561–570 of 692 posts
For those who would like to know the total and active parameter count of this model: even though Google doesn't disclose the model technicals, we can infer them within relatively tight margins based on what we do know. We know they serve the model on TPU 8i, which we have plenty of hard specs for (so we know the key constraints: total memory and bandwidth and compute flops). We can also set a ceiling on the compute c…
Gemini 3.5 Flash's 2000 token clocks aren't bad. https://clocks.brianmoore.com/
The price is crazy. And I guess Gemini 3.5 pro will have the pricing increment, too. 12 x 5 = 60? It seems like google does want us to use Chinese models.
What exactly are you doing with this that you can’t generate $1.50 of value per million tokens?
They are more willing to wait though, so Chinese models are pretty attractive right now.
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Deepseek V4 (not flash) trippled in price too by the way (from Deepseek). Get used to this pattern. This is what you get for relying on the generosity of billionaires. Keep offshoring your thinking ability to a machine and let me know how competitive you. Hint, you wont be. There's nothing special about being able to use an LLM.
Mate why are you so mad at people upset the price trippeled? It's a fair complaint that people built services using the cheaper ones with the expectation future models would be similarly priced. You can avoid 'offloading thinking' while still building ontop of these models
Everyone could see this coming from miles away, everyone warned that this would happen again and again and again, and it always got dismissed.
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This is not priced at inference cost. My guess: it's the price at which they make more money than if they rent the TPUs to other companies. The Gemini team has had trouble securing enough TPUs for their user's needs. They struggle with load and their rate limits are really bad. Maybe at a higher price, they have a better chance at getting more TPUs assigned?
The cost at such they could rent out the TPUs, i.e. the market rate, is the inference cost. Just because you are vertically integrated doesn't mean you get to discount the one business units products to the other. Doing so discounts the opportunity cost you pay and is just bad accounting.
That depends, if all developers get used to Claude and Codex it will become harder for Google to attract them in the future.
They might lose devs in the long term.
For those who would like to know the total and active parameter count of this model: even though Google doesn't disclose the model technicals, we can infer them within relatively tight margins based on what we do know. We know they serve the model on TPU 8i, which we have plenty of hard specs for (so we know the key constraints: total memory and bandwidth and compute flops). We can also set a ceiling on the compute c…
We've been really impressed with the performance of ~30B parameter class models and how close they are to the frontier from ~6-12 months ago, which begs the question, are the frontier labs really serving 10T parameter models? Seems unlikely. If these Gemini 3.5 numbers are accurate, then I'd wager GPT 5.5 and Opus 4.7 are a lot smaller than people have speculated, too. It's not that frontier labs can't create a 5T+ p…
And serving is not training. For distilling you need to train the big models to have something to be distilled.
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I agree with parent. I'm not sure where your stance is coming from. From what I hear, most enterprise AI deployments are seat-based subscriptions with annual commitments.
Yes, I work at a 50 person startup and even here switching from CC to codex or cursor would be non-trivial for multiple reasons - not just the annual commitment.
Click on "Listen to article", make sure the voice is "Umbriel" and skip to 4:15 - there's a hallucinated part at the end in Russian (I think). On a blog post about the latest and greatest AI model. Oh the irony.
Click on "Listen to article", make sure the voice is "Umbriel" and skip to 4:15 - there's a hallucinated part at the end in Russian (I think). On a blog post about the latest and greatest AI model. Oh the irony.
Yeap it russian, but the whole russian sentence doesn't make any sense, just messed words with no meaning at all :)