These kind of limits happen all the time for big clients.

Cloud services like to present the illusion of an infinite amount of compute available at a fixed price per unit, but the reality is if you try to use too much of any service you'll find you have a quota and requests to increase it will fall on deaf ears if the provider doesn't have more of that resource.

Too much of my working life has been spent shoehorning services into less space/compute/ram/spindles or migrations to other data centers to solve such issues.

Given Meta’s current AI situation though, I wouldn’t be surprised if they were trying to do distillation and the capacity story is a cover

Don't know, but Gemini 3.1 flash lite is available for free under relatively generous limits, and it had lots of random interruptions like when I was testing it. (Intermittently responding with errors due to high load.)

We use Gemini for some specific tasks. It is often unavailable due to capacity limits or other downtime.

It's probably the best multimodal model I've worked with (if somebody knows a better one for audio analysis, please let me know!)

My curiosity is not the free AI summaries (which they can opaquely tune as necessary), but instead the renting of TPUs to Anthropic and OpenAI. Many of these contracts were announced last minute and seemed to involve a very desperate Anthropic. Based on the Anthropic/xAI data center contract, they’re willing to pay crazy markup to get immediate access to compute.

I want to know how impacted Gemini has been by that, because that will reveal a lot about their margins and revenue generating first party demand. Each MSFT earnings report they discuss the balance they’re dealing with between supplying GPUs to Azure customers and first party demand.

My pet theory is that Gemini is “losing” the LLM race because they’re preferentially selling the TPUs to competitors, while keeping just enough for themselves to stay competitive and build their own products.

I don't know numbers, but their APIs have a bad uptime in my experience for some models. Too often failure because of "traffic too high".

It's worse than OpenAI or Anthropic. However their lower tier consumer offerings can sometimes be had for <$10/mo on offer and come bundled with other Google services like cloud storage.

This seems less about frontier models and restriction and more just lack of compute capacity to meet demand. This has always been an issue for large clients running on cloud, though not to this extent.

I would imagine there are many situations within Meta's applications where relatively small models can do a good job — sentiment analysis, abusive language detection, characterising users based on their posts, summarising a user's complaint so it can be ignored more efficiently, assessing whether ads are likely to be fraudulent so they can be run more often, etc.

Google tends to be very good at vision and smaller/ edge

> It's interesting that Meta is heavily using Google's models (as opposed to Anthropic or OpenAI)

Who says they aren't? Could be using all of them for "research".

also the only cloud platform, the only workspace, the only cloud drive... it's just standard Google fare

Facebook is ethically challenged and that's putting it very very very mildly. Yes, they have unlimited money, but at a certain point, it comes across like a rich dude at a bar telling a beautiful woman that he'll buy her a diamond bracelet if she will just come over to his place right now. They make my skin crawl.

if you use this as a rough gauge: https://openrouter.ai/models?order=top-weekly

Llama Meta 70b is 50th or so down the list of popular models.

It has 24.1b tokens used in 7 days vs the top models that have trillions or hundreds of billions of tokens.

So practically dead!

Meta's latest model is Spark Muse and not available outside of its products.

https://ai.meta.com/blog/introducing-muse-spark-msl/

Not similar at all, as explained in the article below the headline.

... Because Meta have a contract with Google, are paying for the requests, and are supplying their API key with every request.

I've criticized Antigravity in this same conversation, but Google Gemini is good at coding. Even Flash 3.5 low is good at coding. The problem is that Google isn't hungry anymore and it really really really shows in how much they've botched everything to do with Antigravity.

I am a huge fan of Google Gemini, but Antigravity is not a good product. Just recently I've had issues with:

* Repeated instances of incorrect code insertion that the agent cannot clean up. Sure, version control, but this is often happening in new files that aren't even in version control yet.

* Lost chat history when I close and restart the app.

* Not being able to restore a chat from the history (just saw this last week).

* Overly broad searches that waste time and tokens.

* No vertical scroll bar arrows. WTF?? Doesn't the interface look "flat" enough already? This feels arbitrary and stupid.

* The previous chat prompt takes up a large portion of the vertical space of the chat window, even on a high res display.

When it works Antigravity is excellent. When it doesn't work, it's absolutely horrible. If you check the update history, there are usually just a few items and they're super generic things like "Fixed a bug with text entry.".

I don't see it improving at any kind of reasonable pace, even over the last 6 months As a result, I've mostly relegated Antigravity to a planning tool and it does an excellent job. Or I use it to write prompts that I give to Codex. It definitely can do an excellent job writing code sometimes, but sometimes it also does an absolutely horrible job with not breaking the code when it inserts it. It seems to be terrible at understanding C++ braces. How often? Way too often. I always know it's happening because it prompts me to run Git while it's doing something. LOL, that's how I know that it's broken something.

Codex is definitely way, way, way better. It's not even a contest at this point. Codex never breaks my code. It might not always do what I want, but it's just an order of magnitude better than Antigravity. Antigravity really feels like a comedy of errors at this point. ESPECIALLY from a company with Google's resources.

Counterpoint, 80% of the code I write is not hard and I don't care about it past it being close to a reference implementation