AI Inference Servers
50% Less Than Cloud
Deploy ML models on dedicated bare metal. 192-768GB RAM, 10Gbps network. No virtualization overhead. No surprise billing.
Cloud vs Bare Metal — Side by Side
Stop overpaying for virtualized infrastructure. Get more hardware for less.
Why Bare Metal for AI Inference
Zero Overhead
No hypervisor tax. Direct hardware access. 30%+ faster than cloud VMs for inference workloads. Every CPU cycle goes to your models.
192-768GB RAM
Load large language models entirely in RAM. No disk swapping. Instant inference. Run 70B+ parameter models without compromise.
Predictable Pricing
Fixed monthly cost. No per-request billing. No bandwidth surprises. Know your infrastructure costs upfront, every month.
AI Inference Use Cases
Bare metal servers handle every stage of the ML inference pipeline.
LLM Inference
Run Llama 3, Mistral, Mixtral, and other large language models on dedicated hardware. High-memory servers let you load 70B+ parameter models entirely in RAM for low-latency inference without quantization compromises.
Vector Databases
Weaviate, Qdrant, Milvus, and Pinecone self-hosted all need high RAM for in-memory vector indexes. Our 192-768GB servers keep your entire index in memory for sub-millisecond similarity search.
Model Serving
Deploy with TensorRT, vLLM, TGI, or Triton Inference Server on bare metal. No container orchestration overhead. Direct hardware access means faster tokenization, batching, and response generation.
Fine-tuning
CPU-based fine-tuning on high-core servers with 48-128 cores. Use QLoRA, LoRA, or full fine-tuning workflows. Persistent storage means your datasets and checkpoints stay on fast NVMe between runs.
Recommended Servers for AI Inference
Every server includes 10Gbps networking, 100TB bandwidth, and deploys in under 15 minutes.
AMD Ryzen 9700X
amd-ryzen-9700xAMD Ryzen 9900X
amd-ryzen-9900x2x E5-2620v4
2x-e5-2620v42x E5-2630v3
2x-e5-2630v32x E5-2650v4
2x-e5-2650v42x E5-2670v3
2x-e5-2670v32x E5-2680v4
2x-e5-2680v4AMD Epyc 4564P
amd-epyc-4564PAMD Ryzen 9950X
amd-ryzen-9950xAMD EPYC 9254P
amd-epyc-9254pAMD EPYC 9255
amd-epyc-9255AMD EPYC 9354P
amd-epyc-9354pAMD EPYC 9355
amd-epyc-93552x Intel GOLD 6230R
2x-intel-gold-6230r2x AMD EPYC 7443
2x-amd-epyc-74432x Intel GOLD 6330
2x-intel-gold-6330AMD EPYC 9554P
amd-epyc-9554pAMD EPYC 9474F
amd-epyc-9474FAMD EPYC 9375F
amd-epyc-9375FAMD Threadripper PRO 7965WX
amd-threadripper-pro-7965wxAMD EPYC 9654
amd-epyc-9654Solana Server Gen5
solana-server-gen5AMD Threadripper PRO 7975WX
amd-threadripper-pro-7975wxAMD EPYC 9754
amd-epyc-9754Frequently Asked Questions
Can I run large language models without a GPU?
Yes. CPU-based inference with frameworks like llama.cpp and vLLM works well on high-memory servers. With 384-768GB RAM, you can load 70B+ parameter models entirely in memory for reasonable throughput without any GPU.
How does pricing compare to AWS or GCP?
For always-on inference workloads, bare metal is typically 50-70% cheaper than equivalent cloud instances. A 192GB RAM server starts from $607/mo vs $1,200+/mo for a comparable AWS instance, with no bandwidth or egress fees.
What ML frameworks are supported?
All of them. You get full root access to install PyTorch, TensorFlow, vLLM, TGI, Triton, ONNX Runtime, or any framework. No vendor lock-in, no managed service limitations.
Is the 10Gbps network really dedicated?
Yes. Every server has a dedicated 10Gbps port — not shared, not burstable. This matters for model serving workloads where consistent low-latency responses are critical. 100TB bandwidth included monthly.
Can I scale up RAM later?
You can upgrade to a higher-spec server at any time. We offer servers from 96GB up to 768GB RAM, so you can start small and move to more powerful hardware as your inference needs grow.
How fast is deployment?
Servers deploy in under 15 minutes. Choose your OS (Ubuntu, Debian, etc.), and you get full SSH access immediately. No waiting for provisioning queues or support tickets.
Deploy Your AI Infrastructure Today
From $449/mo. No setup fees. Crypto payments accepted. Cancel anytime.