Everyone Said "Sold Out" — GB200 & B300, Available Now on VESSL Cloud
This post was written by the VESSL AI team and includes an introduction to VESSL Cloud. GPU availability, pricing, and configurations may vary depending on timing, capacity, and setup. All spec data is based on official NVIDIA publications.
GB200 and B300 are both available on VESSL Cloud today.
Can't get the GPUs you actually need?
Most AI teams are running into the same problem right now.
Models keep getting bigger. The GPU specs required for training keep going up. But the GPUs you actually need? Nearly impossible to get. Lead times for purchasing the latest NVIDIA GPUs now exceed 12 months for most enterprises.
GB200 and B300 are especially tight. It's not just about the GPU — you need the power, cooling, rack, and network infrastructure to match. NVIDIA has shipped over 3.6 million Blackwell GPUs to the top four cloud providers alone, and CEO Jensen Huang has publicly stated that "Blackwell sales are off the charts, cloud GPUs are sold out."
The question isn't "which GPU is best" — it's "can I start now?"
What makes GB200 and B300 different?
It's not just "newer = better." There's a real inflection point compared to previous generations.
Training gets faster
B300's FP8 performance is approximately 3.5x that of H100. You can run larger batches, longer sequences, in the same amount of time — finishing experiments in roughly half the time.
Bigger models fit on a single GPU
B300 comes with 288GB VRAM — 3.6x the H100's 80GB. The size of models you can load without partitioning changes completely.
Inference throughput jumps significantly
The Blackwell generation delivers up to 4x higher throughput for LLM inference than the previous generation. You can lower the cost per token while maintaining serving quality.
Distributed training bottlenecks shrink
The GB200 NVL72 system uses NVLink to dramatically improve GPU-to-GPU communication bandwidth. If communication has been your multi-node training bottleneck, you'll notice a real difference.
At a glance
| GPU | VRAM | Key advantage | Best for |
|---|---|---|---|
| A100 | 80GB | Stable, cost-effective | Teams prioritizing cost efficiency |
| H100 | 80GB | Balanced training/inference | Time-sensitive large workloads |
| GB200 | 13.5TB HBM3e (system) | Multi-node communication | Ultra-scale distributed training |
| B300 | 288GB | 3.5x perf, 3.6x VRAM vs H100 | High-throughput training & inference |
GB200 B300 H100 A100 GPU spec comparison — VRAM performance and recommended use cases
A GPU cloud you can actually start using today
VESSL Cloud offers both GB200 and B300 on demand — no 12-month procurement wait. Since our availability announcement, teams from enterprises to startups have been reaching out.
But getting access to GPUs is only half the story. Operations matter just as much.
- Smart Pausing — Automatically pauses workspaces when idle. With high-end GPUs, idle costs add up fast — this dramatically reduces your effective spend.
- Flexible scaling — Start small during experimentation, scale up for training, scale back down. Your environment persists across pause/resume cycles.
- End-to-end configuration — GPU selection is just the beginning. We help you design the full setup: multi-node, InfiniBand, storage — tailored to your workload.
- Up to 80% cheaper than hyperscalers — Compared to on-demand pricing on AWS, GCP, and Azure, VESSL Cloud can save you up to 80%. Purpose-built AI infrastructure (neocloud) makes this possible.
Want to learn more about VESSL Cloud's GPU lineup and features? See our full VESSL Cloud overview.
The longer you wait, the more it costs
Demand for the latest GPUs keeps climbing, and supply will remain tight for the foreseeable future. TSMC production bottlenecks and HBM3e memory shortages aren't resolving anytime soon.
Starting now, while capacity is available, is the fastest and most cost-effective decision you can make.
You don't need to have exact requirements figured out. Just tell us where you are, and we'll propose realistic options.
Contact Us About GB200 / B300
FAQ
Should I start with GB200 or B300?
Why is pricing "contact us"?
How much does Smart Pausing actually save?
How is this different from AWS, GCP, or Azure?
References
VESSL AI