What's the peak FP16 performance of NVIDIA L4?
💡 Answer
Released in 2023, NVIDIA L4 is an Ada Lovelace-class accelerator with 24 GB of GDDR6, 300 GB/s of memory bandwidth, and 121 FP16 TFLOPS of compute. FP32 peaks at 30.3 TFLOPS and the card draws up to 72W.
In practical terms: enough VRAM to load models into the ~24B-parameter range in FP16 (larger with quantisation), enough bandwidth to avoid memory-starving attention layers, and enough compute to train transformers at batch sizes that saturate modern optimisers.
Get NVIDIA L4 on RunPod starting at $0.39/hr — live pricing and fast provisioning.
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RunPod GPU Provider Review & Key Facts (April 2026)
Snapshot of RunPod: GPU models, pricing, billing granularity, infrastructure, developer tools, support channels, and compliance. Data verified April 2026.
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RunPod
The cloud built for AI — deploy and scale GPU workloads from serverless inference to instant multi-node clusters on demand.
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| Overview | |
| Trustpilot Rating | 3.7 |
| Headquarters | United States |
| Provider Type | GPU-Focused |
| Best For | AI training inference fine-tuning Stable Diffusion batch processing rendering research LLM serving generative AI |
| GPU Hardware | |
| GPU Models | B300 B200 H200 H100 SXM H100 PCIe H100 NVL MI300X A100 SXM A100 PCIe RTX 5090 RTX PRO 6000 L40S L40 RTX 6000 Ada RTX 5000 Ada RTX A6000 RTX A5000 RTX 4090 RTX 4080 SUPER RTX 4080 RTX 4070 Ti RTX 3090 Ti RTX 3090 RTX 3080 Ti RTX 3080 RTX 3070 A40 A30 A2 L4 |
| Max VRAM (GB) | 288 |
| Max GPUs/Instance | 8 |
| Interconnect | NVLink |
| Pricing | |
| Starting Price ($/hr) | $0.06/hr |
| Billing Granularity | Per-second |
| Spot/Preemptible | Yes |
| Reserved Discounts | 15-29% (1-month to 1-year plans) |
| Free Credits | $5-$500 bonus after first $10 spend |
| Egress Fees | None (Free) |
| Storage | Container/Volume ($0.10/GB/mo), Idle Volume ($0.20/GB/mo), Network Storage ($0.07/GB/mo 1TB) |
| Infrastructure | |
| Regions | 31 global regions |
| Uptime SLA | 99.99% |
| Developer Experience | |
| Frameworks | PyTorch TensorFlow JAX ONNX CUDA |
| Docker Support | Yes |
| SSH Access | Yes |
| Jupyter Notebooks | Yes |
| API / CLI | Yes |
| Setup Time | Instant |
| Kubernetes Support | No |
| Business Terms | |
| Min Commitment | None |
| Compliance | SOC 2 Type II |
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