NVIDIA Blackwell — B200 rental
Most serious budgets in the Blackwell generation land on the B200. The card offers near-flagship throughput without the scarcity, which is exactly why we built our rental around it. You can rent B200 GPU clusters from TheAI as dedicated eight-card nodes, assigned within days of the first call. The rate is monthly and agreed before you sign.
180 GB
HBM3e per card
1,440 GB across the 8-card node
8 TB/s
Memory Bandwidth
Keeps large models fed, no read stalls
Native FP4
5th-gen Tensor Cores
~2x inference throughput vs FP8
In Days
To Assignment
Dedicated node after the first call
High-Performance Computing
The B200 packs two dies and 208 billion transistors into a single GPU built on the Blackwell architecture. Fifth-generation Tensor Cores add native FP4 support, roughly doubling inference throughput on quantized models compared with FP8.
The memory system matters just as much: at about 8 TB/s, the card keeps large models fed where older generations stalled on reads. B200 rental at TheAI starts at eight dedicated cards, on the same monthly terms as everything else we run.
208B transistors
Two dies on Blackwell
FP4 Tensor Cores
~2x inference vs FP8
~8 TB/s memory
No read stalls at scale
Eight dedicated cards, single tenant, bare metal.
180 GB HBM3e per card — most open-weight models fit on one node
Fifth-generation NVLink at 1.8 TB/s per GPU
Root access from the driver up, nothing shared
Reference system
The DGX B200 is NVIDIA's reference eight-GPU system, and it's a useful yardstick for what an NVIDIA B200 GPU cloud instance should deliver. Note the GPU memory: 180 GB per card, or 1,440 GB per node.
GPUs
8× NVIDIA B200
Tensor Core GPUs
GPU memory
1,440 GB
HBM3e per node · 180 GB/card
Memory bandwidth
8 TB/s
per GPU
AI performance
72 / 144 PFLOPS
FP8 training · FP4 inference
GPU interconnect
1.8 TB/s
5th-gen NVLink per GPU
CPUs
2× Xeon 8570
112 cores total
System memory
up to 4 TB
DDR5
Networking
8× ConnectX-7
400 Gb/s each
Storage
~30 TB
local NVMe (reference build)
Memory decides what fits on a card, and bandwidth decides how fast it runs. Our B200 GPU rental service covers both, which is why the list below stretches from AI training to generative AI serving.
FP4 throughput and fast memory make the B200 a strong default for the whole model lifecycle.
With 180 GB per card, most open-weight models fine-tune on a single node.
Agent fleets run around the clock and need inference capacity that holds under bursty tool calls.
Simulation workloads that pair AI surrogate models with classic numerical methods map well onto Blackwell.
Retrieval-augmented generation lives and dies on latency; fast memory keeps embedder and generator responsive.
Diffusion and video models are memory gluttons; 180 GB per card means fewer compromises.
One number, agreed up front
B200 GPU rental at TheAI is priced as one monthly rate, agreed before you sign, covering the whole dedicated cluster.
Quoted per project
The figure depends on cluster size and rental term, so we quote per project. GPU cloud pricing elsewhere comes with a calculator full of sliders. Ours is a single number that stays flat regardless of utilization. Talk to our team, and you'll have that number before any paperwork.
Get started
Launch your B200 instance today. Talk to our team and you'll have the number before any paperwork.
A short, human process
You rent B200 capacity through one conversation and one agreement; hardware follows within days.
Start with the workload. Know the model size and training plan, and we confirm the cluster on the first call. If you don't, our engineers help you size it — from a single node to custom clusters spanning several nodes.
Once the agreement is signed, we assign your dedicated cluster and hand over root access. The machines run bare metal, single tenant, with your own stack from the driver up. Nothing changes underneath you mid-training.
From here it's your environment. Load datasets onto local NVMe SSD storage, pull your containers, and launch the run. When you rent B200 GPUs from us, the engineers who set up the cluster stay on call around the clock.
A dedicated cluster lands as a predictable monthly rate; the capex conversation never happens.
Pay month by month, no long-term commitment. Leaving is as simple as not renewing.
Run Blackwell this quarter, while a purchase order for the same cards sits in procurement.
Start at eight cards and grow to multi-node clusters inside the same agreement.
A fixed rate turns cost per token into a spreadsheet exercise — no usage meters underneath.
Bare metal and root access, your own stack from driver to container runtime.
Memory and bandwidth decide the fit. Here's the B200 next to the cards teams cross-shop.
B200 GPU rental at TheAI comes with the terms the rest of our platform runs on: dedicated bare metal, a single monthly rate, root access, and humans on call.
Your cluster is assigned within days of the first call, while quota requests at hyperscale clouds are still pending.
You see one monthly rate before you sign, while hyperscale invoices arrive itemized by the hour with line items nobody ordered.
Cards in your cluster talk over a high-bandwidth interconnect, so gradient syncs keep pace with Blackwell compute.
24/7 support from engineers who run GPU clusters — a stuck driver gets the same attention as a scaling plan.
Your cluster is single-tenant by design, so data and model weights never share hardware with anyone.
While Blackwell capacity sits on waitlists worldwide, TheAI already has B200 clusters in our data centers.
TheAI prices NVIDIA B200 rental as one monthly rate for the whole dedicated cluster, agreed before you sign. The figure depends on cluster size and term, so we quote per project. There are no pricing tiers to decode; the quote is the price.
One conversation, one agreement, hardware within days. Tell us the model and we'll size the cluster on the first call.