103 launches on Arc. In just 2 days. CUDAPAD is turning token launches into real compute: > 33 GPUs backed. > 1 pair asset. Every trade buys GPU-hours. Launch a token. Back compute. Put GPUs to work.

Every token launch on CUDA get their charts on @GeckoTerminal

Launch your token on Arc. Back it with real GPU compute. Pick the GPU behind your token: → NVIDIA B300 SXM 288GB → NVIDIA GB200 NVL72 186GB → NVIDIA B200 SXM 180GB → AMD Instinct MI355X 288GB → NVIDIA H200 SXM 141GB → AMD Instinct MI325X 256GB Every token launches directly into a Uniswap v4 position, paired with USDC. Your token isn’t just launched It’s backed by compute. Launch on @arc.

Launch your token on @arc in less than a minute. From there, the flywheel runs itself. Every creator fee is automatically routed to GPU backing turning token activity into real compute for any purpose. Token launch → fees → GPUs → compute. And we’re about to ship a massive update for both sides of this loop.

The First GPU-Backed Launchpad on @arc. Pick a GPU from the catalogue, launch a token against it on @circle L1 through @Arguspad, quoted in native USDC. No launch fee. Gas only. cudapad.com/launch

New look on cudapad and we are coming to something huge this week Cudapad’s homepage is now the board and BIG UPDATE will release asap. King of the Hill sits up top. Contenders ranked beside it. Top tokens by market cap below. Then every token backed by a GPU. No one picks the crown. It’s computed directly from the bonding curve whoever is closest to graduation takes the hill.

One day in. 14 tokens launched on CudaPad since yesterday. every one of them is backed by a specific GPU, from a GB200 down to a 3090. 6 different GPUs are now backed. 2 pair assets in use: ETH and $NVDA. each of those launches pays a 2% creator fee on every trade, and half of that fee buys GPU-hours anyone on the platform can run jobs on. launch a token. back a GPU. fund the hours. cudapad.com/explore

Assuming you haven't tried the console yet: any wallet that has launched a token can run a job on any GPU on the platform, paid by the shared pool. launch once, then pick a GPU here: cudapad.com/compute

We seeded the GPU pool with $1,500 today so day-one launchers can run jobs right away. 14 launches, 6 GPUs backed, $1,500 available to spend. Fees take over from here.

We pride ourselves on being one of the first building GPU infrastructure on Robinhood Chain. Very few people are building in this sector here, even though compute is the most capital-hungry part of AI. The goal is simple: more GPU access, for more people, funded by markets that are already active.

NVIDIA's DSX pitch is that the constraint on AI is no longer chips. it's the megawatts feeding them, and how well a factory adapts when the grid changes. That's the supply side. the question that gets less attention is who pays for the hours a GPU actually runs. Today most of it is a cloud bill, or a fund raise. We're testing a third way. $DSX went up on CudaPad this morning: a token backed by a B300 SXM 288GB, paired with $NVDA. its trading fees buy hours on that GPU, and anyone on the platform can run jobs on them.

CudaPad × Pons. Every token launched on CudaPad is a @ponsdotfamily token on Robinhood Chain. Which means every launch shows up on the pons dashboard the second it goes live: curve, holders, graduation, all of it. One launch, two homes. Trading → Creator fees → GPU-hours → Jobs Launch a token. Trade onchain. Fund a GPU. cudapad.com/launch

if you've been around GPUs for as long as we have, you know how this started. in 2007 Nvidia shipped CUDA and turned a graphics card into a general-purpose computer. every model you use today runs on that idea. then DePIN took the next step. Render, Akash, io.net and the marketplaces that followed proved that spare GPUs could be pooled and rented onchain. what nobody did is let a token pay the bill. every GPU marketplace still ends at the same place: someone opens a wallet and pays per hour. we want to carry that idea forward on Robinhood Chain. a token is launched, it trades, and the fees from that trading buy the GPU-hours themselves. CUDA made the card programmable. DePIN made it rentable. we want to make it fundable.

We have limits in place to prevent anyone from draining the pool. every job is capped at 8 hours, a wallet can run 2 jobs at a time, and every job is billed on the actual hourly rate of the GPU it ran on. access is shared without letting a single wallet burn through the balance.

Adding [higher job limits for wallets that have launched more than one token / more GPUs to the catalogue / x], will be pushed out in a few minutes.

Launch a token backed by an H100 and paired with $NVDA. Same curve, different pair. The fees come in whatever you paired with, and they still buy GPU-hours. 13 pairs live: ETH, USDC, EURC, TSLA, NVDA, AAPL, MSTR, HOOD, COIN, SPY, QQQ, and two gold tokens. cudapad.com/explore?quote=nv…

As models get bigger, the scarce resource is not intelligence. It is the GPU underneath it. Now a token's trading activity can pay for one.

Launches are now enabled. pick a GPU, name your token, one transaction. launch here: cudapad.com/launch

DEX PAID $CUDA