Specifications Compared
| Spec | B300 | RTX-5000-ADA |
|---|---|---|
| TDP | 1200W | 250W |
| VRAM | 288 GB | 32 GB |
| Memory Type | HBM3e | GDDR6 |
| Architecture | Blackwell Ultra | Ada Lovelace |
| Form Factors | SXM | PCIe |
| Interconnect | NVSwitch, NVLink | |
| FP8 Performance | 4,500 TFLOPS | |
| FP16 Performance | 2,250 TFLOPS | 65.3 TFLOPS |
| FP32 Performance | 90 TFLOPS | 65.3 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 4,500 TOPS | 1,044 TOPS |
| Memory Bandwidth | 12,000 GB/s | 576 GB/s |
Performance Analysis
The B300's FP16 performance reaches 2250 TFLOPS, dwarfing the RTX 5000 Ada's 65.3 TFLOPS, which accelerates AI training and inference for massive datasets. Its FP32 at 90 TFLOPS slightly exceeds the RTX 5000 Ada's 65.3 TFLOPS, but the real gap lies in low-precision FP8 at 4500 TFLOPS on B300, ideal for transformer models. This delta means B300 handles larger batch sizes in training, reducing epochs needed for convergence. Memory bandwidth defines scalability: B300's 12000 GB/s versus 576 GB/s enables processing models exceeding 100 GB without swapping, while RTX 5000 Ada limits to smaller batches around 32 GB VRAM. In inference, B300 supports enterprise-scale deployments; RTX 5000 Ada fits edge or prototyping. TDP reflects power: B300 at 1200W demands robust cooling, RTX 5000 Ada at 250W suits standard setups. Bandwidth disparity boosts B300 throughput by over 20x in memory-bound tasks like LLM fine-tuning.
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 | |||
 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 |
RTX 5000 Ada
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 0 vCPU 0GB RAM | Chubbuck, Idaho | $0.55/GPU/hr | Available | ||
RunPod | NVIDIA RTX 5000 Ada Generation 32GB VRAM | 32GB | 10 vCPU 83GB RAM | 🌍global | $0.83/GPU/hr |
When to Choose the B300
Choose the B300 for large-scale AI training where 288 GB HBM3e VRAM and 12000 GB/s bandwidth handle models over 100 billion parameters. Its 2250 TFLOPS FP16 outperforms in multi-GPU clusters via NVLink, cutting training time significantly. Datacenter users benefit from $2.45 per hour starting pricing for high-volume inference at 4500 TFLOPS FP8.
When to Choose the RTX 5000 Ada
Opt for RTX 5000 Ada in cost-sensitive workstations needing 32 GB GDDR6 for Stable Diffusion or visualization, with 65.3 TFLOPS FP32 matching FP16 for graphics. Its 250W TDP and $0.25 per hour pricing suit single-user prototyping without cluster overhead. PCIe form factor enables easy integration in non-datacenter environments.
Use Cases
B300's 288 GB VRAM and 2250 TFLOPS FP16 support massive models and large batches. RTX 5000 Ada's 32 GB limits scale.
4500 TFLOPS FP8 and 12000 GB/s bandwidth on B300 enable high-throughput serving. RTX 5000 Ada suits only small models.
B300 excels for large datasets with 90 TFLOPS FP32; RTX 5000 Ada handles smaller LoRAs at lower $0.51 per hour cost.
RTX 5000 Ada's 65.3 TFLOPS FP16 and 32 GB VRAM suffice for image generation. B300 overkill for single-instance use.
B300's 12000 GB/s bandwidth accelerates simulations; 288 GB VRAM fits complex datasets versus RTX 5000 Ada's constraints.
Frequently Asked Questions
What is the VRAM difference between B300 and RTX 5000 Ada?▾
B300 provides 288 GB HBM3e VRAM, nine times more than RTX 5000 Ada's 32 GB GDDR6. This allows B300 to load larger models without partitioning. RTX 5000 Ada fits mid-sized workloads.
How do FP16 performances compare?▾
B300 delivers 2250 TFLOPS FP16, over 34 times the RTX 5000 Ada's 65.3 TFLOPS. B300 accelerates deep learning training dramatically. RTX 5000 Ada performs adequately for inference.
What are the cloud pricing ranges?▾
B300 starts at $2.45 per hour, averaging $6.44 across 7 offers. RTX 5000 Ada begins at $0.25 per hour, averaging $0.51 across 5 offers. Choice depends on workload scale.
Which has higher memory bandwidth?▾
B300 offers 12000 GB/s, over 20 times RTX 5000 Ada's 576 GB/s. This boosts B300 in memory-intensive tasks like large batch training. RTX 5000 Ada suffices for lighter loads.
What are the TDP values?▾
B300 requires 1200W TDP for its compute power. RTX 5000 Ada uses 250W, easier for standard power supplies. B300 needs datacenter infrastructure.
Which GPU supports NVLink?▾
B300 includes NVSwitch and NVLink for multi-GPU scaling. RTX 5000 Ada lacks specified interconnects, relying on PCIe. B300 enables cluster efficiency.
Which is cheaper to rent, the B300 or the RTX 5000 Ada?▾
Cloud rental prices for both the B300 and RTX 5000 Ada 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 5000 Ada?▾
The B300 has 288 GB of HBM3e memory. The RTX 5000 Ada has 32 GB of GDDR6 memory.
Can I find B300 and RTX 5000 Ada 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 5000 Ada?▾
The B300 uses the Blackwell Ultra architecture (2025) while the RTX 5000 Ada uses Ada Lovelace (2023). The B300 delivers 34.5x the FP16 throughput and 20.8x the memory bandwidth of the RTX 5000 Ada.