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Review

Latitude.sh Review 2026: Bare-Metal GPU Cloud for Serious AI Teams

3/16/2026
7 min read

Latitude.sh Review 2026: Bare-Metal GPU Cloud for Serious AI Teams

Overview

Latitude.sh is a bare-metal cloud provider that has expanded into the AI/GPU market with a focused offering of high-end servers. Unlike hyperscalers or shared GPU marketplaces, Latitude.sh gives you a **dedicated physical machine** — no hypervisor, no noisy neighbours, no virtualisation overhead.

Founded in 2018 and headquartered in San Francisco, the company operates data centres across North America, South America, Europe, and Asia-Pacific. Its GPU catalogue is intentionally small but high-quality.

Available GPUs and Pricing

| GPU | VRAM | Price/hr |

|-----|------|----------|

| NVIDIA H100 80GB | 80 GB HBM2e | $3.37 |

| NVIDIA RTX PRO 6000 | 96 GB GDDR7 | $3.41 |

Pricing is simple and transparent — no hidden egress fees or marketplace bidding. You pay a flat hourly rate for a dedicated server.

Pros

**1. True Bare-Metal Performance**

Bare metal means your CUDA kernels run directly on the hardware. No hypervisor tax, no CPU contention from other VMs. In bandwidth-bound workloads (large-batch training, NVLink-heavy multi-GPU jobs) this can translate to 5–15% better throughput versus equivalent virtual instances.

**2. Enterprise SLA**

Latitude.sh offers a 99.9% uptime SLA with credits if they miss it. For production inference or time-sensitive training runs, this matters far more than slightly cheaper spot instances that can be reclaimed mid-run.

**3. Global Footprint**

With regions in the US, Brazil, Netherlands, Singapore, and more, teams can place GPU capacity close to users or comply with data-residency rules without leaving the platform.

**4. Predictable Billing**

Flat per-hour pricing eliminates surprises. Engineers can budget accurately without worrying about spot market spikes.

Cons

**Higher Upfront Cost**

At $3.37/hr for an H100, Latitude.sh is pricier than RunPod Community Cloud (~$2.49–2.89/hr) or Vast.ai spot pricing. For cost-sensitive experimentation, the premium is hard to justify.

**Limited GPU Catalogue**

Only two GPU types at the time of writing. Teams needing A100s, L40S, or consumer GPUs for cheaper workloads will need to look elsewhere.

**Longer Provisioning**

Bare-metal servers typically take 3–10 minutes to provision, compared to 30–60 seconds for virtual instances on RunPod.

Latitude.sh vs RunPod

| Factor | Latitude.sh | RunPod |

|--------|-------------|--------|

| H100 price | $3.37/hr | ~$2.49–2.89/hr |

| Isolation | Bare metal | Virtualised |

| SLA | 99.9% | Best-effort |

| GPU variety | 2 types | 20+ types |

| Ideal for | Enterprise, prod | Experiments, dev |

Ideal Users

Latitude.sh is the right choice for:

  • Enterprise ML teams: running production training jobs where reproducibility and performance consistency matter
  • Regulated industries: (fintech, healthcare) needing guaranteed hardware isolation
  • Teams with GDPR/data-residency requirements: needing EU data centres with dedicated hardware
  • High-throughput inference services: where every percentage point of GPU utilisation translates to revenue
  • Verdict: 7.5/10

    Latitude.sh earns its premium for enterprise teams that need bare-metal reliability, a solid SLA, and global reach. For early-stage startups or researchers doing exploratory work, the cost gap versus RunPod or Vast.ai is hard to overlook. But if you are running production AI workloads where downtime or noisy-neighbour effects cost you real money, Latitude.sh is one of the most trustworthy options in the market today.

    Compare Latitude.sh prices with other providers →

    LF

    Lucas Ferreira

    Senior AI Engineer

    Ex-NVIDIA, spent 3 years benchmarking data center GPUs. Now helps teams pick the right hardware for their ML workloads. Ran inference benchmarks on every GPU generation since Volta.

    GPU BenchmarksInference OptimizationCUDAHardware

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