LocalLLaMA debates single-GPU server for 100-employee AI

One GPU for 100 users is a performance trap that prioritizes VRAM capacity over the throughput reality of enterprise-scale chat. While 96GB VRAM fits the GPT-OSS 120B weights, it leaves little room for the concurrent context windows of 100 active sessions. Multi-GPU configurations are essential to handle parallel requests without unacceptable queueing latency during peak office hours. Furthermore, the power-optimized Max-Q variant of the RTX 6000 Blackwell may limit the raw compute cycles needed for high-frequency token generation. For agentic workflows in a 100-person organization, the system should prioritize aggregate memory bandwidth and parallel processing over a single high-VRAM card.