Price: ₹1,19,999 - ₹79,999.00
(as of Oct 19, 2026 10:46:34 UTC – Details)


The VRAM wall is the real wall. When you run language models locally, a model either fits in video memory or it does not run at all – capacity is the first constraint, before speed. The KnytX Ultra Edition raises that ceiling: 22GB of GDDR6 on a full 352-bit bus at 616 GB/s. WHAT WE DO – Each card begins as a tested, pre-owned RTX 2080 Ti reference board. Our technicians replace all eleven 1GB GDDR6 modules with 2GB modules, adjust the memory straps, and flash a custom vBIOS verified in-house, so standard GeForce drivers recognise the full 22GB from first boot. This is a hardware modification performed by KnytX, not a factory configuration – documented, not hidden. WHAT RUNS – 32B-parameter models at Q4_K_M with working context; 14B at Q8; 8B at FP16; GPT-OSS 20B; SDXL and Flux image generation without CPU offloading. Full CUDA 12.x, cuDNN and TensorRT support: Ollama, llama.cpp, LM Studio, ComfyUI and PyTorch work as expected on Windows and Linux. WHAT TO KNOW – Turing supports FP32, FP16 and INT8, but not BF16 or FP8, and the interface is PCIe 3.0 x16. Built for inference and image generation, not large-scale training. The blower exhausts heat out the rear bracket: louder than open-air coolers in a single-card desktop, ideal for compact cases and multi-GPU builds. CONDITION AND WARRANTY – Re-engineered from a pre-owned board; expect light cosmetic scratches on the shroud and bracket. Every card is electrically tested and burn-in verified, and covered by a 1-year KnytX limited warranty on the memory upgrade and card function, serviced in India. SPECIFICATIONS – RTX 2080 Ti (TU102, Turing); 22GB GDDR6, 352-bit, 14 Gbps, 616 GB/s; 4352 CUDA cores; 544 tensor cores; boost up to 1650 MHz; PCIe 3.0 x16; 1x HDMI 2.0b, 3x DisplayPort 1.4, 1x USB-C; two-slot blower, no backplate; 268 x 113 x 40 mm; 250W, 650W PSU recommended. IN THE BOX – KnytX RTX 2080 Ti 22GB Ultra Edition (KNX-RTX2080TI-22GB); warranty card; quick-start guide with digital recovery link.
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.