Specifications Compared
| Spec | B300 | L4 |
|---|---|---|
| TDP | 1200W | 72W |
| VRAM | 288 GB | 24 GB |
| Memory Type | HBM3e | GDDR6 |
| Architecture | Blackwell Ultra | Ada Lovelace |
| Form Factors | SXM | PCIe |
| Interconnect | NVSwitch, NVLink | PCIe 4.0 |
| FP8 Performance | 4,500 TFLOPS | 242 TFLOPS |
| FP16 Performance | 2,250 TFLOPS | 121 TFLOPS |
| FP32 Performance | 90 TFLOPS | 30.3 TFLOPS |
| FP64 Performance | 45 TFLOPS | 0.5 TFLOPS |
| INT8 Performance | 4,500 TOPS | 242 TOPS |
| Memory Bandwidth | 12,000 GB/s | 300 GB/s |
Performance Analysis
The B300 SXM6 vastly outpaces the L4 in compute: 2250 TFLOPS FP16 and 90 TFLOPS FP32 versus 121 TFLOPS FP16 and 30.3 TFLOPS FP32. This translates to approximately 18 times higher FP16 throughput on the B300, ideal for accelerating large-scale AI model training where mixed-precision computations dominate. FP32 advantages support scientific simulations requiring precise floating-point operations.
Memory specs define real-world limits: the B300's 288 GB HBM3e at 12000 GB/s enables massive batch sizes for training billion-parameter LLMs, reducing iteration times. The L4's 24 GB GDDR6 at 300 GB/s suits smaller batches in inference, where lower latency matters over capacity. NVSwitch and NVLink on the B300 facilitate multi-GPU scaling, unlike the L4's PCIe 4.0 interconnect.
Power efficiency highlights trade-offs: the L4's 72W TDP allows dense deployments, while the B300's 1200W demands robust cooling for sustained 4500 TFLOPS FP8 inference peaks.
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 |
L4
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 Vast.ai | NVIDIA L4 24GB VRAM | 24GB | 64 vCPU 101GB RAM 485GB Storage | Iceland | $0.33/GPU/hr | Available | ||
RunPod | NVIDIA L4 24GB VRAM | 24GB | 12 vCPU 50GB RAM | 🌍global | $0.39/GPU/hr | |||
 TensorDock | NVIDIA L40S 48GB VRAM | 48GB | 0 vCPU 0GB RAM | Wolverhampton | $0.55/GPU/hr | Available | ||
RunPod | NVIDIA L40 48GB VRAM | 48GB | 8 vCPU 94GB RAM | 🌍global | $0.82/GPU/hr | |||
RunPod | NVIDIA L40S 48GB VRAM | 48GB | 16 vCPU 94GB RAM | 🌍global | $0.86/GPU/hr |
When to Choose the B300 SXM6
Opt for the NVIDIA B300 SXM6 in scenarios demanding extreme scale, such as training LLMs with over 288 GB VRAM requirements or datasets needing 12000 GB/s bandwidth for large batches. Its 2250 TFLOPS FP16 performance excels in multi-node clusters via NVLink, justifying $2.45 per hour starting costs for production AI pipelines.
When to Choose the L4
Select the NVIDIA L4 for budget-conscious inference on models fitting within 24 GB GDDR6, where 300 GB/s bandwidth and 72W TDP enable low-cost, high-density deployments. At $0.32 per hour average $0.68 per hour, it suits edge computing or prototyping without the B300's infrastructure overhead.
Use Cases
The B300's 288 GB HBM3e VRAM and 2250 TFLOPS FP16 support massive models and large batches unattainable on the L4's 24 GB GDDR6.
B300's 4500 TFLOPS FP8 and 12000 GB/s bandwidth handle high-throughput serving for large LLMs; L4 limits scale with 242 TFLOPS FP8.
B300 accommodates full-model fine-tuning via 288 GB VRAM, while L4's 24 GB restricts to parameter-efficient methods.
L4's 121 TFLOPS FP16 suffices for real-time generation on modest resolutions; B300 accelerates high-res or batch jobs with 2250 TFLOPS.
L4's 30.3 TFLOPS FP32 and 72W TDP fit precise simulations in clusters; B300's 90 TFLOPS FP32 overkills for most non-AI tasks.
Frequently Asked Questions
What is the VRAM difference between NVIDIA B300 SXM6 and L4?▾
The B300 SXM6 provides 288 GB HBM3e VRAM, while the L4 offers 24 GB GDDR6. This 12-fold gap allows the B300 to load massive models entirely in memory.
How do FP16 performances compare?▾
B300 SXM6 achieves 2250 TFLOPS FP16 versus L4's 121 TFLOPS. The B300 processes AI training workloads nearly 19 times faster in half-precision.
What are the cloud pricing ranges?▾
NVIDIA B300 SXM6 starts at $2.45 per hour averaging $6.44 per hour across 7 offers. NVIDIA L4 begins at $0.32 per hour averaging $0.68 per hour over 15 offers.
Which has higher memory bandwidth?▾
B300 SXM6 delivers 12000 GB/s with HBM3e, compared to L4's 300 GB/s GDDR6. This enables 40 times larger data throughput for batch processing.
What are the power requirements?▾
The B300 SXM6 has a 1200W TDP suited for data centers, while L4 uses 72W for efficient PCIe setups. L4 consumes 17 times less power.
Can L4 scale like B300?▾
L4 relies on PCIe 4.0 interconnects limiting multi-GPU efficiency, unlike B300's NVSwitch and NVLink. B300 supports seamless large-scale clusters.
Which is cheaper to rent, the B300 or the L4?▾
Cloud rental prices for both the B300 and L4 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 L4?▾
The B300 has 288 GB of HBM3e memory. The L4 has 24 GB of GDDR6 memory.
Can I find B300 and L4 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 L4?▾
The B300 uses the Blackwell Ultra architecture (2025) while the L4 uses Ada Lovelace (2023). The B300 delivers 18.6x the FP16 throughput and 40.0x the memory bandwidth of the L4.