Specifications Compared
| Spec | B300 | RTX-2070 |
|---|---|---|
| TDP | 1200W | 175W |
| VRAM | 288 GB | 8 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 | 7.5 TFLOPS |
| FP32 Performance | 90 TFLOPS | 7.5 TFLOPS |
| FP64 Performance | 45 TFLOPS | |
| INT8 Performance | 4,500 TOPS | |
| Memory Bandwidth | 12,000 GB/s | 448 GB/s |
Performance Analysis
Compute disparities define usability: the B300 SXM6 achieves 2250 TFLOPS in FP16 versus the RTX 2070 SUPER's 9 TFLOPS, accelerating AI training where half-precision dominates. Its 90 TFLOPS FP32 outstrips the 2070 SUPER's 9 TFLOPS, benefiting simulations requiring full precision. This gap translates to training large language models in hours on B300 versus weeks on 2070 SUPER.
Memory capacity and speed are critical: 288 GB HBM3e on B300 SXM6 supports massive batch sizes for stable training, unlike the 8 GB GDDR6 limit on 2070 SUPER that forces tiny batches or out-of-memory errors. The 12000 GB/s bandwidth eliminates data starvation in inference pipelines, compared to 448 GB/s bottlenecks on 2070 SUPER. FP8 at 4500 TFLOPS further optimizes B300 for quantized inference at scale.
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 | |||
 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 SXM6
Select the NVIDIA B300 SXM6 for demanding AI workloads such as training billion-parameter models: 288 GB VRAM accommodates full datasets, and 2250 TFLOPS FP16 delivers rapid iterations. NVSwitch and NVLink enable multi-GPU clusters, with cloud pricing from $2.45 per hour suiting scalable enterprise deployments.
High TDP of 1200W reflects datacenter optimization, ideal where power efficiency yields to throughput.
When to Choose the RTX 2070 SUPER
The NVIDIA GeForce RTX 2070 SUPER suits budget desktop gaming or hobbyist compute: its 215W TDP integrates into consumer PCs via PCIe, avoiding cloud costs like $6.44 per hour average for B300. 8 GB VRAM handles small-scale fine-tuning or Stable Diffusion at 1080p resolutions.
Local ownership eliminates rental fees, perfect for intermittent personal projects without datacenter needs.
Use Cases
B300 SXM6's 288 GB VRAM and 2250 TFLOPS FP16 handle massive models and large batches; RTX 2070 SUPER's 8 GB VRAM causes out-of-memory failures.
4500 TFLOPS FP8 and 12000 GB/s bandwidth on B300 SXM6 support high-throughput serving; 2070 SUPER's 448 GB/s limits scale.
90 TFLOPS FP32 and 288 GB capacity accelerate precise adaptations on B300; 2070 SUPER suffices only for tiny models.
RTX 2070 SUPER generates images at 9 TFLOPS FP16 for local use; B300 SXM6 excels in batch production with 2250 TFLOPS.
B300's 1200W TDP and NVLink scale simulations via 90 TFLOPS FP32; 2070 SUPER's PCIe restricts complex runs.
Frequently Asked Questions
What is the VRAM difference between NVIDIA B300 SXM6 and RTX 2070 SUPER?▾
The B300 SXM6 provides 288 GB HBM3e VRAM, enabling large model handling. The RTX 2070 SUPER offers 8 GB GDDR6, suitable for smaller tasks. This 36-fold gap impacts batch sizes directly.
How do FP16 performances compare?▾
B300 SXM6 delivers 2250 TFLOPS FP16 for rapid AI training. RTX 2070 SUPER reaches 9 TFLOPS, adequate for basic inference. The difference speeds up deep learning by orders of magnitude.
What are the cloud pricing details?▾
NVIDIA B300 SXM6 starts at $2.45 per hour, averaging $6.44 across 7 offers. No live cloud offers exist for RTX 2070 SUPER. Local purchase avoids hourly fees.
Which has higher memory bandwidth?▾
B300 SXM6 achieves 12000 GB/s with HBM3e, preventing inference bottlenecks. RTX 2070 SUPER provides 448 GB/s GDDR6. This supports larger data flows on B300.
What are the TDP ratings?▾
B300 SXM6 requires 1200W for datacenter power delivery. RTX 2070 SUPER uses 215W, fitting consumer systems. Higher TDP correlates with B300's compute density.
Can RTX 2070 SUPER run modern AI workloads?▾
RTX 2070 SUPER manages light fine-tuning with 9 TFLOPS FP32 and 8 GB VRAM. It struggles with large LLMs due to memory limits. B300 SXM6 handles them effortlessly.
Which is cheaper to rent, the B300 or the RTX 2070?▾
Cloud rental prices for both the B300 and RTX 2070 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 2070?▾
The B300 has 288 GB of HBM3e memory. The RTX 2070 has 8 GB of GDDR6 memory.
Can I find B300 and RTX 2070 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 2070?▾
The B300 uses the Blackwell Ultra architecture (2025) while the RTX 2070 uses Turing (2018). The B300 delivers 300.0x the FP16 throughput and 26.8x the memory bandwidth of the RTX 2070.