Specifications Compared
| Spec | GB300 | H200 |
|---|---|---|
| TDP | 1400W | 700W |
| VRAM | 288 GB | 141 GB |
| Memory Type | HBM3e | HBM3e |
| Architecture | Blackwell Ultra | Hopper |
| Form Factors | SXM | SXM, NVL |
| Interconnect | NVSwitch, NVLink | NVLink, PCIe 5.0, InfiniBand |
| FP8 Performance | 4,500 TFLOPS | 3,958 TFLOPS |
| FP16 Performance | 2,250 TFLOPS | 1,979 TFLOPS |
| FP32 Performance | 90 TFLOPS | 67 TFLOPS |
| FP64 Performance | 45 TFLOPS | 34 TFLOPS |
| INT8 Performance | 4,500 TOPS | 3,958 TOPS |
| Memory Bandwidth | 12,000 GB/s | 4,800 GB/s |
Performance Analysis
The GB300 SXM6 outperforms the H200 NVL in FP16 at 2250 TFLOPS versus 1979 TFLOPS, accelerating large language model training by enabling larger batch sizes and faster iterations on datasets exceeding hundreds of billions of parameters. Its FP32 rate of 90 TFLOPS surpasses the H200 NVL's 67 TFLOPS, benefiting scientific simulations requiring precise single-precision computations. FP8 performance reaches 4500 TFLOPS on the GB300 SXM6 compared to 3958 TFLOPS, optimizing inference for quantized models in production serving. Memory bandwidth of 12000 GB/s on the GB300 SXM6 doubles the H200 NVL's 4800 GB/s, allowing twice the effective batch sizes for memory-bound workloads like transformer training, reducing out-of-memory errors for models over 100 billion parameters. Higher VRAM capacity of 288 GB versus 141 GB supports longer context lengths in inference without model sharding.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H200 NVL
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vultr | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 72 vCPU 480GB RAM 960GB Storage | Atlanta | $1.99/GPU/hr | Available | ||
 Lambda Labs | NVIDIA GH200 Grace Hopper 96GB VRAM | 96GB | 64 vCPU 432GB RAM 4096GB Storage | Virginia | $2.29/GPU/hr | Available | ||
 Nebius | NVIDIA H200 SXM 141GB VRAM | 141GB | 16 vCPU 200GB RAM | 🌍Europe | $2.45/GPU/hr | |||
 CoreWeave | 8×NVIDIA H200 SXM 141GB VRAM | 141GB | 128 vCPU 0GB RAM 61440GB Storage | United States | $2.58/GPU/hr $20.64/hr total (8×) | |||
 Ori | 4×NVIDIA H200 SXM 141GB VRAM | 141GB | 96 vCPU 960GB RAM 12000GB Storage | London | $3.50/GPU/hr $14.00/hr total (4×) | Available |
When to Choose the GB300 SXM6
The GB300 SXM6 suits deployments demanding extreme scale, such as training foundation models beyond 1 trillion parameters, where 288 GB VRAM and 12000 GB/s bandwidth prevent bottlenecks. Its 2250 TFLOPS FP16 performance excels in multi-node clusters via NVSwitch, ideal for research labs prioritizing future-proofing over current availability.
When to Choose the H200 NVL
The H200 NVL fits cost-sensitive production inference with immediate cloud access at $0.50 per hour minimum pricing. Its 700W TDP halves power costs compared to the GB300 SXM6's 1400W, suiting environments with density constraints, while 141 GB VRAM handles most current LLMs effectively.
Use Cases
GB300 SXM6's 288 GB VRAM and 2250 TFLOPS FP16 handle massive datasets and models exceeding H200 NVL limits. Bandwidth of 12000 GB/s supports larger batches for faster convergence.
Higher FP8 at 4500 TFLOPS and 288 GB VRAM enable serving longer contexts without sharding on GB300 SXM6. It outperforms H200 NVL's 3958 TFLOPS for high-throughput quantized inference.
H200 NVL's 141 GB VRAM suffices for models under 70B parameters at lower cost. GB300 SXM6 excels for larger scales with 288 GB capacity.
H200 NVL's 1979 TFLOPS FP16 and availability at $2.24 per hour average meet image generation needs efficiently. GB300 SXM6's power overhead provides minimal gains for this workload.
GB300 SXM6's 90 TFLOPS FP32 surpasses H200 NVL's 67 TFLOPS for simulations. NVSwitch interconnect aids complex multi-GPU physics and climate modeling.
Frequently Asked Questions
What is the VRAM difference between GB300 SXM6 and H200 NVL?▾
The GB300 SXM6 provides 288 GB HBM3e VRAM, more than double the H200 NVL's 141 GB. This enables handling larger models without partitioning. Bandwidth reaches 12000 GB/s on GB300 SXM6 versus 4800 GB/s.
How do FP16 performances compare?▾
GB300 SXM6 delivers 2250 TFLOPS FP16, exceeding H200 NVL's 1979 TFLOPS by 14 percent. This boosts training speed for deep learning workloads. FP8 hits 4500 TFLOPS on GB300 SXM6.
What are the power requirements?▾
GB300 SXM6 has a 1400W TDP, twice the H200 NVL's 700W. Higher power supports greater compute density. Cooling infrastructure must accommodate this for GB300 SXM6.
Is H200 NVL available for rent?▾
H200 NVL offers cloud pricing from $0.50 per hour, averaging $2.24 per hour across three providers. GB300 SXM6 has no live offers currently. This makes H200 NVL immediately deployable.
Which has better interconnects?▾
GB300 SXM6 uses NVSwitch and NVLink for superior multi-GPU bandwidth. H200 NVL supports NVLink, PCIe 5.0, and InfiniBand. NVSwitch enables tighter scaling on GB300 SXM6.
When was each GPU released?▾
H200 NVL stems from Hopper architecture in 2024. GB300 SXM6 uses Blackwell Ultra from 2025. Generational leap provides GB300 SXM6 with advanced efficiency.
Which is cheaper to rent, the GB300 or the H200?▾
Cloud rental prices for both the GB300 and H200 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 GB300 have compared to the H200?▾
The GB300 has 288 GB of HBM3e memory. The H200 has 141 GB of HBM3e memory.
Can I find GB300 and H200 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 GB300 and the H200?▾
The GB300 uses the Blackwell Ultra architecture (2025) while the H200 uses Hopper (2024). The GB300 delivers 1.1x the FP16 throughput and 2.5x the memory bandwidth of the H200.