Specifications Compared
| Spec | GB300 | L40S |
|---|---|---|
| TDP | 1400W | 350W |
| VRAM | 288 GB | 48 GB |
| Memory Type | HBM3e | GDDR6X |
| Architecture | Blackwell Ultra | Ada Lovelace |
| Form Factors | SXM | PCIe |
| Interconnect | NVSwitch, NVLink | PCIe 4.0 |
| FP8 Performance | 4,500 TFLOPS | 724 TFLOPS |
| FP16 Performance | 2,250 TFLOPS | 362 TFLOPS |
| FP32 Performance | 90 TFLOPS | 91 TFLOPS |
| FP64 Performance | 45 TFLOPS | 1.4 TFLOPS |
| INT8 Performance | 4,500 TOPS | 724 TOPS |
| Memory Bandwidth | 12,000 GB/s | 864 GB/s |
Performance Analysis
The GB300's FP16 performance of 2250 TFLOPS vastly outpaces the L40S's 362 TFLOPS, accelerating deep learning training by over six times in tensor operations central to model optimization. FP32 rates are similar at 90 TFLOPS for GB300 and 91 TFLOPS for L40S, ensuring balanced general-purpose computing without major gaps. For inference, the GB300's 4500 TFLOPS FP8 capability supports quantized models at higher speeds than the L40S's 724 TFLOPS, enabling more queries per second in production. The 288 GB VRAM on GB300 handles full loading of models exceeding 100 billion parameters, unlike the L40S's 48 GB limit that often requires model parallelism. Memory bandwidth defines batch size feasibility: GB300's 12000 GB/s sustains large batches for efficient training throughput, while L40S's 864 GB/s restricts scales in memory-bound tasks. These metrics translate to shorter epochs and lower latency in real-world AI pipelines.
Live Cloud Pricing
Real-time prices from 25+ providers. Updated every 60 seconds.
L40S
| Provider | GPU Model | VRAM | Host Specs | Region | Price | Status | Action | |
|---|---|---|---|---|---|---|---|---|
 TensorDock | NVIDIA L40S 48GB VRAM | 48GB | 0 vCPU 0GB RAM | Wolverhampton | $0.55/GPU/hr | Available | ||
 RunPod | NVIDIA L40S 48GB VRAM | 48GB | 16 vCPU 94GB RAM | 🌍global | $0.86/GPU/hr | |||
 Massed Compute | NVIDIA L40S 48GB VRAM | 48GB | 12 vCPU 72GB RAM 625GB Storage | Iowa | $0.88/GPU/hr | Available | ||
Massed Compute | 2×NVIDIA L40S 48GB VRAM | 48GB | 24 vCPU 144GB RAM 1250GB Storage | Iowa | $0.88/GPU/hr $1.76/hr total (2×) | Available | ||
Massed Compute | NVIDIA L40S 48GB VRAM | 48GB | 12 vCPU 72GB RAM 625GB Storage | Iowa | $0.88/GPU/hr | Available |
When to Choose the GB300 SXM6
Select the GB300 for large-scale LLM training where 288 GB HBM3e VRAM and 12000 GB/s bandwidth manage trillion-parameter models without fragmentation. Its 2250 TFLOPS FP16 and 4500 TFLOPS FP8 excel in multi-node clusters via NVSwitch and NVLink interconnects. High-throughput inference on massive deployments favors this GPU's SXM form factor and 1400W TDP capacity.
When to Choose the L40S
The L40S suits immediate deployments with pricing from $0.40 per hour and average $1.17 per hour across 21 offers. Its 350W TDP and PCIe 4.0 form factor enable easy integration into standard servers without specialized cooling. Choose it for cost-sensitive inference or fine-tuning where 48 GB VRAM and 362 TFLOPS FP16 suffice.
Use Cases
GB300's 2250 TFLOPS FP16 and 288 GB VRAM support training of models over 100 billion parameters at scale. L40S's 362 TFLOPS and 48 GB limit batch sizes severely.
GB300 delivers 4500 TFLOPS FP8 for high-throughput quantized serving. Its 12000 GB/s bandwidth handles large concurrent requests unlike L40S's 724 TFLOPS.
L40S's 48 GB VRAM and 362 TFLOPS FP16 handle most fine-tuning tasks cost-effectively. GB300's capacity shines for very large models.
L40S's 362 TFLOPS FP16 generates images efficiently at $0.40 per hour starting price. GB300 overkill for typical diffusion model sizes.
Comparable 91 TFLOPS FP32 on L40S matches workloads with lower 350W TDP. PCIe form factor simplifies non-AI HPC setups.
Frequently Asked Questions
What is the VRAM capacity of GB300 versus L40S?▾
GB300 provides 288 GB HBM3e VRAM, enabling full loading of massive AI models. L40S offers 48 GB GDDR6X, suitable for smaller or partitioned workloads. This sixfold difference impacts model scale in training and inference.
How do FP16 performances compare?▾
GB300 achieves 2250 TFLOPS FP16, over six times the L40S's 362 TFLOPS. This boosts training speed for deep learning. Inference benefits similarly in tensor-heavy phases.
What are the memory bandwidth specs?▾
GB300 delivers 12000 GB/s, nearly 14 times L40S's 864 GB/s. Higher bandwidth supports larger batch sizes and faster data movement. It reduces bottlenecks in memory-intensive AI tasks.
Is GB300 available for cloud rental now?▾
No live offers exist for GB300 currently. L40S has 21 offers from $0.40 per hour averaging $1.17 per hour. GB300 targets 2025 Blackwell Ultra rollout.
What are the power requirements?▾
GB300 demands 1400W TDP in SXM form factor with NVLink. L40S uses 350W in PCIe, easing deployment. Lower power aids dense rack configurations.
Which is better for FP8 inference?▾
GB300's 4500 TFLOPS FP8 outperforms L40S's 724 TFLOPS by over six times. This excels in quantized LLM serving. Bandwidth of 12000 GB/s further enhances throughput.
Which is cheaper to rent, the GB300 or the L40S?▾
Cloud rental prices for both the GB300 and L40S 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 GB300 have compared to the L40S?▾
The GB300 has 288 GB of HBM3e memory. The L40S has 48 GB of GDDR6X memory.
Can I find GB300 and L40S 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 GB300 and the L40S?▾
The GB300 uses the Blackwell Ultra architecture (2025) while the L40S uses Ada Lovelace (2023). The GB300 delivers 6.2x the FP16 throughput and 13.9x the memory bandwidth of the L40S.