GPUs optimized for serving production AI models at scale. Whether you're running real-time LLM chat, recommendation engines, or computer vision pipelines, these accelerators deliver the throughput and latency profiles required for production deployment.
Native FP4/FP8 quantization and Transformer Engine deliver sub-100ms response times for real-time chat, code completion, and search.
A single next-gen GPU can serve the inference throughput of an entire previous-generation rack, dramatically reducing cost-per-token.
141GB–288GB HBM capacity allows serving 70B+ parameter models on a single GPU without tensor parallelism overhead.
High memory capacity enables hosting routing models, embedding models, and multiple LLMs simultaneously on a single GPU.
All accelerators eligible for GPU-backed financing through GPU Loans.
Next-gen Rubin architecture with 288GB HBM4, 22 TB/s bandwidth, and 50 PFLOPS FP4.
View Specs →Grace Blackwell Superchip with 384GB HBM3e and 40 PFLOPS FP4.
View Specs →Blackwell Ultra with 288GB HBM3e and 15 PFLOPS FP4 for exascale AI.
View Specs →Next-gen Blackwell architecture with 192GB HBM3e and 20 PFLOPS FP4.
View Specs →Enhanced Hopper with 141GB HBM3e for memory-intensive AI workloads.
View Specs →The industry-standard AI accelerator with 80GB HBM3.
View Specs →AMD's CDNA 4 flagship with 288GB HBM3e, 8 TB/s bandwidth, and 10.1 PFLOPS FP8.
View Specs →Memory-upgraded CDNA 3 with 256GB HBM3e and 6 TB/s bandwidth.
View Specs →AMD's flagship AI accelerator with 192GB HBM3 and 5.3 PFLOPS FP8.
View Specs →Enterprise OEM partners offering server platforms for ai inference workloads.
Get up to 70% LTV on enterprise GPU hardware. Fast approvals, competitive rates, flexible terms.
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