A Hong Kong-based eBay seller is offering pre-modded RTX 2080 Ti graphics cards with 22GB of VRAM (doubled from the original 11GB) for $499. The upgrade doubles memory capacity, making older Turing-generation GPUs viable for modern LLM inference and diffusion tasks. The listing shows 38+ confirmed buyers with positive feedback; the seller has 99.6% lifetime eBay feedback and supplies GPUs from various OEMs (Gigabyte, MSI, ASUS, Leadtek) depending on stock.
The modding service represents a secondary market response to AI inference bottlenecks. An RTX 2080 Ti's 616 GB/s memory bandwidth and Tensor Cores (present since NVIDIA's 2018 Turing launch) remain useful for local LLM quantization workloads, though limited reduced-precision support limits diffusion performance. For context: Nvidia's Titan RTX (24GB) trades for ~$800 on eBay, the RTX 3090 (24GB, faster GDDR6X) commands ~$1200, and Quadro RTX 6000 (24GB) sells for ~$900.
The persistence of 6–8 year-old GPU pricing reflects scarce post-training inference VRAM at competitive costs. Local AI builders lacking access to newer H100s or L40s repurpose older architectures to avoid public API costs. CUDA ecosystem dominance means Nvidia GPUs command price floors other vendors cannot undercut, even for aging hardware.
For practitioners: the 22GB mod at $500 signals sustained demand for mid-tier inference acceleration outside cloud. VRAM arbitrage remains a viable market (memory bandwidth, not raw compute, is the bottleneck for LLM decode). Teams operating cost-sensitive deployments may find 2080 Ti refreshes cheaper than renting cloud capacity, though thermal and power constraints apply. Watch for similar mods on RTX 3090 and 4080 stock as supply tightens.