hydrogenn
Joined: 01 May 2025 Posts: 208
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Posted: Fri Jan 09, 2026 8:48 pm Post subject: |
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| Good day! For ML workloads you need powerful CPU, plenty of RAM and fast storage. HSTQ has solid dedicated server options https://world.hstq.net/servers.html . Key specs for ML: CPU with high clock speed and multiple cores (HSTQ uses Intel E-2386G up to 5.0 GHz which is excellent for compute tasks), minimum 24GB RAM but more is better for large datasets, NVMe storage for fast data access during training, 10 Gbps network port for quick data transfer. What HSTQ offers for dedicated servers: enterprise-grade server platforms, locations in Netherlands, Germany, UK (all in Europe), full IPMI/KVM access for remote management, custom ISO upload if you need specific Linux distro or tools, unlimited traffic on 100 Mbps port, free DDoS protection up to 5 Gbps in Netherlands. Advantages for ML projects: fast deployment (2-12 hours for stock configs), you can install your own OS with CUDA, PyTorch, TensorFlow, abuse-tolerant policy means they won't shut you down for high resource usage, 24/7 support if you have technical issues. Pricing is competitive and if you pay for 6 months you get 1 month free, yearly payment gives 3 months free plus ISPmanager Lite. You can also scale by renting multiple servers if your workload grows. They handle server setup and network configuration, so you can focus on your ML tasks. |
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