


Deploy powerful Ampere Altra ARM servers for AI inference, cloud-native applications, big data analytics, edge computing, and high-traffic web hosting with unmatched scalability and efficiency.
Experience the power of high core Ampere® ARM servers, designed for scalability, energy efficiency and outstanding performance across AI inference, machine learning, cloud native applications, big data analytics, high traffic websites and edge computing.
Up to 80 ARM-based cores per server, delivering exceptional speed for demanding cloud workloads.
Perfect for Kubernetes, Docker, microservices, and ultra-low-latency edge computing deployments.
Manage large-scale analytics, high-traffic websites, and content delivery networks effortlessly.
Powered by 80 high-performance ARM64 cores, the Ampere Altra Q80-30 delivers exceptional parallel processing for CPU-intensive workloads. With upto 256 GB DDR4 ECC RAM and upto 8 TB NVMe SSD Gen4 storage, it’s ideal for AI inference, big data analytics, and high-traffic web hosting.
ARM64 and x86 are built differently. Understanding the difference helps you pick the right server and avoid paying for compute you don't need.
| Criteria | Ampere Altra Q80-30 | Intel Xeon (x86) | AMD EPYC (x86) |
|---|---|---|---|
| CPU Cores | 80 independent cores | Up to 32 cores | Up to 48 cores |
| Core Architecture | Fully independent (no LLC sharing) | Shared L3 cache | CCX clusters, shared L3 |
| Power Efficiency | ~3W per core | ~8–12W per core | ~6–9W per core |
| Bandwidth | Unlimited | Unmetered (EU plans) | Unmetered (EU plans) |
| Best For | Containers, AI inference, CI/CD, microservices | Single-thread apps, Windows, legacy software | Virtualisation, databases, HPC |
| OS Support | |||
| Starting Price | €233/mo | from €44/mo | from €57/mo |
80 independent cores mean no core-to-core contention. Run hundreds of pods simultaneously without one noisy service degrading another — ideal for production Kubernetes clusters.
Deploy ONNX Runtime, TensorFlow Lite, and ARM-optimised PyTorch for batch inference. High memory bandwidth handles large embedding models and recommendation engines efficiently.
Parallel compilation and testing across 80 cores cuts build times significantly. Native ARM64 builds for multi-arch Docker images without emulation overhead.
Apache Spark, Kafka, and Flink all run natively on ARM64. High core parallelism processes large datasets faster, while ECC RAM keeps long-running jobs stable.
Nginx, Caddy, and HAProxy run excellently on ARM64. Serve millions of requests per day across 80 cores with unlimited bandwidth and no traffic overages.
Ampere Altra uses ~3W per core versus 8–12W for comparable x86 designs. For teams with sustainability goals or carbon budgets, ARM64 delivers the same compute at a fraction of the energy cost.
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