 4mo ago
  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.

verdverm 4mo ago

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

bachmeier 4mo ago

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 4mo ago
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.

schipperai 4mo ago

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

mugivarra69 4mo ago

[dead]

moffkalast 4mo ago

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.