Specifications Compared
| Spec | B200 | H100 |
|---|---|---|
| TDP | 1000W | 700W |
| VRAM | 192 GB | 80-94 GB |
| CUDA Cores | 18,432 | 16,896 |
| Memory Type | HBM3e | HBM3 |
| Architecture | Blackwell | Hopper |
| Form Factors | SXM, NVL | SXM5, PCIe, NVL |
| Interconnect | NVLink, PCIe 6.0, InfiniBand | NVLink, PCIe 5.0, InfiniBand |
| Tensor Cores | 576 | 528 |
| FP8 Performance | 9,000 TFLOPS | 3,958 TFLOPS |
| FP16 Performance | 4,500 TFLOPS | 1,979 TFLOPS |
| FP32 Performance | 90 TFLOPS | 67 TFLOPS |
| FP64 Performance | 45 TFLOPS | 34 TFLOPS |
| INT8 Performance | 9,000 TOPS | 3,958 TOPS |
| Memory Bandwidth | 8,000 GB/s | 3,350 GB/s |
Performance Analysis
Compute differences translate directly to workload efficiency: B200 NVL's 4500 TFLOPS FP16 rate accelerates AI training by over 2x compared to H100 SXM5's 1979 TFLOPS, enabling shorter epochs on massive datasets. FP32 performance edges to 90 TFLOPS on B200 NVL from 67 TFLOPS on H100 SXM5, benefiting simulations requiring precision. FP8 inference surges to 9000 TFLOPS on B200 NVL against 3958 TFLOPS on H100 SXM5, ideal for high-volume serving.
Memory specs reshape practical limits. The 192 GB HBM3e VRAM on B200 NVL supports batch sizes 2-2.4x larger than H100 SXM5's 80-94 GB HBM3, minimizing out-of-memory errors in fine-tuning or inference. Bandwidth of 8000 GB/s on B200 NVL halves latency for memory-bound operations versus 3350 GB/s on H100 SXM5, boosting effective throughput in transformer models.
Power draw reflects scaling: B200 NVL's 1000W TDP demands robust cooling versus H100 SXM5's 700W, but yields superior flops per watt in FP16 at approximately 4.5 TFLOPS/W compared to 2.8 TFLOPS/W.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
B200 NVL
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Nebius | NVIDIA B200 SXM 192GB VRAM | 192GB | 20 vCPU 224GB RAM | 🌍Europe | $3.95/GPU/hr | |||
 Cirrascale | 8×NVIDIA B200 SXM 192GB VRAM | 192GB | 192 vCPU 2048GB RAM 43923GB Storage | United States | $4.79/GPU/hr $38.32/hr total (8×) | |||
Cirrascale | 8×NVIDIA B200 SXM 192GB VRAM | 192GB | 192 vCPU 2048GB RAM 43923GB Storage | United States | $5.39/GPU/hr $43.12/hr total (8×) | |||
Cirrascale | 8×NVIDIA B200 SXM 192GB VRAM | 192GB | 192 vCPU 2048GB RAM 43923GB Storage | United States | $5.69/GPU/hr $45.52/hr total (8×) | |||
 RunPod | NVIDIA B200 SXM 192GB VRAM | 192GB | 28 vCPU 283GB RAM | California | $5.89/GPU/hr |
H100 SXM5
| 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 B200 NVL
The B200 NVL excels in frontier AI research requiring extreme scale. Its 192 GB VRAM and 8000 GB/s bandwidth handle trillion-parameter LLMs without multi-node sharding, while 4500 TFLOPS FP16 cuts training time by factors of 2-3x over H100 SXM5. Deploy for production inference at $10.50 per hour when latency under 100ms per query justifies premium.
When to Choose the H100 SXM5
Opt for H100 SXM5 in cost-constrained environments with proven stability. At $1.47 per hour starting price and 34 cloud offers, it delivers 1979 TFLOPS FP16 for mid-scale training, sufficient for models under 100B parameters. Mature software stacks ensure seamless integration where 80-94 GB VRAM meets batch needs without overprovisioning.
Use Cases
B200 NVL's 4500 TFLOPS FP16 and 192 GB VRAM enable 2x faster training of models over 500B parameters than H100 SXM5's 1979 TFLOPS and 80-94 GB.
9000 TFLOPS FP8 and 8000 GB/s bandwidth on B200 NVL support higher throughput for serving large models, outperforming H100 SXM5's 3958 TFLOPS FP8.
192 GB VRAM accommodates full model fine-tuning without gradient checkpointing, unlike H100 SXM5's 80-94 GB limits.
H100 SXM5's 1979 TFLOPS FP16 suffices for image generation at lower cost of $3.62 per hour average, as tasks rarely exceed 94 GB VRAM.
H100 SXM5's 67 TFLOPS FP32 handles most simulations cost-effectively, but B200 NVL's 90 TFLOPS FP32 accelerates HPC at scale.
Frequently Asked Questions
Which GPU has more VRAM?▾
B200 NVL offers 192 GB HBM3e, exceeding H100 SXM5's 80-94 GB HBM3 by 2-2.4x. This supports larger models without distributed setups.
How do prices compare?▾
B200 NVL averages $10.50 per hour from one offer, while H100 SXM5 starts at $1.47 per hour averaging $3.62 across 34 offers. H100 provides better value for moderate workloads.
What is the FP16 performance difference?▾
B200 NVL achieves 4500 TFLOPS FP16, more than double H100 SXM5's 1979 TFLOPS. Training times reduce proportionally for deep learning.
Which has higher memory bandwidth?▾
B200 NVL delivers 8000 GB/s, 2.4x H100 SXM5's 3350 GB/s. This minimizes stalls in bandwidth-limited inference.
What are the TDP ratings?▾
B200 NVL consumes 1000W TDP versus H100 SXM5's 700W. B200 yields higher performance per watt in FP16 at 4.5 TFLOPS/W.
Best for large model training?▾
B200 NVL dominates with 192 GB VRAM and 4500 TFLOPS FP16, enabling single-GPU handling of models H100 SXM5 requires multi-GPU for.
Which is cheaper to rent, the B200 or the H100?▾
Cloud rental prices for both the B200 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 B200 have compared to the H100?▾
The B200 has 192 GB of HBM3e memory. The H100 has 80 to 94 GB of HBM3 memory.
Can I find B200 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 B200 and the H100?▾
The B200 uses the Blackwell architecture (2024) while the H100 uses Hopper (2022). The B200 delivers 2.3x the FP16 throughput and 2.4x the memory bandwidth of the H100.