Does Vultr support Hugging Face, vLLM, or other inference frameworks?
💡 Answer
Vultr provides the following pre-installed frameworks and tools:
PyTorch, TensorFlow, CUDA, cuDNN, ROCm, Hugging Face, NVIDIA NGC
Custom images: 1
Jupyter notebooks: 1
Persistent storage: 1
Having popular frameworks pre-installed means you can start training or inference immediately without spending time on environment setup. If you need a specific CUDA version or custom dependencies, custom image support lets you bring your own Docker container.
For pre-built templates and framework compatibility details, see Vultr official website.
More FAQs about Vultr
- What makes Vultr different from other cloud GPU providers?
- How many Trustpilot reviews does Vultr have, and what is its score?
- Can I SSH into GPU instances at Vultr?
- How does serverless GPU work at Vultr?
- How reliable is Vultr infrastructure?
- Does Vultr support multi-node GPU clusters?
- Does Vultr provide interruptible GPU instances at lower prices?
- What are the data transfer and storage fees at Vultr?
- What free credits or promotional offers does Vultr provide?
- What GPU hardware can I rent from Vultr?
- What does it cost to rent a GPU from Vultr?
Guides Where Vultr Is Featured
- Best Cloud GPU Providers with NVIDIA H200
- Best Cloud GPUs for AI Model Training
- Cheapest Cloud GPUs Under $0.50/hr
- Cloud GPU Providers with API & CLI Management
- Cloud GPU Providers with Docker & Custom Images
- Cloud GPU Providers with Free Credits
- Cloud GPU Providers with Jupyter Notebook Support
- Cloud GPU Providers with Kubernetes Support
- Cloud GPU Providers with Multi-Node GPU Clusters
- Cloud GPU Providers with NVLink or InfiniBand
- Cloud GPU Providers with Per-Second Billing
- Cloud GPU Providers with Persistent Storage
- Cloud GPU Providers with Serverless GPU Inference
- Cloud GPU Providers with Spot / Preemptible Instances
- Cloud GPU Providers with SSH Access
- Cloud GPU Providers with Zero Egress Fees
These guides include Vultr alongside other cloud GPU providers, grouped by hardware, pricing, features, and infrastructure.
Vultr vs Massed Compute vs RunPod - GPU Provider Comparison (April 2026)
Side-by-side comparison of Vultr vs Massed Compute vs RunPod. Quickly scan maximum funding, profit splits, risk rules, leverage, platforms, instruments, payout schedules, payment options, trading permissions and KYC restrictions to narrow down your prop trading firm shortlist. Data updated April 2026.
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Vultr
High-performance cloud GPU across 32 global regions
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Massed Compute
GPU cloud with direct engineer support
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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 | 0 | 3.8 |
| Headquarters | United States | United States | United States |
| Provider Type | Multi-Cloud | GPU-Focused | GPU-Focused |
| Best For | AI training inference video rendering HPC Stable Diffusion game development generative AI fine-tuning research | AI training inference VFX rendering generative AI fine-tuning HPC Stable Diffusion 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 | A30 RTX A5000 RTX A6000 L40S A100 SXM H100 PCIe H100 SXM H100 NVL RTX PRO 6000 H200 NVL | 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 | 141 | 288 |
| Max GPUs/Instance | 16 | 8 | 8 |
| Interconnect | NVLink | NVLink | NVLink |
| Pricing | |||
| Starting Price ($/hr) | $0.47/hr | $0.35/hr | $0.06/hr |
| Billing Granularity | Per-hour | Per-minute | Per-second |
| Spot/Preemptible | 1 | 0 | 1 |
| Reserved Discounts | N/A | N/A | 15-29% (1-month to 1-year plans) |
| Free Credits | Up to $300 free credit for 30 days | None | $5-$500 bonus after first $10 spend |
| Egress Fees | Standard (varies by plan) | None | None (Free) |
| Storage | 350 GB - 61 TB NVMe (included), Block Storage at $0.10/GB/mo, S3-compatible Object Storage | Local NVMe included with instances | 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) | United States (Tier III data centers) | 31 global regions |
| Uptime SLA | 100% | Tier III (99.98% design) | 99.99% |
| Developer Experience | |||
| Frameworks | PyTorch TensorFlow CUDA cuDNN ROCm Hugging Face NVIDIA NGC | PyTorch TensorFlow CUDA cuDNN ComfyUI pre-configured ML templates | PyTorch TensorFlow JAX ONNX CUDA |
| Docker Support | 1 | 1 | 1 |
| SSH Access | 1 | 1 | 1 |
| Jupyter Notebooks | 1 | 0 | 1 |
| API / CLI | 1 | 1 | 1 |
| Setup Time | Minutes | Minutes | Instant |
| Kubernetes Support | 1 | 0 | 0 |
| Business Terms | |||
| Min Commitment | None | None | None |
| Compliance | SOC 2+ (HIPAA) PCI ISO 27001 ISO 27017 ISO 27018 ISO 20000-1 CSA STAR Level 1 | SOC 2 Type II HIPAA | SOC 2 Type II |