Qwen3.5 user weighs GPU swap

The core issue here is probably not raw compute so much as model quality, memory headroom, and how well the serving stack is orchestrated. More VRAM can unlock larger models and smoother multi-GPU inference, but “agency” usually comes from better model selection plus tooling, not just a bigger card.

• –Swapping to more RTX Pro 6000s would most likely buy capacity, stability, and easier large-model loading, not a magical reasoning jump
• –For prototype coding and technical discussion, a smaller top-tier model with good tool use can beat a larger model that is awkwardly quantized or poorly served
• –This is the kind of setup where context management, retrieval, and agent scaffolding matter as much as GPU choice
• –If the user wants more headroom, the better question is which model sizes they want to run comfortably at what context lengths