Specifications Compared
| Spec | B200 | RTX-5080 |
|---|---|---|
| TDP | 1000W | 360W |
| VRAM | 192 GB | 16 GB |
| CUDA Cores | 18,432 | 10,752 |
| Memory Type | HBM3e | GDDR7 |
| Architecture | Blackwell | Blackwell |
| Form Factors | SXM, NVL | PCIe |
| Interconnect | NVLink, PCIe 6.0, InfiniBand | |
| Tensor Cores | 576 | 336 |
| FP8 Performance | 9,000 TFLOPS | |
| FP16 Performance | 4,500 TFLOPS | 56.3 TFLOPS |
| FP32 Performance | 90 TFLOPS | 56.3 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 9,000 TOPS | 900 TOPS |
| Memory Bandwidth | 8,000 GB/s | 960 GB/s |
Performance Analysis
The B200 NVL dominates compute with 4500 TFLOPS FP16 and 9000 TFLOPS FP8, enabling rapid large-scale model training where the RTX 5080's 56.3 TFLOPS FP16 limits it to smaller batches. This FP16 to FP32 parity on the RTX 5080 at 56.3 TFLOPS each suits gaming but hampers training efficiency compared to the B200's 90 TFLOPS FP32, which accelerates mixed-precision workflows in datacenters.
Memory differences reshape real-world use: the B200's 192 GB HBM3e supports batch sizes for billion-parameter LLMs, while the RTX 5080's 16 GB GDDR7 restricts it to sub-10B models or heavy quantization. Bandwidth at 8000 GB/s on the B200 minimizes data bottlenecks in inference pipelines, versus 960 GB/s on the RTX 5080, which suffices for edge deployment but stalls at high throughput.
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 |
RTX 5080
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
RunPod | NVIDIA GeForce RTX 5080 16GB VRAM | 16GB | 0 vCPU 0GB RAM | 🌍global | $0.59/GPU/hr |
When to Choose the B200 NVL
Opt for the NVIDIA B200 NVL in large-scale AI training or inference requiring over 100 GB VRAM, such as full fine-tuning of 70B LLMs, where its 192 GB HBM3e and 4500 TFLOPS FP16 enable efficient multi-GPU scaling via NVLink. Datacenter environments with InfiniBand clusters favor its 1000W TDP for sustained 90 TFLOPS FP32 compute in scientific simulations.
When to Choose the RTX 5080
Select the NVIDIA GeForce RTX 5080 for cost-sensitive tasks like Stable Diffusion generation or small-model inference, leveraging its 16 GB GDDR7 at $0.25 per hour starting price across four providers. Gaming-integrated AI prototyping or fine-tuning under 7B parameters benefits from its 360W efficiency and 56.3 TFLOPS FP16 in PCIe desktops.
Use Cases
The B200 NVL's 192 GB HBM3e VRAM and 4500 TFLOPS FP16 support large batch sizes for training models over 70B parameters. The RTX 5080's 16 GB limits it to tiny models.
B200 NVL handles high-throughput inference with 9000 TFLOPS FP8 and 8000 GB/s bandwidth for unquantized large LLMs. RTX 5080 suits only quantized small models.
RTX 5080 works for models under 13B with 56.3 TFLOPS FP16 at low cost, while B200 NVL excels for larger ones via 192 GB VRAM.
RTX 5080's 16 GB GDDR7 and 960 GB/s bandwidth generate images efficiently at $0.38 average hourly rate. B200 NVL overkill for consumer diffusion tasks.
B200 NVL's 90 TFLOPS FP32 and NVLink scaling accelerate simulations needing high precision and memory. RTX 5080 adequate only for modest datasets.
Frequently Asked Questions
Which GPU has more VRAM: B200 NVL or RTX 5080?▾
The B200 NVL provides 192 GB HBM3e VRAM, far exceeding the RTX 5080's 16 GB GDDR7. This enables the B200 for massive AI models, while RTX 5080 fits smaller workloads.
How do their FP16 performances compare?▾
B200 NVL achieves 4500 TFLOPS FP16, over 80 times the RTX 5080's 56.3 TFLOPS. This gap favors B200 for accelerated training and inference.
What are the cloud pricing differences?▾
B200 NVL starts at $10.50 per hour from one provider. RTX 5080 offers from $0.25 per hour, averaging $0.38 across four providers.
Which has higher memory bandwidth?▾
B200 NVL delivers 8000 GB/s, compared to RTX 5080's 960 GB/s. Higher bandwidth on B200 reduces bottlenecks in data-heavy tasks.
Is the RTX 5080 suitable for LLM training?▾
RTX 5080's 16 GB VRAM and 56.3 TFLOPS FP16 limit it to small LLMs under 7B parameters. B200 NVL is required for larger scale.
What are their TDPs?▾
B200 NVL has a 1000W TDP for datacenter use. RTX 5080 uses 360W, ideal for consumer PCIe systems.
Which is cheaper to rent, the B200 or the RTX 5080?▾
Cloud rental prices for both the B200 and RTX 5080 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 5080?▾
The B200 has 192 GB of HBM3e memory. The RTX 5080 has 16 GB of GDDR7 memory.
Can I find B200 and RTX 5080 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 5080?▾
The B200 uses the Blackwell architecture (2024) while the RTX 5080 uses Blackwell (2025). The B200 delivers 79.9x the FP16 throughput and 8.3x the memory bandwidth of the RTX 5080.