GPU sourcing through GPUSeeker starts here, with 15 NVIDIA and AMD data center GPUs in one place. We’re a concierge-level, vendor-neutral broker for mid-market companies. Each GPU below links to its own sourcing page, with specs, workloads, and answers to common questions. Pick the GPU that fits what your AI teams are building, training, or running in production.
Start with the workload, then the memory it needs. Training large models, serving inference in production, and fine-tuning each stress GPUs differently. The blurbs below name who each GPU serves and what for. NVIDIA is listed first, then AMD. Neither maker is ranked.
NVIDIA describes Hopper, including its Transformer Engine and NVLink, on its Hopper architecture page.
NVIDIA’s Blackwell architecture overview covers the platform behind these four options.
The NVIDIA Vera Rubin NVL72 page lists the rack’s published specs.
AMD lists the CDNA generation of current Instinct GPUs in its ROCm GPU architecture specs.
AMD places MI430X and MI455X on CDNA 5 in its CDNA architecture overview.
We find hard-to-source GPU paths and route your requirements to a respected Technology Services Distributor (TSD). The TSD’s solutions engineers build a right-sized proposal across neocloud and channel options. The TSD and its providers handle diligence and contracting. GPUSeeker never handles your data, holds capacity, or quotes prices.
Related: reserved capacity, on-demand, neocloud sourcing, TSD channel, and GPU advisory.
Talk to a GPU sourcing advisor. Share your GPU shortlist, workloads, and timeline in a short conversation. We’ll route a warm request to the right TSD path for a right-sized proposal.
