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Our eighth generation TPUs: two chips for the agentic era

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Re: Our eighth generation TPUs: two chips for the agentic era

#111

Post by horsawlarway »

surajrmal wrote: post #58
akersten wrote: post #43

Earlier quoted context omitted.

I'd go long Google too if using Gemini CLI felt anything close to the experience I get with Codex or Claude. They might have great hardware but it's worthless if their flagship coding agent gets stuck in loops trying to find the end of turn token.

Gemini CLI isn't a great product unfortunately. While it's unfortunately tied to a GUI, antigravity is a far superior agent harness. I suggest comparing that to Claude code instead.

Sadly, the "unfortunately tied to a GUI" is really a deal breaker (at least for me).

Re: Our eighth generation TPUs: two chips for the agentic era

#112

Post by virgildotcodes »

surajrmal wrote: post #58
akersten wrote: post #43

Earlier quoted context omitted.

I'd go long Google too if using Gemini CLI felt anything close to the experience I get with Codex or Claude. They might have great hardware but it's worthless if their flagship coding agent gets stuck in loops trying to find the end of turn token.

Gemini CLI isn't a great product unfortunately. While it's unfortunately tied to a GUI, antigravity is a far superior agent harness. I suggest comparing that to Claude code instead.

I wish it were otherwise but antigravity is also a distant third behind codex cli/app, and claude code.

3.1 pro is just fundamentally not on the same level. In any context I've tried it in, for code review it acts like a model from 1yr ago in that it's all hallucinated superficial bullshit.

Claude code is significantly less likely to produce the same (yet still does a decent amount). Gpt 5.4 high/xhigh is on another level altogether - truly not comparable to Gemini.

Re: Our eighth generation TPUs: two chips for the agentic era

#113

Post by mlmonkey »

FTA:

> One pod of TPU 8t is 121 ExaFlops; or 121,000 PetaFlops.

Meanwhile, the compute capacity of the top 10 supercomputers in the entire world is 11,487 Petaflops.[1]

I know, I know, not the same flops, yada yada, but still. Just 1 pod alone is quite a beast.

Edit: [1] https://top500.org/lists/top500/2025/11/

Re: Our eighth generation TPUs: two chips for the agentic era

#114

Post by burnte »

fulafel wrote: post #21

"TPU 8t and TPU 8i deliver up to two times better performance-per-watt over the previous generation" sounds impressive especially as the previous generation is so recent (2025). Interesting that there's separate inference and training focused hardware. Do companies using NV hardware also use different hardware for each task or is their compute more fungible?

> Interesting that there's separate inference and training focused hardware. Do companies using NV hardware also use different hardware for each task or is their compute more fungible?

Dedicated hardware will usually be faster, which is why as certain things mature, they go from being complicated and expensive to being cheap and plentiful in $1 chips. This tells me Google has a much better grasp on their stack than people building on NVidia, because Google owns everything from the keyboard to the silicon. They've iterated so much they understand how to separate out different functions that compete with each other for resources.

Re: Our eighth generation TPUs: two chips for the agentic era

#115

Post by mlmonkey »

surajrmal wrote: post #58
akersten wrote: post #43

Earlier quoted context omitted.

I'd go long Google too if using Gemini CLI felt anything close to the experience I get with Codex or Claude. They might have great hardware but it's worthless if their flagship coding agent gets stuck in loops trying to find the end of turn token.

Gemini CLI isn't a great product unfortunately. While it's unfortunately tied to a GUI, antigravity is a far superior agent harness. I suggest comparing that to Claude code instead.

Bad software kills good hardware.

And the converse is true also. I mean, look at NVIDIA. For the longest time they were just a gaming card company, competing with AMD. I remember alternating between the two companies for my custom builds in the 90s and it basically came down to rendering speed and frame rate.

But Jensen bet on the "compute engine" horse and pushed CUDA out, which became the defacto standard for doing fast, parallel arithmetic on a GPU. He was able to ride the BitCoin wave and then the big one, DNNs. AMD still hasn't caught on yet (despite 15 years having gone by).

Re: Our eighth generation TPUs: two chips for the agentic era

#116

Post by kemotep »

NitpickLawyer wrote: post #20
vibe42 wrote: post #16

The pics of the cooling system is pretty good sci-fi / cyberpunk / steampunk inspo. If the whole AI bubble spectularly collapes, at least we got a lot of cool pics of custom hardware!

> If the whole AI bubble spectularly collapes Every other news for the past month has been about lacking capacity. Everyone is having scaling issues with more demand than they can cover. Anthropic has been struggling for a few months, especially visible when EU tz is still up and US east coast comes online. Everything grinds to a halt. MS has been pausing new subscriptions for gh Copilot, also because a lack of capac…

Is the internet bigger or smaller than it was in 1998 compared to today?

Demand for internet and web services is significantly higher today than in 2000 but a bubble still popped. Heck a regular old recession or depression, completely unrelated to AI could happen next year and could collapse the industry. I mean housing is more expensive than ever nearly 20 years after collapsing in the Great Recession.

Re: Our eighth generation TPUs: two chips for the agentic era

#117

Post by hypercube33 »

magicalhippo wrote: post #59
WarmWash wrote: post #44

Whats interesting to note, as someone who uses Gemini, ChatGPT, and Claude, is that Gemini consistently uses drastically fewer tokens than the other two. It seems like gemini is where it is because it has a much smaller thinking budget. It's hard to reconcile this because Google likely has the most compute and at the lowest cost, so why aren't they gassing the hell out of inference compute like the other two? Maybe a…

I've been trying Gemini Pro using their $20-ish Goole One subscription for a couple of months, and I also find it consistently does fewer web searches to verify information than say ChatGPT 5.4 Pro which I have through work. I was planning on comparing them on coding but I didn't get the Gemini VSCode add-in to work so yeah, no dice. The Android and web app is also riddled with bugs, including ones that makes you los…

You're supposed to download the antigravity VSCode fork and use that and it's rough at best I think. Hey free opus tokens though.

Re: Our eighth generation TPUs: two chips for the agentic era

#119

Post by jauntywundrkind »

WarmWash wrote: post #44

Whats interesting to note, as someone who uses Gemini, ChatGPT, and Claude, is that Gemini consistently uses drastically fewer tokens than the other two. It seems like gemini is where it is because it has a much smaller thinking budget. It's hard to reconcile this because Google likely has the most compute and at the lowest cost, so why aren't they gassing the hell out of inference compute like the other two? Maybe a…

I'm 50% convinced that the main lift in GLM-5 over GLM-4.7 was that it was much more willing to use tokens. I had the hardest time getting 4.7 to read enough source code to actually know what it was doing, but once I convinced it to read, it was pretty capable.

Being thrifty can be good! But it also can mean your system is not reflecting sufficiently, is not considering enough factors, isn't reading enough source code.

We are still firmly in "who really knows" territory. I have mixed feelings about token spendiness vs thrift, is all.

Re: Our eighth generation TPUs: two chips for the agentic era

#120

Post by rtaylorgarlock »

delbronski wrote: post #118

I’ve been using Gemini with Junie (jetbrains attempt at Claude code). While Junie is nowhere near as good as Claude Code, it is way ahead of the current Google tooling. I get quite good consistent results for pretty cheap with this combo.

Do you think that Junie specifically inside the context of jetbrains IDEs and tooling matches the competitors?
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