NVIDIA B300 GPU Cloud
Reserve NVIDIA B300 (Blackwell Ultra) capacity on VESSL Cloud — up to 288GB HBM3e and FP4 acceleration for the largest models and high-concurrency reasoning inference.
- GPU memory
- up to 288GB HBM3e
- Memory bandwidth
- 8 TB/s
Technical specifications
- Architecture
- Blackwell
- GPU memory
- up to 288GB HBM3e
- Memory bandwidth
- 8 TB/s
- NVLink
- 1.8 TB/s
- FP8 (Tensor)
- 10 PFLOPS
- FP4 (Tensor)
- 20 PFLOPS
- Max TDP
- 1,400W
- GPUs per node
- 8 (HGX B300)
*Peak performance with sparsity, per NVIDIA official specs. Final specs may vary by node configuration.
Pricing & availability
What's the B300 best for?
Largest-model training
Up to 288GB HBM3e per GPU and 1.8 TB/s NVLink keep trillion-parameter models resident with fewer partitions and less communication overhead.
Reasoning & long-context inference
Blackwell Ultra's huge HBM3e holds massive KV caches; ~1.5× FP4 vs B200 serves agentic and reasoning workloads at high concurrency.
Consolidate inference fleets
More memory and FP4 throughput per GPU means fewer GPUs for the same serving capacity — lower cost-per-token for large deployments.
Compare NVIDIA data-center GPUs
| H100 Hopper | H200 Hopper | B200 Blackwell | B300 You're viewing | |
|---|---|---|---|---|
| Architecture | Hopper | Hopper | Blackwell | Blackwell |
| GPU memory | 80GB HBM3 | 141GB HBM3e | 192GB HBM3e | up to 288GB HBM3e |
| Memory bandwidth | 3.35 TB/s | 4.8 TB/s | 8 TB/s | 8 TB/s |
| FP8 (Tensor) | 3,958 TFLOPS | 3,958 TFLOPS | 9 PFLOPS | 10 PFLOPS |
| Access | from $2.39/hr | Available on request | Available on request | Available on request |
| Best for | Cost-efficient training & inference | Long-context & large-model inference | Frontier-scale training (FP4) | Largest models & reasoning inference |
Why industry-leading teams run GPUs on VESSL Cloud
No waitlists
Access capacity across clouds through one platform — skip quotas and procurement.
Scale to multi-node
Spin up a single GPU or scale to large multi-node clusters over high-speed InfiniBand — as much as you need.
Transparent pricing
Spot, on-demand, and reserved options with pay-as-you-go billing.
Enterprise-ready
SOC 2 Type II compliance, with dedicated support for production AI.
Frequently asked questions
How do I get access to NVIDIA B300 GPUs?
B300 (Blackwell Ultra) capacity is allocated on request. Talk to our team and we'll secure capacity matched to your timeline.
How much memory does the B300 have?
HGX B300 (Blackwell Ultra) scales to up to 288GB HBM3e per GPU — talk to our team for current node configurations and availability.
What's the difference between the B200 and B300?
The B300 (Blackwell Ultra) increases memory to up to 288GB HBM3e (vs 192GB on the B200) and adds roughly 1.5× FP4 compute — built for the largest models and high-concurrency reasoning inference.
Is the B300 better for training or inference?
Both. FP4/FP8 acceleration and up to 288GB HBM3e make the B300 ideal for frontier-scale training and high-throughput, low-latency reasoning inference.
Can I reserve a full B300 cluster?
Yes. We provision HGX B300 nodes (8 GPUs each) with high-speed InfiniBand, scaling from a single node to large multi-node clusters.
Explore other GPUs
Different workload? Pick the GPU that fits your memory, throughput, and budget.
Blackwell with 192GB HBM3e and FP4 acceleration — for frontier-scale training and high-throughput inference.
View detailsSame Hopper compute as the H100 with 141GB HBM3e — for long-context LLMs and larger models without sharding.
View detailsThe proven Hopper workhorse — best price/performance for training, fine-tuning, and inference. From $2.39/hr.
View detailsStop chasing GPUs.
Start shipping AI.
Unified access to GPU capacity across providers. One platform, transparent pricing.
- Start in minutes
- Scale to multi-node clusters
- High availability built-in
- 24/7 support available