Green ComputeEnterprise inference.
Two SKUs. One environment.
We sell inference. Enterprise grade, production ready, metered by the token. Rent by the hour or the month. No setup, no driver roulette, no matrix of six GPU generations to pick from. Plug in and compute.
Every node is the same node.
Same card: RTX 4090 or RTX 5090. Same rack. Same drivers. Same firmware. Same container runtime. You point a workload at Green Compute and you get the same environment on every instance, in every region, on every request. That is the boring promise, and it matters more than anything else when you're running inference for a real business.
The interesting promise is the power bill. The hardware serving your inference sits on working UK farms that already produce electricity from on-farm biogas. Those farms run as miners on the subnet. Methane stops getting vented. Farmers earn. Your inference gets cheaper.
Three things, in the order you care about them.
Most inference clouds pay grid rates for power and mark it up. The miners on subnet 110 burn electrons that were already being produced to run a dairy, at costs closer to farm-gate than grid-gate. That gap lands on your bill.
Two SKUs, and nothing else. Every instance is interchangeable with every other instance. Procurement negotiates against a single SKU. Security audits a single image. Ops pages on a single topology.
Dairy farms produce methane whether we show up or not. Methane is ~30× worse than CO₂ over a century. Capturing it, burning it, and running tokens on the result is one of the few honest wins available in compute today.
Humans answer the phone.
Try the hardware first.
Enterprise compute shouldn't feel like a six-week procurement dance with a quota manager who won't return your emails. We run this differently.
We have an in-house tech team that walks you through onboarding end to end, and a live sales team you can call to talk through your compute needs before anything gets signed. Real humans, real responses. No ticketing queue. No faceless portal. No six-week procurement dance with a quota manager who won't return your emails. AWS and Oracle have forgotten what this feels like. We haven't.
If you want to benchmark your workload on real hardware before a contract starts, we'll set you up with remote access to a node. Bring your model, bring your numbers, see what the network actually does. Then decide.
Why 4090s and 5090s, and nothing else.
Inference in 2026 wants memory bandwidth, low-precision tensor throughput, and price per watt. The 4090 and 5090 win every one of those fights at a fraction of the capital cost of a data-center SKU.
- · 24 GB GDDR6X
- · 1008 GB/s bandwidth
- · Mature kernel ecosystem
Enough tensor throughput to serve a 70B model quantised sensibly, at a power envelope a farm transformer can feed comfortably. Two years of open-source kernels tuned against it — the software is mature, throughput is known, and the unit economics are honest.
- · 32 GB GDDR7 (Blackwell)
- · FP4 tensor cores
- · ~2× throughput at FP4
FP4 tensor cores are the single biggest thing to happen to inference cost per token this decade. For FP4-quantised models, throughput roughly doubles per card while power stays in the same envelope. Best per-token-per-watt card you can buy today without a seven-figure cheque.
Why we skip the data-center SKUs. H100s and B200s are optimised for training. They carry a price premium inference workloads do not pay back. If you're running a forward pass, you want bandwidth and low-precision throughput per dollar and per watt. The 4090 and 5090 win on both.
Plug in and compute.
OpenAI-compatible chat completion API, streaming responses. Drop the endpoint into whatever you already run and it behaves the way you'd expect. When a miner goes offline, another picks up the workload without your application noticing, because the node it lands on is the same node it left.
$ curl https://api.green-compute.com/v1/chat/completions \ -H "Authorization: Bearer $GC_KEY" \ -H "Content-Type: application/json" \ -d '{"model":"meta-llama/Llama-3.1-8B-Instruct", "messages":[{"role":"user","content":"hi"}]}' { "id":"chatcmpl-...","choices":[{"message":{"role":"assistant","content":"Hi!"}}] }
Talk to sales.
Enterprise contracts, dedicated capacity, token-metered billing. We'll get you live quickly.