How well does NVIDIA L4 scale across multiple GPUs?
Sagot
121 FP16 TFLOPS and 300 GB/s of memory bandwidth put NVIDIA L4 squarely in the class of accelerators targeted at modern transformer workloads. FP32 caps at 30.3 TFLOPS, which still handles most non-AI scientific compute comfortably.
For training from scratch, token throughput roughly tracks FP16 TFLOPS. For production inference on foundation models, throughput tracks bandwidth. Real-world numbers will depend heavily on the framework stack (PyTorch, TensorRT-LLM, vLLM), and can vary 30-50% depending on how aggressively you quantise.
The cheapest NVIDIA L4 cloud access right now is on RunPod at $0.39/hr.
Higit pang FAQs tungkol sa NVIDIA L4
Pagsusuri ng RunPod GPU Provider at Pangunahing Impormasyon (Abril 2026)
Snapshot ng RunPod: pinakamataas na pondo, paghahati ng kita, mga patakaran sa drawdown, leverage, mga instrumento, iskedyul ng payout, mga paraan ng pagbabayad, mga pahintulot sa trading at KYC. Datos na na-verify noong Abril 2026.
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RunPod
Ang ulap na ginawa para sa AI — mag-deploy at mag-scale ng GPU workloads mula sa serverless inference hanggang sa instant multi-node clusters ayon sa pangangailangan.
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| Pangkalahatang-ideya | |
| Rating sa Trustpilot | 3.7 |
| Punong-tanggapan | United States |
| Uri ng Provider | Nakatuon sa GPU |
| Pinakamainam Para sa | AI training inference fine-tuning Stable Diffusion batch processing rendering research LLM serving generative AI |
| GPU Hardware | |
| Mga Modelo ng GPU | B300 B200 H200 H100 SXM H100 PCIe H100 NVL MI300X A100 SXM A100 PCIe RTX 5090 RTX PRO 6000 L40S L40 RTX 6000 Ada RTX 5000 Ada RTX A6000 RTX A5000 RTX 4090 RTX 4080 SUPER RTX 4080 RTX 4070 Ti RTX 3090 Ti RTX 3090 RTX 3080 Ti RTX 3080 RTX 3070 A40 A30 A2 L4 |
| Max VRAM (GB) | 288 |
| Max GPUs/Bawat Instance | 8 |
| Interconnect | NVLink |
| Pagpepresyo | |
| Simulang Presyo ($/oras) | $0.06/hr |
| Granularidad ng Pagsingil | Bawat segundo |
| Spot/Preemptible | Oo |
| Nakalaang Diskwento | 15-29% (mga plano mula 1 buwan hanggang 1 taon) |
| Libreng Kredito | $5-$500 na bonus pagkatapos ng unang $10 na gastusin |
| Bayad sa Paglabas | Wala (Libre) |
| Storage | Container/Volume ($0.10/GB/buwan), Idle Volume ($0.20/GB/buwan), Network Storage ($0.07/GB/buwan 1TB) |
| Imprastruktura | |
| Mga Rehiyon | 31 global na rehiyon |
| Uptime SLA | 99.99% |
| Karanasan ng Developer | |
| Mga Framework | PyTorch TensorFlow JAX ONNX CUDA |
| Suporta sa Docker | Oo |
| SSH Access | Oo |
| Jupyter Notebooks | Oo |
| API / CLI | Oo |
| Oras ng Setup | Agad-agad |
| Suporta sa Kubernetes | Hindi |
| Mga Termino ng Negosyo | |
| Minimum na Commitment | Wala |
| Pagsunod sa Batas | SOC 2 Type II |
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