Specifications Compared
| Spec | B300 | P100 |
|---|---|---|
| TDP | 1200W | 250W |
| VRAM | 288 GB | 16 GB |
| Memory Type | HBM3e | HBM2 |
| Architecture | Blackwell Ultra | Pascal |
| Form Factors | SXM | SXM2, PCIe |
| Interconnect | NVSwitch, NVLink | NVLink |
| FP8 Performance | 4,500 TFLOPS | |
| FP16 Performance | 2,250 TFLOPS | 9.3 TFLOPS |
| FP32 Performance | 90 TFLOPS | 9.3 TFLOPS |
| FP64 Performance | 45 TFLOPS | 4.7 TFLOPS |
| INT8 Performance | 4,500 TOPS | |
| Memory Bandwidth | 12,000 GB/s | 732 GB/s |
Performance Analysis
The B300's FP16 performance of 2250 TFLOPS vastly outpaces the P100's 9.3 TFLOPS, enabling faster deep learning training where half-precision computations dominate: training epochs complete over 240 times quicker on B300 for equivalent workloads. In contrast, P100 maintains parity between FP16 and FP32 at 9.3 TFLOPS each, suiting balanced precision tasks from its era, but B300's FP32 reaches 90 TFLOPS, still 9.7 times higher. For inference, B300's FP8 capability at 4500 TFLOPS accelerates low-precision serving, reducing latency for large language models. Memory bandwidth defines practical limits: B300's 12000 GB/s supports batch sizes up to 16 times larger than P100's 732 GB/s, minimizing out-of-memory errors in transformer models and boosting throughput. Power draw reflects this: B300's 1200W TDP demands robust cooling versus P100's efficient 250W, impacting deployment density.
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 | 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 |
Tesla P100
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 LeaderGPU | 2×NVIDIA Tesla P100 16GB VRAM | 16GB | 0 vCPU 256GB RAM 960GB Storage | Netherlands | $0.60/GPU/hr $1.20/hr total (2×) | Available |
When to Choose the B300 SXM6
Opt for the B300 in scenarios demanding extreme scale, such as training trillion-parameter LLMs, where 288 GB HBM3e VRAM and 2250 TFLOPS FP16 enable handling full model contexts without sharding. Its 12000 GB/s bandwidth sustains massive batch sizes in inference pipelines, ideal for enterprise AI serving at $2.45 per hour starting price across SXM form factors with NVSwitch interconnects.
When to Choose the Tesla P100
Select the P100 for cost-sensitive legacy applications, like reproducing 2016-era experiments or running small-scale FP32 simulations at 9.3 TFLOPS, where 16 GB HBM2 suffices and $0.07 per hour pricing minimizes expenses. It fits PCIe or SXM2 deployments with NVLink for modest multi-GPU setups without high TDP of 250W straining budgets.
Use Cases
B300's 288 GB HBM3e VRAM and 2250 TFLOPS FP16 support training massive LLMs without partitioning, unlike P100's 16 GB constraint. Its 12000 GB/s bandwidth accelerates data movement for large batches.
B300 excels with 4500 TFLOPS FP8 and 12000 GB/s bandwidth for high-throughput serving of billion-parameter models. P100's 9.3 TFLOPS FP16 cannot match latency or scale.
The 288 GB VRAM on B300 accommodates full fine-tuning datasets, with 90 TFLOPS FP32 outperforming P100's 9.3 TFLOPS. Bandwidth enables efficient gradient computations.
B300's high FP16 performance and vast memory generate high-resolution images rapidly, far beyond P100's capabilities limited by 16 GB VRAM.
B300's 90 TFLOPS FP32 and NVSwitch interconnect speed simulations like molecular dynamics, surpassing P100's 9.3 TFLOPS for complex datasets.
Frequently Asked Questions
What is the VRAM difference between B300 and P100?▾
The B300 offers 288 GB HBM3e VRAM, 18 times more than the P100's 16 GB HBM2. This enables B300 to load much larger AI models entirely in memory. P100 suits smaller workloads from its Pascal era.
How do their FP16 performances compare?▾
B300 achieves 2250 TFLOPS in FP16, over 242 times the P100's 9.3 TFLOPS. This gap accelerates modern deep learning training on B300. P100 provides baseline half-precision for legacy tasks.
What are the current cloud rental prices?▾
B300 SXM6 starts at $2.45 per hour, averaging $6.44 across seven offers. P100 begins at $0.07 per hour, averaging $0.25 across three offers. Pricing reflects performance disparities.
Which has higher memory bandwidth?▾
B300 delivers 12000 GB/s, 16.4 times the P100's 732 GB/s. Higher bandwidth on B300 supports larger batch sizes in training. P100 suffices for modest data flows.
What are their TDPs?▾
B300 requires 1200W TDP for its capabilities, compared to P100's 250W. B300 demands advanced cooling in SXM form factors. P100 offers power efficiency for dense deployments.
Can P100 handle modern LLMs?▾
P100's 16 GB VRAM limits it to small models under its 9.3 TFLOPS FP16. B300's 288 GB and 2250 TFLOPS FP16 manage large LLMs effectively. Use P100 only for compatibility with old code.
Which is cheaper to rent, the B300 or the P100?▾
Cloud rental prices for both the B300 and P100 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 P100?▾
The B300 has 288 GB of HBM3e memory. The P100 has 16 GB of HBM2 memory.
Can I find B300 and P100 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 P100?▾
The B300 uses the Blackwell Ultra architecture (2025) while the P100 uses Pascal (2016). The B300 delivers 241.9x the FP16 throughput and 16.4x the memory bandwidth of the P100.