Specifications Compared
| Spec | B200 | RTX-A2000 |
|---|---|---|
| TDP | 1000W | 70W |
| VRAM | 192 GB | 6-12 GB |
| CUDA Cores | 18,432 | 3,328 |
| Memory Type | HBM3e | GDDR6 |
| Architecture | Blackwell | Ampere |
| Form Factors | SXM, NVL | PCIe |
| Interconnect | NVLink, PCIe 6.0, InfiniBand | |
| Tensor Cores | 576 | 104 |
| FP8 Performance | 9,000 TFLOPS | |
| FP16 Performance | 4,500 TFLOPS | 8 TFLOPS |
| FP32 Performance | 90 TFLOPS | 8 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 9,000 TOPS | |
| Memory Bandwidth | 8,000 GB/s | 288 GB/s |
Performance Analysis
The B200's FP16 performance reaches 4500 TFLOPS compared to the A2000's 8 TFLOPS, accelerating deep learning training where half-precision arithmetic prevails and enabling models with billions of parameters. Its FP32 throughput of 90 TFLOPS exceeds the A2000's 8 TFLOPS, aiding precision-sensitive tasks like scientific simulations. The FP16 to FP32 ratio on B200 favors mixed-precision workflows, reducing training times dramatically.
Memory bandwidth defines scalability: B200's 8000 GB/s supports enormous batch sizes in inference and training, preventing bottlenecks for large models fitting its 192 GB VRAM. The A2000's 288 GB/s constrains it to smaller batches and models under 12 GB, limiting throughput in data-heavy scenarios. For inference, B200's 9000 TFLOPS FP8 crushes the A2000, enabling high-volume serving.
Power draw amplifies differences: B200's 1000W TDP powers peak performance in clusters via NVLink, while A2000's 70W fits efficient, low-cost deployments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
B200 SXM
| 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 |
RTX A2000
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
RunPod | NVIDIA RTX A2000 12GB VRAM | 12GB | 6 vCPU 20GB RAM | 🌍global | $0.50/GPU/hr |
When to Choose the B200 SXM
Choose the NVIDIA B200 for large-scale AI training and inference where 192 GB HBM3e VRAM loads models exceeding 100 billion parameters. Its 4500 TFLOPS FP16 and 8000 GB/s bandwidth excel in distributed setups with NVLink and PCIe 6.0, ideal for research labs or enterprises handling massive datasets.
When to Choose the RTX A2000
The NVIDIA RTX A2000 suits prototyping, small-scale inference, and visualization tasks fitting within 12 GB GDDR6 VRAM. Its low 70W TDP and $0.06 per hour starting price make it perfect for individual developers or edge computing where cost and power efficiency matter over raw speed.
Use Cases
B200's 192 GB VRAM and 4500 TFLOPS FP16 support training models with hundreds of billions of parameters at scale. RTX A2000 lacks capacity for such workloads.
B200's 9000 TFLOPS FP8 and 8000 GB/s bandwidth enable high-throughput serving of large models with big batches. A2000 suits only tiny models.
B200's 90 TFLOPS FP32 and vast VRAM accelerate fine-tuning on large datasets. A2000 works for small models but slows significantly.
RTX A2000 handles standard image generation in 6-12 GB VRAM at low cost. B200 overpowers for batch or high-res generation.
B200's 90 TFLOPS FP32 and InfiniBand interconnect optimize simulations across clusters. A2000 limits to modest computations.
Frequently Asked Questions
How much more VRAM does the B200 have than the RTX A2000?▾
The B200 provides 192 GB HBM3e VRAM, while the RTX A2000 offers 6 to 12 GB GDDR6. This 16 to 32 times difference allows B200 to manage far larger AI models without swapping.
What is the performance gap in FP16 between B200 and RTX A2000?▾
B200 achieves 4500 TFLOPS FP16 versus RTX A2000's 8 TFLOPS, a 562.5 times advantage. This translates to drastically faster training for deep learning tasks.
How do prices compare for these GPUs in the cloud?▾
B200 SXM starts at $1.71 per hour averaging $4.60 across 13 offers. RTX A2000 starts at $0.06 per hour averaging $0.23 across 3 offers, making it far cheaper for light use.
Which GPU has higher memory bandwidth?▾
B200 delivers 8000 GB/s, over 27 times the RTX A2000's 288 GB/s. Higher bandwidth on B200 supports larger batch sizes in training and inference.
What are the TDP differences?▾
B200 requires 1000W TDP for peak performance in datacenters. RTX A2000 uses 70W, ideal for low-power workstations or edge devices.
Can RTX A2000 handle large LLMs?▾
RTX A2000's 12 GB max VRAM limits it to small LLMs under 7 billion parameters. B200's 192 GB accommodates models over 100 billion parameters easily.
Which is cheaper to rent, the B200 or the RTX A2000?▾
Cloud rental prices for both the B200 and RTX A2000 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 RTX A2000?▾
The B200 has 192 GB of HBM3e memory. The RTX A2000 has 6 to 12 GB of GDDR6 memory.
Can I find B200 and RTX A2000 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 RTX A2000?▾
The B200 uses the Blackwell architecture (2024) while the RTX A2000 uses Ampere (2021). The B200 delivers 562.5x the FP16 throughput and 27.8x the memory bandwidth of the RTX A2000.