WoolyAI Launches Private Multi-Agent Inference Server for DGX Spark Clusters

Summary

WoolyAI announced a new private inference server specifically designed for multi-model agentic workflows on NVIDIA DGX Spark clusters. The system enables enterprises to run cost-effective, low-latency inference across multiple models simultaneously, addressing the need for dedicated multi-GPU inference infrastructure without prohibitive costs. In LlamaBench testing on a 2 DGX Spark cluster setup, the system achieved 55-90 tokens per second throughput on decode without speculative decoding, supporting models including DeepSeek V4 Flash, Gemma 4 26B, and NVIDIA Nemotron 3 Nano Omni. The platform includes an intelligent scheduler that can dynamically swap between models at safe boundaries while maintaining a single inference endpoint, reducing model activation latency to as little as 2 seconds.

• Targeted at reducing infrastructure costs for companies needing multi-model inference capabilities for complex enterprise workflows
• WoolyAI plans further optimization improvements with potential for 20% performance gains

Editorial Opinion

This release addresses a real infrastructure gap for enterprises moving toward agentic workflows—the reality that complex business processes need multiple specialized models, not single monolithic deployments. By enabling cost-effective multi-model inference on shared GPU clusters, WoolyAI positions itself as a pragmatic solution for the multi-agent era. However, the claimed performance gains are significant and warrant third-party verification; the benchmarks are impressive if the detailed testing methodology holds up under scrutiny.