NVIDIA B200 vs NVIDIA B300 — GPU Comparison (Apr 2026)
NVIDIA B200 (192GB HBM3e, 2,250 TFLOPS FP16, Blackwell) vs NVIDIA B300 (288GB HBM3e, 2,250 TFLOPS FP16, Blackwell Ultra). Cloud pricing: NVIDIA B200 from $1.99/hr. Compare specs, VRAM, performance, and pricing across 2 cloud providers to find the best GPU for your AI workload.
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NVIDIA B200
192GB HBM3e · Blackwell
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NVIDIA B300
288GB HBM3e · Blackwell Ultra
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|---|---|---|---|
| Specifications | |||
| Manufacturer | NVIDIA | NVIDIA | |
| Architecture | Blackwell | Blackwell Ultra | |
| VRAM | 192 GB HBM3e | 288 GB HBM3e | |
| Memory Bandwidth | 8,000 GB/s | 8,000 GB/s | |
| FP16 (Tensor) | 2250.0 TFLOPS | 2250.0 TFLOPS | |
| FP32 | 75.0 TFLOPS | 75.0 TFLOPS | |
| TDP | 1000W | 1400W | |
| Release Year | 2024 | 2025 | |
| Segment | Data center | Data center | |
| Best For | Next-gen AI training large model inference HPC | Frontier AI training largest model workloads | |
| Cloud Pricing | |||
| Cheapest On-Demand | $1.99/hr | — | |
| Cheapest Spot | $5.98/hr | — | |
| Providers | 2 | 1 | |
| Provider Pricing (On-Demand) | |||
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$1.99/hr | N/A | |
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$5.49/hr | N/A | |
NVIDIA B200
NVIDIA B300
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Vultr vs RunPod - GPU Provider Comparison (April 2026)
Head-to-head comparison of Vultr and RunPod. Compare GPU models, hourly pricing, billing granularity, spot instances, VRAM, infrastructure, developer tools, Kubernetes support, and compliance before choosing a provider. Data refreshed April 2026.
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Vultr
High-performance cloud GPU across 32 global regions
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RunPod
The cloud built for AI — deploy and scale GPU workloads from serverless inference to instant multi-node clusters on demand.
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|---|---|---|
| Overview | ||
| Trustpilot Rating | 1.8 | 3.7 |
| Headquarters | United States | United States |
| Provider Type | Multi-Cloud | GPU-Focused |
| Best For | AI training inference video rendering HPC Stable Diffusion game development generative AI fine-tuning research | AI training inference fine-tuning Stable Diffusion batch processing rendering research LLM serving generative AI |
| GPU Hardware | ||
| GPU Models | A16 A40 L40S A100 PCIe GH200 A100 SXM H100 SXM B200 B300 MI300X MI325X MI355X | B300 B200 H200 H100 SXM H100 PCIe H100 NVL MI300X A100 SXM A100 PCIe RTX 5090 RTX PRO 6000 L40S L40 RTX 6000 Ada RTX 5000 Ada RTX A6000 RTX A5000 RTX 4090 RTX 4080 SUPER RTX 4080 RTX 4070 Ti RTX 3090 Ti RTX 3090 RTX 3080 Ti RTX 3080 RTX 3070 A40 A30 A2 L4 |
| Max VRAM (GB) | 288 | 288 |
| Max GPUs/Instance | 16 | 8 |
| Interconnect | NVLink | NVLink |
| Pricing | ||
| Starting Price ($/hr) | $0.47/hr | $0.06/hr |
| Billing Granularity | Per-hour | Per-second |
| Spot/Preemptible | Yes | Yes |
| Reserved Discounts | N/A | 15-29% (1-month to 1-year plans) |
| Free Credits | Up to $300 free credit for 30 days | $5-$500 bonus after first $10 spend |
| Egress Fees | Standard (varies by plan) | None (Free) |
| Storage | 350 GB - 61 TB NVMe (included), Block Storage at $0.10/GB/mo, S3-compatible Object Storage | Container/Volume ($0.10/GB/mo), Idle Volume ($0.20/GB/mo), Network Storage ($0.07/GB/mo 1TB) |
| Infrastructure | ||
| Regions | 32 regions across 6 continents (Americas, Europe, Asia, Australia, Africa) | 31 global regions |
| Uptime SLA | 100% | 99.99% |
| Developer Experience | ||
| Frameworks | PyTorch TensorFlow CUDA cuDNN ROCm Hugging Face NVIDIA NGC | PyTorch TensorFlow JAX ONNX CUDA |
| Docker Support | Yes | Yes |
| SSH Access | Yes | Yes |
| Jupyter Notebooks | Yes | Yes |
| API / CLI | Yes | Yes |
| Setup Time | Minutes | Instant |
| Kubernetes Support | Yes | No |
| Business Terms | ||
| Min Commitment | None | None |
| Compliance | SOC 2+ (HIPAA) PCI ISO 27001 ISO 27017 ISO 27018 ISO 20000-1 CSA STAR Level 1 | SOC 2 Type II |
Vultr
RunPod
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