Explore verified custom enthusiast PC rigs alongside dedicated enterprise AI server systems with calibrated thermals, multi-GPU interconnects, and real-world training benchmarks.
Turnkey single-piece multi-accelerator nodes (8x NVIDIA HGX / AMD OAM) engineered for frontier LLM pre-training, massive MoE scaling, and high-throughput deep learning.

Known for agile delivery and advanced liquid-cooling systems supporting up to 250 kW rack-level thermal dissipation.
Meta Llama 3.1 405B Base: Deploys in liquid-cooled multi-rack pods to pre-train trillion-token corpora without thermal throttling under continuous 700W GPU power load.

Features Dell's broad product ecosystem and the industry-benchmark Dell PowerEdge XE9680 8-way GPU enterprise computing platform.
Mistral Large 2 (123B): Employed by Fortune 500 banks to fine-tune regulatory compliance LLMs using distributed Megatron-LM across internal high-security networks.

Offers Cray supercomputing heritage and ProLiant AI server systems with high-capacity cooling for exascale-class workloads.
DeepSeek-V3 (671B Total / 37B Activated): Scales across hundreds of Cray nodes using HPE Slingshot fabric, maintaining <1.4μs latency during intense all-to-all expert routing.

Provides vertically integrated supply chains and ultra-high-memory configurations like the Lenovo HGX H200 with Neptune cooling.
Meta Llama 3.1 405B: With 1,128 GB HBM3e, the full FP8 weights of Llama 3.1 405B fit entirely into a single node's VRAM without network tensor sharding.

Focuses on strong networking integration paired with dense hardware, backed by Cisco Silicon One and Nexus 9000 switching.
Llama 3.1 70B Base (Multi-Rack Cluster): Leverages Cisco Silicon One telemetry to eliminate micro-burst congestion and PFC (Priority Flow Control) deadlock during NCCL AllReduce collectives.

The undisputed industry standard for accelerated computing and frontier deep learning, serving as the blueprint for DGX SuperPODs.
175B Parameter Transformer (GPT-3 Class): An 8-node DGX SuperPOD cluster (64 GPUs) trains a 175B parameter foundation model across billions of tokens using 3D Megatron parallelism.

Widely used frontier training nodes for heavy enterprise workloads, packing 8x SXM accelerators into an industry-leading 5U form factor.
DiT (Diffusion Transformer, 14B Video Model): Trains continuous high-resolution 1080p latent video generation models requiring massive continuous FP8 tensor contractions.

Memory-rich alternative systems powered by AMD Instinct MI300X accelerators and dual AMD EPYC processors, providing 1.54 TB of high-speed HBM3.
Llama 3.1 70B Base: With 1,536 GB total VRAM, all FP16 model weights, gradients, and AdamW optimizer states fit on a single node without CPU offload or tensor parallelism across the network.
Production-tested consumer configurations with verified 2D/3D component clearances, calibrated power transients, and benchmark curves.
Zero-compromise 4K ray tracing and high-bandwidth workstation compute.
Peak gaming FPS with 3D V-Cache and synchronized neon ARGB chassis.
Maximum price-to-performance ratio with zero pump failure risk.