Does Latitude.sh provide interruptible GPU instances at lower prices?
💡 Answer
Latitude.sh spot instance availability: 0
For workloads that can handle occasional interruptions — such as large-scale model training with regular checkpointing or batch processing jobs — spot instances provide substantial cost savings compared to on-demand pricing. Regular on-demand instances at Latitude.sh start at $0.35/hr.
See live spot pricing and interruption rates on Latitude.sh official website.
More FAQs about Latitude.sh
- What makes Latitude.sh different from other cloud GPU providers?
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- What free credits or promotional offers does Latitude.sh provide?
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These guides include Latitude.sh alongside other cloud GPU providers, grouped by hardware, pricing, features, and infrastructure.
Latitude.sh vs DigitalOcean vs Vultr - GPU Provider Comparison (March 2026)
Side-by-side comparison of Latitude.sh vs DigitalOcean vs Vultr. 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 March 2026.
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Latitude.sh
Bare metal GPU cloud across 23 global locations
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DigitalOcean
Simple, scalable GPU cloud for AI/ML
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Vultr
High-performance cloud GPU across 32 global regions
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|---|---|---|---|
| Overview | |||
| Trustpilot Rating | 3.7 | 4.6 | 1.8 |
| Headquarters | Brazil | United States | United States |
| Provider Type | Bare Metal | N/A | Multi-Cloud |
| Best For | AI training inference bare metal GPU fine-tuning research dedicated workloads generative AI | AI training inference fine-tuning LLM deployment LLM serving computer vision startups generative AI research | AI training inference video rendering HPC Stable Diffusion game development generative AI fine-tuning research |
| GPU Hardware | |||
| GPU Models | A30 RTX A5000 RTX A6000 L40S RTX 6000 Ada A100 SXM H100 SXM GH200 RTX PRO 6000 | RTX 4000 Ada RTX 6000 Ada L40S MI300X H100 SXM H200 | A16 A40 L40S A100 PCIe GH200 A100 SXM H100 SXM B200 B300 MI300X MI325X MI355X |
| Max VRAM (GB) | 96 | 192 | 288 |
| Max GPUs/Instance | 8 | 8 | 16 |
| Interconnect | NVLink | NVLink | NVLink |
| Pricing | |||
| Starting Price ($/hr) | $0.35/hr | $0.76/hr | $0.47/hr |
| Billing Granularity | Per-hour | Per-second | Per-hour |
| Spot/Preemptible | 0 | 0 | 1 |
| Reserved Discounts | N/A | N/A | N/A |
| Free Credits | $200 via referral program | $200 free credit for 60 days | Up to $300 free credit for 30 days |
| Egress Fees | None | None (included in plan) | Standard (varies by plan) |
| Storage | Local NVMe included (up to 4x 3.8TB), Block Storage $0.10/GB/mo, Filesystem Storage $0.05/GB/mo | 500-720 GiB NVMe boot (included), 5 TiB NVMe scratch on larger configs, Volumes at $0.10/GiB/mo | 350 GB - 61 TB NVMe (included), Block Storage at $0.10/GB/mo, S3-compatible Object Storage |
| Infrastructure | |||
| Regions | 23 locations: US (8 cities), LATAM (5), Europe (5), APAC (4), Mexico City. GPU in Dallas, Frankfurt, Sydney, Tokyo | New York (NYC2), Toronto (TOR1), Atlanta (ATL1), Richmond (RIC1), Amsterdam (AMS3) | 32 regions across 6 continents (Americas, Europe, Asia, Australia, Africa) |
| Uptime SLA | 99.9% | 99% | 100% |
| Developer Experience | |||
| Frameworks | ML-optimized images PyTorch TensorFlow (user-installed) CUDA | PyTorch TensorFlow Jupyter Miniconda CUDA ROCm Hugging Face | PyTorch TensorFlow CUDA cuDNN ROCm Hugging Face NVIDIA NGC |
| Docker Support | 1 | 1 | 1 |
| SSH Access | 1 | 1 | 1 |
| Jupyter Notebooks | 0 | 1 | 1 |
| API / CLI | 1 | 1 | 1 |
| Setup Time | Seconds | Minutes | Minutes |
| Kubernetes Support | 0 | 1 | 1 |
| Business Terms | |||
| Min Commitment | None | None | None |
| Compliance | Single-tenant isolation DPA available | SOC 2 Type II SOC 3 HIPAA (with BAA) CSA STAR Level 1 | SOC 2+ (HIPAA) PCI ISO 27001 ISO 27017 ISO 27018 ISO 20000-1 CSA STAR Level 1 |