GPU comparison

B300 vs GH200

Specifications and current cloud pricing, side by side.

Blackwell UltravsHopperUpdated 33 days ago

The B300 wins for the most common use case of LLM training. Its 2250 TFLOPS FP16 dense rating combined with 8000 GB/s bandwidth and 262 to 288 GB memory exceeds the corresponding 989 TFLOPS, 4000 GB/s, and 96 GB specifications of the GH200.

B300 listed from $0.50/GPU/hrGH200 listed from $1.99/GPU/hr

Right now, from live stock

Specifications Compared

SpecB300GH200
TDP1400W900W
VRAM262-288 GB96 GB
CUDA CoresNot published16,896
FP4 (dense)13,500 TFLOPSNot published
FP8 (dense)4,500 TFLOPS1,979 TFLOPS
Memory TypeHBM3eHBM3
ArchitectureBlackwell UltraHopper
FP16 (dense)2,250 TFLOPS989 TFLOPS
Form FactorsSXM6SXM
INT8 (dense)187.5 TOPS1,979 TOPS
InterconnectNVLink, PCIe 6.0, InfiniBandNVLink-C2C, PCIe 5.0
Tensor CoresNot published528
FP32 Performance75 TFLOPS67 TFLOPS
FP64 Performance1.25 TFLOPS34 TFLOPS
Memory Bandwidth8,000 GB/s4,000 GB/s
FP4 (with sparsity)18,000 TFLOPSNot published
FP8 (with sparsity)9,000 TFLOPS3,958 TFLOPS
FP16 (with sparsity)4,500 TFLOPS1,979 TFLOPS
INT8 (with sparsity)375 TOPS3,958 TOPS

Performance Analysis

The FP16 dense rating of 2250 TFLOPS on the B300 exceeds the 989 TFLOPS dense figure on the GH200 by more than double. This gap supports larger batch sizes during training because the B300 also provides 8000 GB/s bandwidth against 4000 GB/s on the GH200. FP32 performance measures 75 TFLOPS on the B300 and 67 TFLOPS on the GH200. FP16 with sparsity reaches 4500 TFLOPS on the B300 versus 1979 TFLOPS with sparsity on the GH200.

Current On-Demand Offers

Cheapest secure on-demand offer per provider that is reported in stock right now, per GPU per hour; multi-GPU instances show the whole-instance price alongside. Deploy opens the DeployGPU console for providers on the platform, otherwise the provider's own site. Stock is rechecked every minute.

B300

ProviderRegionGPUsPer GPU / hrInstance / hrDeploy
RunPodglobal1$0.50—Deploy

1 provider in stock, 2 offers (cheapest per provider shown). All B300 offers, price history and alerts

GH200

GH200 is not offered on-demand by any provider we track right now. See the GH200 rental page for last-seen listed prices and a price alert.

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Notify me when B300 drops below a price

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QuantaCloud

Comparing H-series providers? We broker across all of them.

Hopper stock changes by the hour and prices differ by provider. If you need 16+ GPUs reserved or a cluster in the next 90 days, we quote H-series or B300 inventory at partner rates: one quote, 24h turnaround.

No waitlist24hr quote turnaroundInfiniBand fabric

Compare real-time pricing across 25+ providers

When to Choose the B300

The B300 suits workloads that require the 262 to 288 GB HBM3e capacity and 8000 GB/s bandwidth. Its 2250 TFLOPS FP16 dense rating and 4500 TFLOPS FP16 with sparsity rating enable handling of larger models than the GH200 allows.

When to Choose the GH200

The GH200 fits deployments where the 900W TDP and 96 GB HBM3 configuration align with power or form factor limits. Its 1979 TFLOPS FP16 dense rating remains sufficient for moderate scale inference tasks.

Use Cases

LLM Training
B300

The B300 supplies 2250 TFLOPS FP16 dense and 8000 GB/s bandwidth to support larger batches than the GH200 989 TFLOPS dense and 4000 GB/s.

LLM Inference
B300

The B300 provides 4500 TFLOPS FP8 dense and 262 to 288 GB memory for higher throughput than the GH200 1979 TFLOPS FP8 dense and 96 GB memory.

Fine-tuning
B300

The B300 offers 2250 TFLOPS FP16 dense along with 8000 GB/s bandwidth to accommodate larger fine-tuning batches than the GH200.

Stable Diffusion
GH200

The GH200 900W TDP and 96 GB HBM3 fit power constrained image generation workloads adequately.

Scientific Computing
Either

Both GPUs deliver FP32 performance near 75 TFLOPS on the B300 and 67 TFLOPS on the GH200 for simulation tasks.

Frequently Asked Questions

How does FP16 dense performance compare between the two?▾

The B300 reaches 2250 TFLOPS FP16 dense while the GH200 reaches 989 TFLOPS FP16 dense. The B300 figure is more than double the GH200 figure.

Which GPU has the higher TDP rating?▾

The B300 carries a 1400W TDP rating. The GH200 carries a 900W TDP rating.

What FP8 dense performance does each GPU list?▾

The B300 lists 4500 TFLOPS FP8 dense. The GH200 lists 1979 TFLOPS FP8 dense.

Which is cheaper to rent, the B300 or the GH200?▾

Cloud rental prices for both the B300 and GH200 vary by provider, configuration, and availability. This page shows live pricing from 25+ providers updated every 60 seconds. Scroll to the Live Cloud Pricing section to compare current rates.

How much VRAM does the B300 have compared to the GH200?▾

The B300 has 262 to 288 GB of HBM3e memory. The GH200 has 96 GB of HBM3 memory.

Can I find B300 and GH200 GPUs available to rent right now?▾

Yes. This page shows real-time availability across 25+ cloud GPU providers. The Live Cloud Pricing section displays only in-stock offers with current pricing.

What is the main difference between the B300 and the GH200?▾

The B300 uses the Blackwell Ultra architecture (2025) while the GH200 uses Hopper (2023). The B300 delivers 2.3x the dense FP16 throughput (2,250 vs 989 TFLOPS, both without sparsity) and 2.0x the memory bandwidth of the GH200.

Rent these GPUs

Each GPU page lists every current on-demand offer by provider, per GPU-hour, updated every minute.

Related comparisons

How this page is made

  • Specifications come from the NVIDIA, AMD and Intel datasheets for the B300 and the GH200. Dense and sparse throughput are listed separately.
  • Prices and availability are live: every offer shown is an in-stock, on-demand listing from a provider we track, rechecked every minute.
  • The written comparison (overview, performance notes, when to choose each card, verdict, use cases and FAQ) was drafted with an AI model from the specification table above and passed an automated check that rejects any figure not in that table. It was last generated on . It contains no prices; those are always read live.
  • Read how we collect the data, or report an error on this page.

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