NVIDIA B300 Blackwell Ultra vs NVIDIA H200 SXM5

Side-by-side comparison of NVIDIA B300 Blackwell Ultra (288 GB VRAM, 9.0 TB/s) and NVIDIA H200 SXM5 (141 GB VRAM, 4.8 TB/s). Compare specs, compute throughput, and workload sizing for LLM inference.

Decision Summary

Spec	NVIDIA B300 Blackwell Ultra	NVIDIA H200 SXM5
VRAM	288GB HBM3e	141GB HBM3e
Memory Bandwidth	9.0 TB/s	4.8 TB/s
FP8 TFLOPS	2,500	1,979
FP16 TFLOPS	1,250	989
Interconnect	NVLink 5.0 (1.8 TB/s)	NVLink 4.0 (900 GB/s)
TDP	1200W	700W
Recommended Quantization	FP4 / FP8 / BF16 — all precisions native, no quality tradeoff	FP8 / FP4 native

Compare for a Workload

Configure a workload to see how each selected GPU performs. Calculations are deterministic estimates based on architectural specifications.

Workload

Context Length

Precision

Batch Size

Configure workload parameters above and click "Calculate VRAM Requirement" to see results.

Cloud Provider Pricing

Current spot and on-demand rates across providers for NVIDIA B300 Blackwell Ultra and NVIDIA H200 SXM5.

Featured GPU Pricing Pages

NVIDIA H100 SXM5

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NVIDIA A100 80GB

Verified spot rates & reserved pricing

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NVIDIA T4

16GB GDDR6 • 0.32 TB/s • PCIe 3.0

	Provider	GPU & VRAM	Interconnect	Spot Price ($/hr)	On-Demand ($/hr)	Monthly ($/720h)	Status	Action
No providers match your filters.

On-demand and monthly figures are the providers' listed rates (monthly = listed rate, else hourly × 720h). Rows without a tracked rate show —. All rates subject to preemption and provider availability.

Data Freshness: Public Cloud APIs & Market Scraping | Refreshed Daily (UTC)|Benchmark Baseline: Ubuntu 24.04, CUDA 12.4, vLLM v0.6.x, PagedAttention v2, FlashAttention-3

Prices verified daily from Spheron, RunPod, Vast.ai, and Lambda Labs APIs.

Microarchitecture & Interconnect

NVIDIA B300 Blackwell Ultra

ArchitectureBlackwell Ultra GB300

Process Node4NP TSMC

FP8 TFLOPS2,500

FP16 TFLOPS1,250

Compute BoundCompute-bound at small batch with FP8/BF16; memory-bound for frontier parameter counts

Recommended Topology8-way NVLink 5.0 Full Mesh, multi-node via NVLink-C2C

Recommended Quantization: FP4 / FP8 / BF16 — all precisions native, no quality tradeoff

NVIDIA H200 SXM5

ArchitectureHopper GH200

Process Node4nm TSMC

FP8 TFLOPS1,979

FP16 TFLOPS989

Compute BoundMemory-bandwidth bound across all batch sizes

Recommended Topology8-way HGX Baseboard with NVLink 4.0 Mesh

Recommended Quantization: FP8 / FP4 native

Related GPU Comparisons

Explore canonical side-by-side comparisons for this hardware tier.

NVIDIA B300 Blackwell Ultra vs NVIDIA H100 SXM5→

288GB HBM3e vs 80GB HBM3

NVIDIA B200 Blackwell vs NVIDIA B300 Blackwell Ultra→

192GB HBM3e vs 288GB HBM3e

NVIDIA H100 SXM5 vs NVIDIA H200 SXM5→

80GB HBM3 vs 141GB HBM3e

NVIDIA B200 Blackwell vs NVIDIA H200 SXM5→

192GB HBM3e vs 141GB HBM3e

Deploy NVIDIA B300 Blackwell Ultra Deploy NVIDIA H200 SXM5

Data Freshness: Verified via Public Cloud APIs & Market Scraping | Refreshed Daily (UTC)|Benchmark Baseline: Ubuntu 24.04, CUDA 12.4, vLLM v0.6.x (PagedAttention v2, FlashAttention-3), BF16/FP8 weights.

Methodology →