
Brev.dev
Best for Developers wanting one-click GPU environments without managing raw infrastructure.

Best for Sustainable, large-scale LLM training on European bare metal.
NScale is a rapidly growing AI infrastructure provider based in the UK, deeply focused on delivering sustainable, high-performance GPU clusters. Backed by their own green data centers, NScale offers highly competitive pricing on both NVIDIA H100s and AMD Instinct MI300X accelerators. They cater specifically to AI startups and research institutions needing bare-metal performance for intensive LLM training and high-throughput inference without the excessive egress fees and long wait times of traditional hyperscalers.
| GPU Models | H100, MI300X, A100 |
| GPU Types | A100, H100, MI300X |
| Headquarters | London, UK |
| Founded | 2023 |
| Availability | Available Now |
| Website | nscale.com ↗ |
💡 Pricing note: Rates shown are indicative. Final pricing depends on GPU model, reservation type (spot vs. on-demand), contract length, and region. Get an exact quote →
NScale GPU cloud pricing starts from $1.85/hr depending on GPU type, reservation model (on-demand vs. spot vs. reserved), and region. Use the quote form to get exact pricing for your specific workload.
NScale offers H100, MI300X, A100 GPU instances. Availability varies by region and configuration. Contact the provider through ComputeStacker for current availability.
NScale operates data centers in EU West, UK, US. Choosing a region close to your users minimises latency and can help with data residency compliance requirements.
Use the "Get a Quote" button on this page to submit your GPU requirements. ComputeStacker will forward your request to NScale and other matching providers. You'll receive proposals within 24 hours — no commitment required.
NScale offers high-performance GPU infrastructure suitable for large language model training and fine-tuning workloads. For large-scale distributed training, check the Specs tab for NVLink and InfiniBand interconnect availability.

Best for Developers wanting one-click GPU environments without managing raw infrastructure.

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