NVIDIA’s Blackwell family – the B200, the Blackwell Ultra B300, and the rack-scale DGX B300 system – sits at the center of AI infrastructure spending in 2026. Buyers are juggling on-prem capex, cloud GPU-hour rates, and rapidly shifting availability. This breakdown collects the latest verified pricing signals so you can benchmark quotes against the live market.

DGX B300 System Pricing

NVIDIA positions the DGX B300 as the Blackwell Ultra system built for AI reasoning workloads. As of Q1 2026, an 8-GPU DGX B300 system is anchored at $300,000–$350,000, which works out to roughly $37,500–$43,750 per GPU at the system level.

What the System Price Includes

The 8-GPU configuration bundles the GPUs with NVIDIA’s interconnect fabric, system memory, and the integrated software stack. The per-GPU figure above is an effective rate derived from the full $300,000–$350,000 system price – individual B300 modules are not sold standalone at that effective rate.

Why DGX B300 Commands a Premium

Blackwell Ultra is designed for AI reasoning – workloads where long chains of inference and large context windows dominate the compute profile. The DGX B300 is NVIDIA’s reference platform for that class of workload, which is why it sits at the top of the Blackwell capex stack rather than competing on raw $/FLOP with the standard B200.

B200 Cloud GPU-Hour Pricing

For teams that prefer to rent rather than buy, the B200 is widely available on the cloud – but the spread between providers is much wider than earlier summaries suggested. As of May 2026, live B200 GPU-hour rates range from $2.99 to $27.04 per GPU-hour depending on the provider, contract terms, and region.

B200 Provider Price Comparison

Provider	B200 Price (per GPU-hour)	As of
Vultr	$2.99	May 2026
AWS	$10.30	May 2026
Azure	$27.04	May 2026

Reading the Spread

The roughly 9x gap between the cheapest and most expensive B200 listings reflects more than raw silicon cost. Hyperscaler list pricing typically bundles managed networking, enterprise SLAs, support, and integration with the rest of the provider’s stack. Specialty cloud providers like Vultr compete on bare GPU-hour cost and accept narrower margins. For workloads that don’t need hyperscaler-grade SLAs, the difference compounds quickly – a single B200 running 24/7 for a month at $2.99/hr costs about $2,153, versus roughly $19,469 at $27.04/hr.

B300 Cloud Pricing

B300 availability on the cloud is newer than B200, but concrete pricing signals are now landing. In April 2026, B300 spot pricing was documented as low as $2.45 per GPU-hour, with dedicated B300 capacity at around $6.80 per GPU-hour, and premium managed DGX B300 offerings in the $12–$18 per GPU-hour range.

Spot vs Dedicated vs Managed DGX

B300 Tier	Price (per GPU-hour)	Reference Date
Spot	$2.45	April 2026
Dedicated	$6.80	April 2026
Managed DGX B300 (premium)	$12–$18	April 2026

What the Tiering Means in Practice

Spot pricing at $2.45/hr is the cheapest documented B300 rate to date, but spot capacity can be reclaimed and is best suited to fault-tolerant training jobs and batch inference. Dedicated B300 at $6.80/hr targets teams that need reliable scheduling without paying for a managed DGX wrapper. The $12–$18/hr managed DGX B300 tier prices in the full software stack, networking, and operations – appropriate for reasoning workloads where the DGX reference architecture is part of the value, not just the GPU.

B200 vs B300 vs DGX B300 Cost Comparison

Side-by-Side Pricing Summary

Product	Cloud Low (per GPU-hour)	Cloud High (per GPU-hour)	System-Level Pricing	Reference Date
B200 (cloud)	$2.99 (Vultr)	$27.04 (Azure)	–	May 2026
B300 (cloud)	$2.45 (spot)	$18 (managed DGX)	–	April 2026
DGX B300 (8-GPU system)	–	–	$300,000–$350,000 (~$37,500–$43,750/GPU)	Q1 2026

How to Choose

The cheapest documented Blackwell hour is currently a B300 spot instance at $2.45/hr – slightly below the lowest B200 cloud listing at $2.99/hr – which inverts the usual assumption that newer silicon always rents for more. The inversion is tier-driven, not silicon-driven: spot B300 capacity is being released at aggressive promotional rates while dedicated and managed B300 tiers remain meaningfully more expensive than equivalent B200 capacity. For buyers evaluating capex, the DGX B300 system price of $300,000–$350,000 is the relevant anchor; for cloud-first teams, the per-hour ladder above is what matters.

May 2026 Update

As of May 2026, three pricing signals are worth flagging:

• DGX B300 8-GPU system pricing is now anchored at $300,000–$350,000 (Q1 2026 reference), implying $37,500–$43,750 per GPU at the system level.
• B200 cloud rates are spreading wider, not converging – May 2026 listings span $2.99 at Vultr to $27.04 at Azure, with AWS in the middle at $10.30.
• B300 spot pricing was documented as low as $2.45/hr in April 2026, with dedicated at $6.80/hr and premium managed DGX B300 at $12–$18/hr.

Frequently Asked Questions

How much does a DGX B300 system cost?

As of Q1 2026, an 8-GPU DGX B300 system is anchored at $300,000–$350,000, which implies roughly $37,500–$43,750 per GPU at the system level.

What is the cheapest B200 cloud rate in May 2026?

The lowest documented B200 GPU-hour rate in May 2026 is $2.99 per GPU-hour at Vultr. The same market includes $10.30 at AWS and $27.04 at Azure.

How cheap can B300 cloud pricing get?

The cheapest documented B300 rate is a spot price of $2.45 per GPU-hour in April 2026. Dedicated B300 capacity was around $6.80/hr, and premium managed DGX B300 offerings ranged from $12 to $18 per GPU-hour.

Is B300 always more expensive than B200 in the cloud?

Not in every tier. In April 2026, B300 spot was documented at $2.45/hr, which is below the cheapest B200 listing of $2.99/hr in May 2026. The pattern reverses on dedicated and managed tiers, where B300 generally prices higher than equivalent B200 capacity.

What workloads is the DGX B300 designed for?

NVIDIA describes the DGX B300 as the Blackwell Ultra system for AI reasoning – workloads characterized by long inference chains and large context windows where the integrated DGX reference architecture provides the most value.