Specifications Compared
| Spec | GB300 | H100 |
|---|---|---|
| TDP | 1400W | 700W |
| VRAM | 288 GB | 80-94 GB |
| Memory Type | HBM3e | HBM3 |
| Architecture | Blackwell Ultra | Hopper |
| Form Factors | SXM | SXM5, PCIe, 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 | 3,350 GB/s |
Performance Analysis
Superior compute defines GB300 SXM6's edge: its 2250 TFLOPS FP16 exceeds H100 PCIe by 14 percent, shortening training times for deep learning models that rely on half-precision arithmetic. FP32 at 90 TFLOPS, up 34 percent from 67 TFLOPS, benefits simulation tasks needing full precision. For inference, GB300's 4500 TFLOPS FP8 handles quantized models with higher throughput than H100's 3958 TFLOPS, supporting real-time applications at scale. Vast 288 GB VRAM on GB300 accommodates models three and a half times larger than H100's 80 GB capacity, slashing the need for model parallelism. The 12000 GB/s bandwidth, 3.6 times H100's 3350 GB/s, sustains large batch sizes in training without memory stalls, boosting utilization in LLM workflows.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
H100 PCIe
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Hyperstack | 4×NVIDIA H100 PCIe 80GB VRAM | 80GB | 124 vCPU 720GB RAM 3300GB Storage | Canada | $1.90/GPU/hr $7.60/hr total (4×) | Available | ||
Hyperstack | 2×NVIDIA H100 PCIe 80GB VRAM | 80GB | 60 vCPU 360GB RAM 1600GB Storage | Canada | $1.90/GPU/hr $3.80/hr total (2×) | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.90/GPU/hr $15.20/hr total (8×) | Available | ||
Hyperstack | NVIDIA H100 PCIe 80GB VRAM | 80GB | 28 vCPU 180GB RAM 850GB Storage | Canada | $1.90/GPU/hr | Available | ||
Hyperstack | 8×NVIDIA H100 PCIe 80GB VRAM | 80GB | 252 vCPU 1440GB RAM 6600GB Storage | Canada | $1.95/GPU/hr $15.60/hr total (8×) | Available |
When to Choose the GB300 SXM6
Enterprises targeting frontier AI models opt for GB300 SXM6, where 288 GB VRAM and NVSwitch interconnect enable single-GPU handling of trillion-parameter LLMs. High-bandwidth 12000 GB/s memory excels in cluster-scale training, reducing latency over H100 PCIe setups. Power-tolerant data centers leverage its 1400W TDP for peak 2250 TFLOPS FP16 performance in 2025 deployments.
When to Choose the H100 PCIe
Organizations requiring instant availability select H100 PCIe, priced from $1.25 per hour with an average of $2.69 per hour across 19 providers. Its 700W TDP fits constrained power budgets, and PCIe form factor eases integration into existing servers. For mid-scale inference, 3958 TFLOPS FP8 suffices without GB300's wait for availability.
Use Cases
GB300 SXM6's 288 GB VRAM and 2250 TFLOPS FP16 manage trillion-parameter models and large batches infeasible on H100 PCIe 80 GB capacity. Its 12000 GB/s bandwidth prevents bottlenecks in data-intensive sessions.
4500 TFLOPS FP8 on GB300 SXM6 outperforms H100 PCIe 3958 TFLOPS for high-throughput serving of quantized models. Massive VRAM enables larger context windows without sharding.
H100 PCIe handles medium models effectively at 1979 TFLOPS FP16 with immediate $1.25/hr availability. GB300 SXM6 shines for parameter-heavy fine-tuning via 288 GB VRAM.
H100 PCIe 80 GB VRAM and 3350 GB/s bandwidth suffice for image generation pipelines at lower 700W TDP. GB300 SXM6 overkill for typical diffusion model scales.
H100 PCIe 67 TFLOPS FP32 meets simulation needs with PCIe compatibility and cloud access from $1.25/hr. GB300's 90 TFLOPS FP32 excess for most non-AI science tasks.
Frequently Asked Questions
What is the VRAM capacity of GB300 SXM6 versus H100 PCIe?▾
GB300 SXM6 provides 288 GB HBM3e VRAM, enabling larger models than H100 PCIe 80 GB HBM3. This 3.6-fold increase reduces multi-GPU complexity in training.
How do FP16 performance figures compare?▾
GB300 SXM6 achieves 2250 TFLOPS FP16, 14 percent above H100 PCIe 1979 TFLOPS. Faster half-precision compute accelerates deep learning training cycles.
What are the memory bandwidth differences?▾
GB300 SXM6 offers 12000 GB/s, 3.6 times H100 PCIe 3350 GB/s. Higher bandwidth supports bigger batches without throughput loss.
Is GB300 SXM6 available for cloud rental now?▾
No live offers exist for GB300 SXM6 currently. H100 PCIe starts at $1.25 per hour, averaging $2.69 per hour over 19 providers.
How do power requirements differ?▾
GB300 SXM6 demands 1400W TDP, double H100 PCIe 700W. Lower power suits H100 for efficiency-focused setups.
Which has better FP8 for inference?▾
GB300 SXM6 leads with 4500 TFLOPS FP8 over H100 PCIe 3958 TFLOPS. This edge boosts quantized model serving speeds.
Which is cheaper to rent, the GB300 or the H100?▾
Cloud rental prices for both the GB300 and H100 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 H100?▾
The GB300 has 288 GB of HBM3e memory. The H100 has 80 to 94 GB of HBM3 memory.
Can I find GB300 and H100 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 H100?▾
The GB300 uses the Blackwell Ultra architecture (2025) while the H100 uses Hopper (2022). The GB300 delivers 1.1x the FP16 throughput and 3.6x the memory bandwidth of the H100.