What multi-GPU options are available at Massed Compute for large-scale training?
💡 Answer
Multi-GPU and distributed training capabilities at Massed Compute:
- Interconnect: NVLink
- Max GPUs per instance: 8
- Multi-node clusters: 1
For training large models like LLMs that require multiple GPUs, the interconnect bandwidth directly impacts training throughput. High-bandwidth interconnects like NVLink and InfiniBand minimize the communication overhead during gradient synchronization, resulting in near-linear scaling across GPUs.
View NVLink and InfiniBand configurations at Massed Compute official website.
More FAQs about Massed Compute
- What are the primary use cases for Massed Compute?
- How trustworthy is Massed Compute based on its Trustpilot rating?
- What deep learning frameworks are available out of the box at Massed Compute?
- Does Massed Compute offer Jupyter Notebook support for GPU development?
- Can I deploy models on Massed Compute that only run when called?
- What availability zones does Massed Compute offer?
- What savings can I get from spot instances at Massed Compute?
- Does Massed Compute charge for downloading model weights or training outputs?
- Is there a way to test Massed Compute GPU instances without paying?
- How many GPU models does Massed Compute have in its fleet?
- What billing model does Massed Compute use for cloud GPU services?
Guides Where Massed Compute Is Featured
- Best Cloud GPU Providers with NVIDIA GH200
- Best Cloud GPUs for Inference & Model Serving
- Cheapest Cloud GPUs Under $1/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 Massed Compute alongside other cloud GPU providers, grouped by hardware, pricing, features, and infrastructure.
Massed Compute vs Vultr vs Latitude.sh - GPU Provider Comparison (March 2026)
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Massed Compute
GPU cloud with direct engineer support
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Vultr
High-performance cloud GPU across 32 global regions
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Latitude.sh
Bare metal GPU cloud across 23 global locations
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|---|---|---|---|
| Overview | |||
| Trustpilot Rating | 0 | 1.8 | 3.7 |
| Headquarters | United States | United States | Brazil |
| Provider Type | GPU-Focused | Multi-Cloud | Bare Metal |
| Best For | AI training inference VFX rendering generative AI fine-tuning HPC Stable Diffusion research | AI training inference video rendering HPC Stable Diffusion game development generative AI fine-tuning research | AI training inference bare metal GPU fine-tuning research dedicated workloads generative AI |
| GPU Hardware | |||
| GPU Models | A30 RTX A5000 RTX A6000 L40S A100 SXM H100 PCIe H100 SXM H100 NVL RTX PRO 6000 H200 NVL | A16 A40 L40S A100 PCIe GH200 A100 SXM H100 SXM B200 B300 MI300X MI325X MI355X | A30 RTX A5000 RTX A6000 L40S RTX 6000 Ada A100 SXM H100 SXM GH200 RTX PRO 6000 |
| Max VRAM (GB) | 141 | 288 | 96 |
| Max GPUs/Instance | 8 | 16 | 8 |
| Interconnect | NVLink | NVLink | NVLink |
| Pricing | |||
| Starting Price ($/hr) | $0.35/hr | $0.47/hr | $0.35/hr |
| Billing Granularity | Per-minute | Per-hour | Per-hour |
| Spot/Preemptible | 0 | 1 | 0 |
| Reserved Discounts | N/A | N/A | N/A |
| Free Credits | None | Up to $300 free credit for 30 days | $200 via referral program |
| Egress Fees | None | Standard (varies by plan) | None |
| Storage | Local NVMe included with instances | 350 GB - 61 TB NVMe (included), Block Storage at $0.10/GB/mo, S3-compatible Object Storage | Local NVMe included (up to 4x 3.8TB), Block Storage $0.10/GB/mo, Filesystem Storage $0.05/GB/mo |
| Infrastructure | |||
| Regions | United States (Tier III data centers) | 32 regions across 6 continents (Americas, Europe, Asia, Australia, Africa) | 23 locations: US (8 cities), LATAM (5), Europe (5), APAC (4), Mexico City. GPU in Dallas, Frankfurt, Sydney, Tokyo |
| Uptime SLA | Tier III (99.98% design) | 100% | 99.9% |
| Developer Experience | |||
| Frameworks | PyTorch TensorFlow CUDA cuDNN ComfyUI pre-configured ML templates | PyTorch TensorFlow CUDA cuDNN ROCm Hugging Face NVIDIA NGC | ML-optimized images PyTorch TensorFlow (user-installed) CUDA |
| Docker Support | 1 | 1 | 1 |
| SSH Access | 1 | 1 | 1 |
| Jupyter Notebooks | 0 | 1 | 0 |
| API / CLI | 1 | 1 | 1 |
| Setup Time | Minutes | Minutes | Seconds |
| Kubernetes Support | 0 | 1 | 0 |
| Business Terms | |||
| Min Commitment | None | None | None |
| Compliance | SOC 2 Type II HIPAA | SOC 2+ (HIPAA) PCI ISO 27001 ISO 27017 ISO 27018 ISO 20000-1 CSA STAR Level 1 | Single-tenant isolation DPA available |