NVIDIA B200 memory-bound vs compute-bound workloads
Sagot
NVIDIA B200 delivers 2,250 FP16 TFLOPS and 75 FP32 TFLOPS, backed by 8,000 GB/s of memory bandwidth and 192 GB of VRAM. In mixed-precision fine-tuning, those numbers typically convert to solid throughput on dense models up to several tens of billions of parameters.
For low-latency inference, real-world tokens-per-second on common large language models depends more on memory bandwidth than peak FLOPS — the 8,000 GB/s figure is the relevant ceiling for autoregressive decoding. On batched workloads like diffusion image generation, compute becomes the dominant factor again.
At $1.99 per hour on the budget-friendly cloud provider, performance-per-dollar is competitive for AI-heavy workloads.
Two tracked cloud providers currently offer NVIDIA B200: Vultr and RunPod. Vultr has the cheaper rate at $1.99/hr.
Higit pang FAQs tungkol sa NVIDIA B200
Vultr vs RunPod - Paghahambing ng GPU Provider (Abril 2026)
Direktang paghahambing ng Vultr at RunPod. Tingnan ang max funding, paghahati ng kita, araw-araw at pangkalahatang mga patakaran sa drawdown, leverage, mga assets na maaaring i-trade, dalas ng payout, mga paraan ng pagbabayad at payout, mga pahintulot sa trading at mga limitasyon sa KYC bago ka bumili ng challenge. Datos na na-refresh noong Abril 2026.
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Vultr
Mataas na pagganap na cloud GPU sa 32 pandaigdigang rehiyon
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RunPod
Ang ulap na ginawa para sa AI — mag-deploy at mag-scale ng GPU workloads mula sa serverless inference hanggang sa instant multi-node clusters ayon sa pangangailangan.
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| Pangkalahatang-ideya | ||
| Rating sa Trustpilot | 1.8 | 3.7 |
| Punong-tanggapan | United States | United States |
| Uri ng Provider | Multi-Cloud | Nakatuon sa GPU |
| Pinakamainam Para sa | Pagsasanay ng AI inference video rendering HPC Stable Diffusion pag-develop ng laro generative AI fine-tuning pananaliksik | AI training inference fine-tuning Stable Diffusion batch processing rendering research LLM serving generative AI |
| GPU Hardware | ||
| Mga Modelo ng GPU | A16 A40 L40S A100 PCIe GH200 A100 SXM H100 SXM B200 B300 MI300X MI325X MI355X | B300 B200 H200 H100 SXM H100 PCIe H100 NVL MI300X A100 SXM A100 PCIe RTX 5090 RTX PRO 6000 L40S L40 RTX 6000 Ada RTX 5000 Ada RTX A6000 RTX A5000 RTX 4090 RTX 4080 SUPER RTX 4080 RTX 4070 Ti RTX 3090 Ti RTX 3090 RTX 3080 Ti RTX 3080 RTX 3070 A40 A30 A2 L4 |
| Max VRAM (GB) | 288 | 288 |
| Max GPUs/Bawat Instance | 16 | 8 |
| Interconnect | NVLink | NVLink |
| Pagpepresyo | ||
| Simulang Presyo ($/oras) | $0.47/hr | $0.06/hr |
| Granularidad ng Pagsingil | Kada oras | Bawat segundo |
| Spot/Preemptible | Oo | Oo |
| Nakalaang Diskwento | Hindi naaangkop | 15-29% (mga plano mula 1 buwan hanggang 1 taon) |
| Libreng Kredito | Hanggang $300 libreng credit para sa 30 araw | $5-$500 na bonus pagkatapos ng unang $10 na gastusin |
| Bayad sa Paglabas | Standard (nag-iiba depende sa plano) | Wala (Libre) |
| Storage | 350 GB - 61 TB NVMe (kasama), Block Storage sa $0.10/GB/buwan, S3-compatible Object Storage | Container/Volume ($0.10/GB/buwan), Idle Volume ($0.20/GB/buwan), Network Storage ($0.07/GB/buwan 1TB) |
| Imprastruktura | ||
| Mga Rehiyon | 32 rehiyon sa 6 na kontinente (Americas, Europe, Asia, Australia, Africa) | 31 global na rehiyon |
| Uptime SLA | 100% | 99.99% |
| Karanasan ng Developer | ||
| Mga Framework | PyTorch TensorFlow CUDA cuDNN ROCm Hugging Face NVIDIA NGC | PyTorch TensorFlow JAX ONNX CUDA |
| Suporta sa Docker | Oo | Oo |
| SSH Access | Oo | Oo |
| Jupyter Notebooks | Oo | Oo |
| API / CLI | Oo | Oo |
| Oras ng Setup | Minuto | Agad-agad |
| Suporta sa Kubernetes | Oo | Hindi |
| Mga Termino ng Negosyo | ||
| Minimum na Commitment | Wala | Wala |
| Pagsunod sa Batas | SOC 2+ (HIPAA) PCI ISO 27001 ISO 27017 ISO 27018 ISO 20000-1 CSA STAR Level 1 | SOC 2 Type II |
Vultr
RunPod