Specifications Compared
| Spec | B300 | RTX-PRO-6000-BLACKWELL |
|---|---|---|
| TDP | 1200W | 400W |
| VRAM | 288 GB | 96 GB |
| Memory Type | HBM3e | GDDR7 |
| Architecture | Blackwell Ultra | Blackwell |
| Form Factors | SXM | PCIe |
| Interconnect | NVSwitch, NVLink | NVLink |
| FP8 Performance | 4,500 TFLOPS | 2,000 TFLOPS |
| FP16 Performance | 2,250 TFLOPS | 125 TFLOPS |
| FP32 Performance | 90 TFLOPS | 125 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 4,500 TOPS | 2,000 TOPS |
| Memory Bandwidth | 12,000 GB/s | 1,792 GB/s |
Performance Analysis
The B300's FP16 performance reaches 2250 TFLOPS, compared to the RTX PRO 6000's 125 TFLOPS, enabling dramatically faster AI model training and inference on large datasets. This FP16 advantage suits deep learning where half-precision computations dominate, while the RTX PRO 6000's equal 125 TFLOPS FP16 and FP32 supports graphics and simulation tasks requiring full precision. The B300's 4500 TFLOPS FP8 further accelerates quantized inference, outpacing the RTX PRO 6000's 2000 TFLOPS. Memory specs define real-world limits: the B300's 288 GB HBM3e and 12000 GB/s bandwidth handle enormous batch sizes for training billion-parameter models without swapping, whereas the RTX PRO 6000's 96 GB GDDR7 and 1792 GB/s restrict it to smaller batches or models. Power draw underscores this: the B300's 1200W TDP demands robust cooling in SXM form factors, contrasting the RTX PRO 6000's efficient 400W PCIe design for edge deployments.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
B300
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 RunPod | NVIDIA B300 SXM6 262GB VRAM | 262GB | 0 vCPU 0GB RAM | 🌍global | $7.39/GPU/hr | |||
 VERDA | NVIDIA B300 SXM6 262GB VRAM | 262GB | 30 vCPU 255GB RAM | Helsinki | $7.50/GPU/hr | Available | ||
VERDA | 2×NVIDIA B300 SXM6 262GB VRAM | 262GB | 60 vCPU 510GB RAM | Helsinki | $7.50/GPU/hr $15.00/hr total (2×) | Available | ||
VERDA | 8×NVIDIA B300 SXM6 262GB VRAM | 262GB | 240 vCPU 2040GB RAM | Helsinki | $7.50/GPU/hr $60.00/hr total (8×) | Available | ||
 Scaleway | 8×NVIDIA B300 SXM6 262GB VRAM | 262GB | 224 vCPU 3840GB RAM 22352GB Storage | Paris | $8.73/GPU/hr $69.84/hr total (8×) | Available |
When to Choose the B300
The B300 excels in large-scale LLM training and inference requiring over 96 GB VRAM. Its 288 GB HBM3e capacity fits massive models like 1T-parameter LLMs, with 12000 GB/s bandwidth supporting batch sizes that saturate 2250 TFLOPS FP16 throughput. Datacenter users prioritizing raw speed over cost select it despite $6.44 per hour average pricing.
When to Choose the RTX PRO 6000
The RTX PRO 6000 suits cost-sensitive inference and fine-tuning on models under 96 GB. At $1.25 per hour average, its 400W TDP enables dense PCIe deployments, and balanced 125 TFLOPS FP16/FP32 handles Stable Diffusion or scientific simulations efficiently. Developers avoid overkill for moderate workloads.
Use Cases
The B300's 288 GB HBM3e VRAM and 2250 TFLOPS FP16 support training massive models with large batch sizes. The RTX PRO 6000's 96 GB limits scale.
B300's 4500 TFLOPS FP8 and 12000 GB/s bandwidth accelerate high-throughput quantized inference. RTX PRO 6000 suffices for smaller deployments but bottlenecks on volume.
RTX PRO 6000's 96 GB handles most fine-tuning at low $1.25 per hour cost. B300 overpowers for parameter-heavy tasks needing 288 GB.
RTX PRO 6000's 125 TFLOPS FP32 and PCIe form factor optimize image generation workflows efficiently. B300's 1200W TDP is excessive.
Balanced 125 TFLOPS FP32/FP16 on RTX PRO 6000 fits simulations within 96 GB VRAM at 400W. B300 targets AI-specific compute.
Frequently Asked Questions
Which GPU has more VRAM?▾
The B300 provides 288 GB HBM3e VRAM, exceeding the RTX PRO 6000's 96 GB GDDR7. This enables larger models on the B300. Bandwidth follows suit at 12000 GB/s versus 1792 GB/s.
What are the cloud pricing differences?▾
B300 pricing starts at $2.45 per hour with $6.44 average across seven offers. RTX PRO 6000 begins at $0.59 per hour, averaging $1.25 over five offers. Cost scales with performance.
Which is better for AI training?▾
B300 dominates with 2250 TFLOPS FP16 and 288 GB VRAM for large-scale training. RTX PRO 6000's 125 TFLOPS suits smaller jobs. Memory bandwidth of 12000 GB/s on B300 boosts batches.
How do power requirements compare?▾
B300 demands 1200W TDP in SXM form factors for datacenters. RTX PRO 6000 uses 400W PCIe for workstations. Efficiency favors RTX PRO 6000 in power-constrained setups.
What interconnects do they support?▾
Both feature NVLink, but B300 adds NVSwitch for multi-GPU clusters. This enhances scaling on B300. RTX PRO 6000 relies on PCIe for single-node use.
FP8 performance comparison?▾
B300 achieves 4500 TFLOPS FP8 for quantized inference. RTX PRO 6000 reaches 2000 TFLOPS. B300 accelerates low-precision workloads significantly faster.
Which is cheaper to rent, the B300 or the RTX PRO 6000?▾
Cloud rental prices for both the B300 and RTX PRO 6000 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 B300 have compared to the RTX PRO 6000?▾
The B300 has 288 GB of HBM3e memory. The RTX PRO 6000 has 96 GB of GDDR7 memory.
Can I find B300 and RTX PRO 6000 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 B300 and the RTX PRO 6000?▾
The B300 uses the Blackwell Ultra architecture (2025) while the RTX PRO 6000 uses Blackwell (2025). The B300 delivers 18.0x the FP16 throughput and 6.7x the memory bandwidth of the RTX PRO 6000.