--- title: "RTX 6000 Ada rental in Uzbekistan: early access | UZ Dynamics" description: "NVIDIA RTX 6000 Ada: early access by request; availability, form factor pending. 48 GB GDDR6 · 0.96 TB/s · PCIe 4. LLMs up to 32B in FP8 on one GPU (estimate)." url: "https://uzdynamics.ai/en/gpus/rtx-6000-ada" lang: "en" image: "https://uzdynamics.ai/en/gpus/rtx-6000-ada/opengraph-image/card?f08c4f789845417d" alternates: ru: "https://uzdynamics.ai/ru/gpus/rtx-6000-ada" uz: "https://uzdynamics.ai/uz/gpus/rtx-6000-ada" en: "https://uzdynamics.ai/en/gpus/rtx-6000-ada" --- > For an index of this site's pages, see [llms.txt](https://uzdynamics.ai/llms.txt). A markdown copy of each page is at its address with `.md` appended. # NVIDIA RTX 6000 Ada Generation rental: early access Ada Lovelace · Workstation (being confirmed) We’re collecting early-access requests. We’re placing our capacity in Uzbekistan. We don’t publish prices yet. We’ll confirm availability in our reply. RTX 6000 Ada [Request RTX 6000 Ada](https://uzdynamics.ai/en/request?source=gpu-page%3Artx-6000-ada&gpu=rtx-6000-ada) We’ll reply with terms for your workload. Nothing to pay before the contract. - **Memory per GPU:** 48 GB GDDR6 - **Memory bandwidth:** 0.96 TB/s - **GPU interconnect:** PCIe 4, no NVLink ## NVIDIA RTX 6000 Ada Generation specifications - **Architecture:** Ada Lovelace - **Announced:** 2022 - **Memory:** 48 GB - **Memory type:** GDDR6 - **Memory bandwidth:** 0.96 TB/s - **FP32:** 91.1 TFLOPS - **FP16/BF16, dense:** 364 TFLOPS - **FP8, dense:** 728.5 TFLOPS - **FP4, dense:** none - **FP64:** not in NVIDIA’s card specs NVIDIA’s whitepaper gives FP64 on the AD102 chip as 1/64 of FP32. - **RT cores:** yes - **NVENC/NVDEC:** NVENC 3, NVDEC 3 - **MIG:** none - **GPU interconnect:** PCIe 4, no NVLink - **Power (TDP/TGP):** 300 W - **Form factor:** Workstation (being confirmed) Memory is specified per GPU. Multiple GPUs have separate memory: using a larger model across them requires compatible software and model partitioning. NVLink does not make them one GPU. The RTX 6000 Ada form factor is still being confirmed. Specs from NVIDIA’s official materials, checked 26 September 2026. ## The RTX 6000 Ada by workload - Inference: LLMs up to 32B in FP8 on one GPU - Fine-tuning: QLoRA up to 32B, LoRA up to 14B on one GPU - Training from scratch: models up to 1B on one GPU - Rendering: scenes up to 32 GB - FP64 computing: not suited to this GPU An estimate from open formulas, not a benchmark or an invoice. ## Servers with the NVIDIA RTX 6000 Ada Generation Server configuration (CPU, RAM, disk, network) is being confirmed. Sizing assumption: up to 8 GPUs per server. We’ll confirm the actual configuration in our reply. [More than 8 GPUs? Discuss a cluster](https://uzdynamics.ai/en/enterprise?source=gpu-page-cluster%3Artx-6000-ada&gpu=rtx-6000-ada&count=more) ## Sources - [NVIDIA RTX 6000 Ada Generation Datasheet](https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/rtx-6000/proviz-print-rtx6000-datasheet-web-2504660.pdf) - [NVIDIA RTX 6000 Ada Generation](https://www.nvidia.com/en-us/products/workstations/rtx-6000/) - [NVIDIA RTX PRO Blackwell GPU Architecture (v1.1), Table 4](https://www.nvidia.com/content/dam/en-zz/Solutions/design-visualization/quadro-product-literature/pdf/NVIDIA-RTX-Blackwell-PRO-GPU-Architecture-v1_1.pdf) - [NVIDIA Ada GPU Architecture (v2.02)](https://images.nvidia.com/aem-dam/Solutions/geforce/ada/nvidia-ada-gpu-architecture.pdf) - [NVIDIA Video Encode and Decode Support Matrix](https://developer.nvidia.com/video-encode-decode-support-matrix) - [NVIDIA Newsroom, September 20, 2022](https://nvidianews.nvidia.com/news/nvidias-new-ada-lovelace-rtx-gpu-arrives-for-designers-and-creators) ## Similar GPUs - [NVIDIA RTX A6000](https://uzdynamics.ai/en/gpus/rtx-a6000) 48 GB GDDR6 · 0.77 TB/s · NVLink bridge RTX 6000 Ada leads on 3 of 4 metrics. RTX 6000 Ada has more FP32 (91.1 vs 38.7 TFLOPS) and FP16/BF16 (364 vs 154.8 TFLOPS). Equal: memory size. - [NVIDIA L40S](https://uzdynamics.ai/en/gpus/l40s) 48 GB GDDR6 · 0.86 TB/s · PCIe 4 RTX 6000 Ada leads on 1 of 5 metrics. RTX 6000 Ada has more memory bandwidth (0.96 vs 0.86 TB/s). Equal: memory size. Nearly equal (under 1% apart): FP32, FP16/BF16, FP8. ## All GPUs in the catalogue - [B300](https://uzdynamics.ai/en/gpus/b300) - [B200](https://uzdynamics.ai/en/gpus/b200) - [H200](https://uzdynamics.ai/en/gpus/h200) - [H100](https://uzdynamics.ai/en/gpus/h100) - [A100](https://uzdynamics.ai/en/gpus/a100) - [RTX PRO 6000](https://uzdynamics.ai/en/gpus/rtx-pro-6000) - [L40S](https://uzdynamics.ai/en/gpus/l40s) - [L4](https://uzdynamics.ai/en/gpus/l4) - [RTX A6000](https://uzdynamics.ai/en/gpus/rtx-a6000) - [RTX A5000](https://uzdynamics.ai/en/gpus/rtx-a5000) [Request RTX 6000 Ada](https://uzdynamics.ai/en/request?source=gpu-page-end%3Artx-6000-ada&gpu=rtx-6000-ada) We’ll reply with terms for your workload. Nothing to pay before the contract. ```json {"@context":"https://schema.org","@type":"BreadcrumbList","itemListElement":[{"@type":"ListItem","position":1,"name":"UZ Dynamics","item":"https://uzdynamics.ai/en"},{"@type":"ListItem","position":2,"name":"GPU catalogue","item":"https://uzdynamics.ai/en/gpus"},{"@type":"ListItem","position":3,"name":"RTX 6000 Ada","item":"https://uzdynamics.ai/en/gpus/rtx-6000-ada"}]} ```