Nvidia's DGX Spark is getting a 64GB RAM variant to make running local models more affordable - XDA

Nvidia's 64GB DGX Spark variant isn't a spec bump—it's a pricing-power reset. For two years, local LLM inference has been gated behind 128GB+ VRAM, locking SMEs and indie developers into renting cloud GPUs. That is Nvidia's fattest margin pool. Cutting the threshold to 64GB deliberately punctures the "you must go to the cloud" narrative. Upstream, this shifts memory demand toward high-capacity, mid-bandwidth DDR5/LPDDR5X rather than pure HBM stacking. For Samsung and SK Hynix, that is a more stable volume base than the HBM arms race. Competitively, AMD's MI300X and Intel's Gaudi 3 sit in an awkward "expensive but ecosystem-thin" zone. Nvidia's CUDA-plus-consumer-pricing combo is converting local inference from a research curiosity into a line item on procurement sheets. Apple's M4 Ultra wins on raw unified-memory specs but lacks operator-library depth—hard to displace within 12 months. The 12-24 month tail: local inference share migrates from under 15% toward 35-40%, compressing cloud inference margins. Nvidia's real play isn't selling silicon—it's embedding CUDA across the full stack. Once a developer's model runs locally, switching costs compound exponentially. That is the moat.