Hardware Economics Shift: DDR5 RDIMM Pricing Now Comparable to GPUs for Local Inference

A critical economic inflection point has been reached in local LLM hardware planning. DDR5 RDIMM memory pricing has climbed to the point where the cost-per-gigabyte is now competitive with or exceeds GPU costs, specifically matching RTX 3090 pricing on a per-GB basis. This fundamentally changes the calculus for builders planning multi-GPU or memory-heavy inference systems, as RAM stacking no longer provides clear economic advantages over GPU acquisition.

For practitioners building local deployment infrastructure, this analysis highlights a crucial decision point: RAM-only systems for inference now compete directly with GPU-accelerated approaches on cost. While RDIMM doesn't provide computation acceleration, high-memory setups remain valuable for large model quantization and batch processing workflows. This pricing pressure is likely temporary, but it underscores the importance of regularly benchmarking hardware ROI before committing to expensive infrastructure.

The shift suggests that practitioners should prioritize GPU efficiency and quantization strategies (achieving better performance per VRAM dollar) rather than pursuing raw memory expansion as a scaling strategy.

Source: r/LocalLLaMA · Relevance: 8/10