Quanta @QuantaCompute

$QUANTA is building wallet friendly compute for the next wave of onchain apps. Agents need runtime, indexers need reliable workers, inference needs GPUs, and developers need a simple way to deploy without becoming cloud operators. We are starting with external providers to validate demand, compare pricing and route jobs intelligently. Providers will remain in the network for overflow, regional coverage and competitive pricing, while the long term goal is to gradually build our own infrastructure underneath the routing layer. If funding and usage support it, our first owned machine will be a rackmount RTX PRO 6000 Blackwell Server Edition with 96GB VRAM, built for agents, inference, rendering, simulation and other workloads. It will be hosted in a Tier III datacenter, with redundant power, NVMe storage, remote management and proper datacenter infrastructure. Our preferred first location is a Tier III facility in Singapore. Start small. Prove demand. Own infrastructure when the numbers make sense. Then scale from real usage.

What’s coming for $QUANTA? $QUANTA integrations We’re working toward integrating $QUANTA directly into the platform, allowing users to pay for compute at lower rates than currently available. NVIDIA stock airdropas Once we’ve reached our key milestones and built a sustainable foundation, we plan to explore using a portion of protocol fees to distribute NVIDIA stock to eligible $QUANTA holders. Owned infrastructure Our long term goal is to move beyond simply aggregating compute. We plan to acquire our own hardware and deploy it in professional data center infrastructure, giving $QUANTA greater control over capacity, availability and pricing. This is only the beginning.

A100 PCIe compute at $0.34/hour. A100 SXM4 at $0.30/hour. L40S at $0.28/hour. Quanta isn’t trying to compete on a single GPU category. The goal is a broad compute market where builders can choose the hardware that actually fits the workload instead of overpaying for whatever their cloud provider happens to offer.

An A100 SXM4 at $0.30/hour puts serious datacenter compute within reach of smaller teams. Train, fine-tune and run demanding models on hardware built for high-throughput AI workloads, without needing an enterprise-sized infrastructure budget just to start experimenting.

An RTX A6000 at $0.24/hour gives you 48GB of VRAM without paying the usual workstation premium. Run larger models, heavier inference and memory intensive workloads that quickly outgrow consumer GPUs. More room for the model, less money disappearing into infrastructure.

An RTX 5090 at $0.18/hour changes what you can afford to experiment with. Run inference, test models, deploy agents, kill what doesn’t work and spin up the next idea without watching a cloud bill explode.

We’ve claimed 100% of the fees generated and used them to buy back directly into the chart We want to be fully transparent with our actions and our plans for the project To further align ourselves with the community, we’ll also be locking the full amount bought back for 6 months app.sablier.com/vesting/stream…

The RTX 4090 is still one of the best workhorses for AI workloads. Quanta brings it down to $0.16/hour, compared with significantly higher rates across traditional and specialized compute providers.

An L40S at $0.28/hour is built for the workloads modern AI products actually need. Inference, generative AI, graphics and multimodal applications. When compute runs continuously in production, hourly pricing matters. Cutting that cost changes the economics of the entire product.

Whenever $QUANTA tokens are used to buy compute; 50% of these tokens will be burned immediately. Other 50% will be used for purposes such as CEX listings in the future. Simple, transparent and fully onchain

You can now rent GPU compute directly through our website using $QUANTA, USDG, or ETH. Simple, accessible compute with multiple payment options.

NVIDIA Stock Airdrop Once $QUANTA reaches its core milestones and establishes sustainable protocol revenue, we plan to allocate a portion of protocol fees toward airdropping NVIDIA stock to holders. This won’t happen immediately. Our priority is building the infrastructure, proving demand, and reaching sustainable revenue first. NVIDIA is a natural fit for $QUANTA given our focus on GPU compute. Our goal is to explore how real-world assets can be distributed to onchain holders through the infrastructure we’re building. More details on eligibility and implementation will be announced when we’re ready.

The $QUANTA Effect What You Actually Pay vs. What You’d Pay Elsewhere GPU compute is expensive. Traditional cloud providers can charge several times more for the exact same GPU-hour. AWS costs $4.10 per GPU-hour. AWS costs almost 14x more than $QUANTA, while even the cheapest alternative in this comparison costs more than 5x as much. That’s not a small discount. It’s a fundamentally different price point for the same compute.

The official $QUANTA token is not live yet. The official token address and launch announcement will be posted exclusively on this official X account. Please beware of fake tokens, contracts, and impersonators. Do not buy or interact with any $QUANTA token until it is officially announced here.

Hello @feeldotcash 👀

x.com/i/article/2088…

AI infrastructure has a pricing problem. The hardware exists, demand exists, but compute is still fragmented across providers with wildly different rates. Quanta turns that fragmented capacity into one marketplace where GPUs compete for workloads. That competition is what should determine the price of compute.

Why Robinhood Chain Matters The interesting part of $QUANTA isn't just the compute marketplace It's where the compute infrastructure is being positioned Robinhood Chain If the ecosystem continues attracting developers and applications, the infrastructure supporting those applications becomes increasingly important. That creates a natural relationship: Developers need compute → applications create demand → ecosystem growth increases workloads → compute infrastructure becomes more valuable. $QUANTA is building into that cycle from the beginning. The thesis is relatively simple: Help the ecosystem build more by making one of its core infrastructure requirements easier to access.

@QuantaCompute will it save more water? 👀