Loading video...

Video Failed to Load

Go Home

📢 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 views • 23 hours ago •via X (Twitter)

17 Comments

Ocean Network's profile picture
Ocean Network23 hours ago

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.

Ocean Network's profile picture
Ocean Network23 hours ago

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:

Ocean Network's profile picture
Ocean Network23 hours ago

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.

Ocean Network's profile picture
Ocean Network23 hours ago

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:

Ocean Network's profile picture
Ocean Network23 hours ago

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!

Richard's profile picture
Richard22 hours ago

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

EmmyTruz's profile picture
EmmyTruz22 hours ago

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

GODEN's profile picture
GODEN21 hours ago

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

Himas's profile picture
Himas22 hours ago

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

Cranky Killjoy's profile picture
Cranky Killjoy22 hours ago

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

ΞLB𝐔𝐌𝐏𝐘's profile picture
ΞLB𝐔𝐌𝐏𝐘22 hours ago

@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.

Florida crocodile🍊🐊's profile picture
Florida crocodile🍊🐊20 hours ago

@huggingface Wow, new stage of efficiency is here!

𝓣𝓪𝓼𝓱𝓪's profile picture
𝓣𝓪𝓼𝓱𝓪22 hours ago

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

Fairu ✳️'s profile picture
Fairu ✳️22 hours ago

@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.

Lilita's profile picture
Lilita22 hours ago

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

What1slove's profile picture
What1slove22 hours ago

@huggingface awesome news, wanna try it

Emmanuel's profile picture
Emmanuel22 hours ago

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

Related 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 views • 1 month ago