Video wird geladen...

Video konnte nicht geladen werden

Zur Startseite

📢 Inference is ON 😎 Run any AI model on dedicated GPU hardware, starting today. The GPU is yours while you're on it, the full price is displayed before you commit, and the model is whatever you bring from Hugging Face. Wild concept, we know! 👇

148,796 Aufrufe • vor 21 Stunden •via X (Twitter)

17 Kommentare

Profilbild von Ocean Network
Ocean Networkvor 21 Stunden

H200 at $2.16/hr. Resources bundled for you. Before your session starts, you see exactly what you're booking and what it costs. The node claims your session window upfront, so what you see is what you pay, no shared resources and no billing surprises. That's it.

Profilbild von Ocean Network
Ocean Networkvor 21 Stunden

Four ways to get running: →Curated: pre-tuned model and engine combos, ready in minutes →Custom: any Hugging Face model, every config flag exposed →Services: ComfyUI, JupyterLab, Open WebUI, Open Code →Templates: skip setup, launch into video gen and more Try it:

Profilbild von Ocean Network
Ocean Networkvor 21 Stunden

Once you're live, you get container logs, a countdown on your paid window, and edit-and-relaunch so you can swap the model or engine without losing your endpoint or the time you booked. Every model exposes an @OpenAI-compatible endpoint, so your existing SDKs drop straight in.

Profilbild von Ocean Network
Ocean Networkvor 21 Stunden

That product video you keep putting off? Write a prompt, pick a Template, and it's generating. A good quality 30-second clip takes roughly 20 minutes. Break down the H200 rate and it comes to about $0.72. Book it, run it, own it:

Profilbild von Ocean Network
Ocean Networkvor 21 Stunden

Your first 6 hours of H200 inference are on us Complimentary tokens, no strings, just you and the hardware Claim yours and show us what you can make with it. Let's turn inference ON together!

Profilbild von Richard
Richardvor 20 Stunden

@huggingface you guys really cooked here 🤯 time to try it out

Profilbild von EmmyTruz
EmmyTruzvor 21 Stunden

@huggingface Giving the first 6 hours for free is wild I am checking this out right away

Profilbild von GODEN
GODENvor 20 Stunden

@huggingface Testing this ASAP 🔥 this was worth the wait 🤯

Profilbild von Himas
Himasvor 21 Stunden

@huggingface Finally, this will save me a ton of money on AI tokens

Profilbild von Cranky Killjoy
Cranky Killjoyvor 21 Stunden

@huggingface I definitely need to put this to the test 👀

Profilbild von ΞLB𝐔𝐌𝐏𝐘
ΞLB𝐔𝐌𝐏𝐘vor 20 Stunden

@huggingface H200 inference at $2.16/hr beats what most clouds won't even quote you. Devs can finally run serious models without the bill killing the vibe.

Profilbild von Florida crocodile🍊🐊
Florida crocodile🍊🐊vor 18 Stunden

@huggingface Wow, new stage of efficiency is here!

Profilbild von 𝓣𝓪𝓼𝓱𝓪
𝓣𝓪𝓼𝓱𝓪vor 21 Stunden

@huggingface This is top-notch H200 for $2.16/hr + your own session + no surprise billing. Yeah, inference just got a serious upgrade 🔥

Profilbild von Fairu ✳️
Fairu ✳️vor 20 Stunden

@huggingface Most GPU marketplaces sell vibes. This one is selling a booked window and a bill you can read. That’s the part worth testing.

Profilbild von Lilita
Lilitavor 21 Stunden

@huggingface Running your own models on dedicated GPUs feels really practical

Profilbild von What1slove
What1slovevor 20 Stunden

@huggingface awesome news, wanna try it

Profilbild von Emmanuel
Emmanuelvor 21 Stunden

@huggingface This is exceptional. Time to start running models on GPUs Well-done Ocean Network

Ähnliche Videos

Dylan Patel of SemiAnalysis says a worse GPU with better storage and memory now beats the best chip without them, so buying the newest GPU alone no longer wins inference. So, an AMD GPU with more memory can outperform Nvidia in some cases. "So what we have is we have over $80 million of compute, GPUs from Nvidia, AMD, TPUs from Google, Trainium from Amazon, and we run this benchmark constantly on the newest inference engine, newest drivers, newest PyTorch version, whatever it is." "Every day it runs on an automated CI, and we run it on all the latest Chinese models, from GLM, Zhipu, Moonshot, Kimi, Alibaba, all these models we run." "Initially, when we were benchmarking the difference between these chips and different engines, different schemes for parallelism, we were just running it fixed context length." "But now with Agent X, we've analyzed over $5 million worth of Claude Code traces. This is real production traffic that people have donated to us as well as internally generated. Now we know what the actual agent workload looks like." "And then as we implement that and run those benchmarks, it turns out yes, the chip you're using is very important, but now even more important is how are you handling this memory offload?" "And so while an Nvidia GPU is faster than an AMD GPU in most cases, because AMD GPUs have more memory, they actually end up outperforming in some cases." "Or you can have a worse GPU, but a much better storage solution, and now you can outperform what the best GPU can do without those solutions. So just buying the newest and latest GPU alone doesn't get you the best inference economics." "Actually, you need to layer in all these other innovations including storage and memory." [ Who's the top player on your chart? ] "That really is a difficult multivariable problem. And generally that means you need to have, yes, you need to have the best GPU, a GB300, but you also need to have the best storage solutions. And so I won't spoil who's the best right here, but I will say that storage solutions matter a lot and memory solutions matter a lot, as does your front-end networking. That matters a lot."

Fireside Alpha

178,511 Aufrufe • vor 1 Monat