Breakthrough
AI Performance:
2x Faster Training and Fine Tuning with 83.5x Lower Latency
As AI models grow more complex, many teams face a critical bottleneck they didn’t anticipate: interconnect inefficiency.
Our latest benchmarks reveal that GigaIO’s AI fabric outperforms traditional RoCE Ethernet in every AI workload, empowering organizations to:
Want smarter interconnects for power-constrained AI? See how our AI fabric outperforms RoCE across NVIDIA A100 and AMD MI300X on training and inference benchmarks.
Power Constraints Solved
With GigaIO’s AI fabric, you achieve target performance using fewer GPUs — directly addressing data center power limits. Our tests show RoCE systems require 35-40% more hardware (and energy) to match our AI fabric’s performance.
Inference at Scale
For models like Llama 3.2-90B Vision Instruct, our AI fabric delivers 83.5x faster response times under load. Chatbots, vision systems, and RAG pipelines respond in milliseconds, not seconds.
No More Tradeoffs
Unlike RoCE, GigaIO’s AI fabric eliminates protocol overhead and complex RDMA tuning. As Lamini CTO Greg Diamos notes: “With GigaIO, we spend less time on infrastructure and more time optimizing LLMs.”
The Bottom Line
Our AI fabric isn’t just faster — it’s cheaper to deploy and operate. By removing expensive NICs, switches, and redundant GPUs, teams report 30-40% lower TCO within the first year.
