RTX 5090 local LLM limits surface

This is less a hardware flex than a reminder that local AI builds are constrained by memory, not spec-sheet glamour.

• –RTX 5090’s 32GB GDDR7 makes it a strong single-GPU box for Qwen Coder-class 30B models, autocomplete, and local dev workflows
• –70B models can run quantized, but “runs” does not mean fast, high-context, or pleasant for serious multi-file coding
• –The community push toward renting first is sound: a few cloud GPU sessions can prevent a $7K build optimized around stale model assumptions
• –64GB system RAM is usable, but 128GB gives more room for containers, offload, indexing, and development workloads alongside inference
• –Premium Gen5 SSD speed is less important than VRAM capacity, cooling, PSU headroom, and motherboard spacing for future multi-GPU options