Local inference build weighs single vs dual GPUs

Hot take: for this use case, the GPU and platform fit matter far more than chasing the biggest possible dual-card spec, and a single high-VRAM card is often the most practical starting point.

• –The post is fundamentally about infrastructure planning, not a product launch, so the main question is capacity planning: VRAM, PCIe lanes, power, cooling, and case spacing.
• –Dual-GPU builds can make sense for throughput or concurrent jobs, but they raise complexity quickly and can waste budget on motherboard, PSU, and chassis constraints.
• –For code assistants and agents, latency and model size often favor fewer, larger GPUs over more smaller ones, especially if the team is still figuring out workloads.
• –A dual-5080 build is the most suspect on value grounds if VRAM is the limiter, while a single-5090 or single-4090 build is likely the cleanest baseline.
• –The post would be stronger if it included target models, expected concurrency, and whether the server will run one large model, multiple smaller models, or mixed workloads.