Specifications Compared
| Spec | B300 | QUADRO-RTX-6000 |
|---|---|---|
| TDP | 1200W | 260W |
| VRAM | 288 GB | 24 GB |
| Memory Type | HBM3e | GDDR6 |
| Architecture | Blackwell Ultra | Turing |
| Form Factors | SXM | PCIe |
| Interconnect | NVSwitch, NVLink | NVLink |
| FP8 Performance | 4,500 TFLOPS | |
| FP16 Performance | 2,250 TFLOPS | 16.3 TFLOPS |
| FP32 Performance | 90 TFLOPS | 16.3 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 4,500 TOPS | |
| Memory Bandwidth | 12,000 GB/s | 672 GB/s |
Performance Analysis
The NVIDIA B300 SXM6 vastly outpaces the Quadro RTX 6000 in compute throughput: its 2250 TFLOPS FP16 performance enables training of trillion-parameter models in hours, while the Quadro's 16.3 TFLOPS limits it to smaller datasets taking days. The B300's FP32 at 90 TFLOPS supports precise simulations, exceeding the Quadro's matched 16.3 TFLOPS by over five times. This FP16-to-FP32 ratio on the B300 favors mixed-precision training, reducing time by leveraging 2250 TFLOPS for forward passes.
Memory specs dictate real-world scalability. The B300's 288 GB HBM3e VRAM handles models exceeding 100 billion parameters without swapping, unlike the Quadro's 24 GB GDDR6 cap. Bandwidth at 12000 GB/s on the B300 supports batch sizes up to thousands in inference, minimizing latency; the Quadro's 672 GB/s restricts batches to dozens, bottlenecking large-scale deployments. The B300's 1200W TDP demands robust cooling, contrasting the Quadro's efficient 260W.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
B300 SXM6
| 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 | |||
 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 SXM6
The NVIDIA B300 SXM6 excels in datacenter environments for LLM training and inference on models with over 288 GB VRAM needs. Its 4500 TFLOPS FP8 performance accelerates quantized inference, ideal for serving billions of tokens daily. Multi-node setups via NVSwitch benefit from 12000 GB/s bandwidth, enabling clusters processing petabytes of data.
Cloud users prioritize the B300 for on-demand scaling at $2.45 per hour starting price across seven providers.
When to Choose the Quadro RTX 6000
The NVIDIA Quadro RTX 6000 fits legacy workstation setups where 24 GB GDDR6 VRAM suffices for CAD or moderate rendering at 16.3 TFLOPS FP32. Its 260W TDP and PCIe form factor integrate easily into existing desktops without high power infrastructure. Cost-conscious users with no cloud needs avoid the B300's $6.44 per hour average.
Use Cases
The B300's 2250 TFLOPS FP16 and 288 GB HBM3e VRAM enable training of trillion-parameter models. The Quadro's 16.3 TFLOPS and 24 GB GDDR6 cannot scale to such sizes.
B300's 4500 TFLOPS FP8 and 12000 GB/s bandwidth support massive batch inference. Quadro lacks capacity for production-scale serving.
B300 handles full-model fine-tuning with 90 TFLOPS FP32 on 288 GB VRAM. Quadro restricts to parameter-efficient methods on 24 GB.
B300 generates images at scale with 2250 TFLOPS FP16 for diffusion steps. Quadro manages basic generation but not high-resolution batches.
B300's 90 TFLOPS FP32 and NVLink accelerate simulations on large grids. Quadro suits small-scale desktop computations only.
Frequently Asked Questions
What is the VRAM difference between NVIDIA B300 SXM6 and Quadro RTX 6000?▾
The B300 SXM6 features 288 GB HBM3e VRAM, twelve times more than the Quadro RTX 6000's 24 GB GDDR6. This allows the B300 to load massive AI models without offloading. The Quadro suits smaller datasets.
How do FP16 performances compare?▾
B300 SXM6 delivers 2250 TFLOPS FP16, over 138 times the Quadro RTX 6000's 16.3 TFLOPS. This gap accelerates deep learning training significantly. Inference also benefits from the B300's scale.
What are the power requirements?▾
The B300 SXM6 has a 1200W TDP, requiring datacenter power setups. The Quadro RTX 6000 uses 260W, fitting standard workstations. Efficiency favors the Quadro for low-power needs.
Is the Quadro RTX 6000 available in the cloud?▾
No live cloud offers exist for the Quadro RTX 6000. The B300 SXM6 starts at $2.45 per hour across seven providers, averaging $6.44 per hour. On-premises use defines the Quadro.
Which has higher memory bandwidth?▾
B300 SXM6 achieves 12000 GB/s, nearly 18 times the Quadro RTX 6000's 672 GB/s. Larger batches and faster data movement result on the B300. This impacts training throughput directly.
What architectures do they use?▾
B300 SXM6 uses Blackwell Ultra from 2025 with FP8 support at 4500 TFLOPS. Quadro RTX 6000 relies on Turing from 2018 without such capabilities. Generational leap favors the B300.
Which is cheaper to rent, the B300 or the Quadro RTX 6000?▾
Cloud rental prices for both the B300 and Quadro RTX 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 Quadro RTX 6000?▾
The B300 has 288 GB of HBM3e memory. The Quadro RTX 6000 has 24 GB of GDDR6 memory.
Can I find B300 and Quadro RTX 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 Quadro RTX 6000?▾
The B300 uses the Blackwell Ultra architecture (2025) while the Quadro RTX 6000 uses Turing (2018). The B300 delivers 138.0x the FP16 throughput and 17.9x the memory bandwidth of the Quadro RTX 6000.