NVIDIA RTX 2080 Ti 22GB AI GPU | Memory-Upgraded GDDR6 Graphics Card for Local AI & LLM Inference | Runs 32B Models at Q4 | 616 GB /s, 4352 CUDA Cores | Ollama & PyTorch Ready | 1-Year India Warranty

Features

• 22GB GDDR6 ON A 352-BIT BUS: 22GB of video memory at 616 GB/s bandwidth. For local AI, capacity decides which models load at all - a model larger than available VRAM will not run regardless of GPU speed. 22GB accommodates 32B-parameter language models at Q4 quantisation with working context, 14B at Q8, or 8B at full FP16.
• MEMORY-UPGRADED BY KNYTX: Each card starts as a tested, pre-owned RTX 2080 Ti reference board. All eleven 1GB GDDR6 modules are replaced with 2GB modules and a custom vBIOS is flashed and verified in-house. This is a hardware modification performed by KnytX, not a factory configuration. Standard GeForce drivers recognise the full 22GB at first boot - no patching, no setup.
• READY FOR THE CUDA TOOLCHAIN: Full CUDA 12.x, cuDNN and TensorRT support. Works with Ollama, llama.cpp, LM Studio, ComfyUI and PyTorch on Windows and Linux. Runs Qwen 32B, Gemma 27B and Mistral Small 24B at Q4_K_M, GPT-OSS 20B, Llama 3.1 8B at FP16, and SDXL or Flux image generation without CPU offloading.
• KNOW THE ARCHITECTURE: Turing supports FP32, FP16 and INT8 - it does not support BF16 or FP8 - and the interface is PCIe 3.0 x16. 4352 CUDA cores, 544 tensor cores, boost up to 1650 MHz. Built for inference and image generation rather than large-scale training. 250W board power; a 650W or stronger power supply is required.
• RE-ENGINEERED BOARD, CONDITION DISCLOSED: Built from a pre-owned board with light cosmetic scratches on the shroud and bracket; every card is electrically tested and burn-in verified before dispatch. Two-slot blower exhausts heat out the rear bracket - suited to compact cases and multi-GPU builds. 1-year KnytX limited warranty on the memory upgrade and card function, serviced in India.