Specifications Compared
| Spec | A100 | B200 |
|---|---|---|
| TDP | 400W | 1000W |
| VRAM | 40-80 GB | 192 GB |
| CUDA Cores | 6,912 | 18,432 |
| Memory Type | HBM2e | HBM3e |
| Architecture | Ampere | Blackwell |
| Form Factors | SXM4, PCIe | SXM, NVL |
| Interconnect | NVLink, PCIe 4.0, InfiniBand | NVLink, PCIe 6.0, InfiniBand |
| Tensor Cores | 432 | 576 |
| FP16 Performance | 312 TFLOPS | 4,500 TFLOPS |
| FP32 Performance | 19.5 TFLOPS | 90 TFLOPS |
| FP64 Performance | 9.7 TFLOPS | 45 TFLOPS |
| INT8 Performance | 624 TOPS | 9,000 TOPS |
| Memory Bandwidth | 2,039 GB/s | 8,000 GB/s |
Performance Analysis
The B200 vastly outpaces the A100 in floating-point performance: its 4500 TFLOPS FP16 rating exceeds the A100's 312 TFLOPS by a factor of 14.4, accelerating neural network training where half-precision computations dominate. FP32 performance reaches 90 TFLOPS on the B200 versus 19.5 TFLOPS on the A100, benefiting general-purpose simulations and precision-sensitive workloads. The B200's FP8 capability at 9000 TFLOPS further optimizes inference for quantized large language models.
Memory specifications profoundly impact real-world usage: the B200's 192 GB HBM3e and 8000 GB/s bandwidth support batch sizes up to four times larger than the A100's 40 GB HBM2e and 2039 GB/s, reducing out-of-memory errors in training massive models. Higher bandwidth minimizes data transfer bottlenecks during inference, enabling throughput increases for vision transformers or diffusion models. Power draw rises to 1000W on the B200 from 400W on the A100, demanding advanced cooling in clusters.
Interconnect advancements aid scalability: B200 supports PCIe 6.0 alongside NVLink and InfiniBand, doubling PCIe 4.0 bandwidth on the A100 for multi-GPU setups.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
A100 SXM4 40GB
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 256 vCPU 63GB RAM 397GB Storage | Slovenia | $0.73/GPU/hr | Available | ||
 LeaderGPU | 8×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 384GB RAM 2000GB Storage | Netherlands | $0.90/GPU/hr $7.20/hr total (8×) | Available | ||
Vast.ai | 2×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 64 vCPU 126GB RAM 1114GB Storage | Czechia | $1.00/GPU/hr $2.00/hr total (2×) | Available | ||
 Denvr | 4×NVIDIA A100 PCIe 80GB 80GB VRAM | 80GB | 64 vCPU 512GB RAM 7600GB Storage | Virginia | $1.15/GPU/hr $4.60/hr total (4×) | |||
Denvr | 8×NVIDIA A100 SXM4 80GB 80GB VRAM | 80GB | 128 vCPU 1024GB RAM 15200GB Storage | Virginia | $1.15/GPU/hr $9.20/hr total (8×) |
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 |
When to Choose the A100 SXM4 40GB
The A100 SXM4 40GB suits cost-sensitive deployments: its pricing from $1.00 per hour averages $2.53 per hour across six providers, far below the B200's $10.50 per hour. Lower 400W TDP fits power-constrained environments or legacy clusters optimized for Ampere architecture.
Smaller-scale fine-tuning or inference on models under 40 GB VRAM favors the A100: 312 TFLOPS FP16 handles Stable Diffusion or mid-sized LLMs efficiently without overprovisioning.
When to Choose the B200 NVL
The B200 NVL excels in frontier AI research: 192 GB HBM3e VRAM accommodates models exceeding 100 billion parameters, impossible on the A100's 40 GB. FP16 at 4500 TFLOPS and FP8 at 9000 TFLOPS slash training and inference times dramatically.
High-throughput production inference benefits from 8000 GB/s bandwidth: it sustains large batch sizes in enterprise LLM serving, justifying the $10.50 per hour cost for revenue-generating workloads.
Use Cases
B200's 4500 TFLOPS FP16 outperforms A100's 312 TFLOPS by 14 times, speeding up training of large models. Its 192 GB VRAM handles massive datasets without splitting.
FP8 performance of 9000 TFLOPS on B200 optimizes quantized inference, absent on A100. 8000 GB/s bandwidth supports high-throughput serving.
A100's 40 GB VRAM and $1.00 per hour pricing suffice for models under 30 GB. B200 accelerates larger fine-tunes with 192 GB VRAM.
A100's 312 TFLOPS FP16 and 2039 GB/s bandwidth generate images efficiently at lower $2.53 per hour average cost. B200 overkill for typical diffusion tasks.
B200's 90 TFLOPS FP32 doubles A100's 19.5 TFLOPS for simulations. 8000 GB/s bandwidth accelerates data-intensive HPC workloads.
Frequently Asked Questions
What is the VRAM capacity of each GPU?▾
The A100 SXM4 40GB has 40 GB HBM2e VRAM. The B200 NVL offers 192 GB HBM3e VRAM, enabling larger models. This quadruples effective capacity for AI training.
How do their prices compare in the cloud?▾
A100 SXM4 40GB starts at $1.00 per hour with an average of $2.53 per hour across six offers. B200 NVL is priced from $10.50 per hour across one offer. A100 provides better value for budget workloads.
Which has higher FP16 performance?▾
B200 achieves 4500 TFLOPS FP16, compared to A100's 312 TFLOPS. This represents a 14-fold increase for training tasks. Inference also benefits from B200's FP8 at 9000 TFLOPS.
What are the memory bandwidth differences?▾
A100 delivers 2039 GB/s bandwidth with HBM2e. B200 reaches 8000 GB/s with HBM3e, nearly quadrupling data throughput. Larger batches become feasible on B200.
How do TDPs compare?▾
A100 SXM4 40GB consumes 400W TDP. B200 NVL requires 1000W TDP for its enhanced capabilities. Deployments must account for cooling and power infrastructure.
Which is better for LLM training?▾
B200 NVL is superior with 4500 TFLOPS FP16 and 192 GB VRAM. A100's 312 TFLOPS and 40 GB limit scale for large LLMs. Performance justifies B200's higher cost.
Which is cheaper to rent, the A100 or the B200?▾
Cloud rental prices for both the A100 and B200 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 A100 have compared to the B200?▾
The A100 has 40 to 80 GB of HBM2e memory. The B200 has 192 GB of HBM3e memory.
Can I find A100 and B200 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 A100 and the B200?▾
The A100 uses the Ampere architecture (2020) while the B200 uses Blackwell (2024). The B200 delivers 14.4x the FP16 throughput and 3.9x the memory bandwidth of the A100.