--- title: "A100 rental in Uzbekistan: early access | UZ Dynamics" description: "NVIDIA A100: early access by request; availability, form factor pending. 80 GB HBM2e · 2.04 TB/s · NVLink. LLMs up to 32B in BF16 on one GPU (estimate)." url: "https://uzdynamics.ai/en/gpus/a100" lang: "en" image: "https://uzdynamics.ai/en/gpus/a100/opengraph-image/card?f08c4f789845417d" alternates: ru: "https://uzdynamics.ai/ru/gpus/a100" uz: "https://uzdynamics.ai/uz/gpus/a100" en: "https://uzdynamics.ai/en/gpus/a100" --- > 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 A100 rental: early access Ampere · SXM (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. A100 [Request A100](https://uzdynamics.ai/en/request?source=gpu-page%3Aa100&gpu=a100) We’ll reply with terms for your workload. Nothing to pay before the contract. - **Memory per GPU:** 80 GB HBM2e - **Memory bandwidth:** 2.04 TB/s - **GPU interconnect:** NVLink 600 GB/s ## NVIDIA A100 specifications - **Architecture:** Ampere - **Announced:** 2020 - **Memory:** 80 GB - **Memory type:** HBM2e - **Memory bandwidth:** 2.04 TB/s - **FP32:** 19.5 TFLOPS - **FP16/BF16, dense:** 312 TFLOPS - **FP8, dense:** none - **FP4, dense:** none - **FP64:** 9.7 TFLOPS - **FP64 Tensor Core:** 19.5 TFLOPS - **RT cores:** no - **NVENC/NVDEC:** NVENC 0, NVDEC 5 - **MIG:** up to 7 instances - **GPU interconnect:** NVLink 600 GB/s - **Power (TDP/TGP):** 400 W - **Form factor:** SXM (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. Other variants: [A100 80GB PCIe](https://www.nvidia.com/en-us/data-center/a100/), [A100 40GB SXM](https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/a100/pdf/nvidia-a100-datasheet-us-nvidia-1758950-r4-web.pdf) The A100 form factor is still being confirmed; memory, its bandwidth and other specifications depend on it. Specs from NVIDIA’s official materials, checked 26 September 2026. ## The A100 by workload - Inference: LLMs up to 32B in BF16 on one GPU - Fine-tuning: QLoRA up to 70B, LoRA up to 14B on one GPU - Training from scratch: models up to 3B on one GPU - Rendering: no RT cores - FP64 computing: 9.7 TFLOPS, Tensor Core 19.5 TFLOPS An estimate from open formulas, not a benchmark or an invoice. ## Servers with the NVIDIA A100 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%3Aa100&gpu=a100&count=more) ## Sources - [NVIDIA A100 Datasheet](https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/a100/pdf/nvidia-a100-datasheet-nvidia-us-2188504-web.pdf) - [NVIDIA A100](https://www.nvidia.com/en-us/data-center/a100/) - [NVIDIA A100 Tensor Core GPU Architecture](https://www.nvidia.com/content/dam/en-zz/Solutions/Data-Center/nvidia-ampere-architecture-whitepaper.pdf) - [NVIDIA Video Encode and Decode Support Matrix](https://developer.nvidia.com/video-encode-decode-support-matrix) - [NVIDIA Newsroom, May 14, 2020](https://nvidianews.nvidia.com/news/nvidias-new-ampere-data-center-gpu-in-full-production) ## Similar GPUs - [NVIDIA H100](https://uzdynamics.ai/en/gpus/h100) 80 GB HBM3 · 3.35 TB/s · NVLink H100 leads on 5 of 6 metrics. H100 has more FP32 (67 vs 19.5 TFLOPS) and FP64 Tensor Core throughput (67 vs 19.5 TFLOPS). Equal: memory size. - [NVIDIA RTX PRO 6000 Blackwell](https://uzdynamics.ai/en/gpus/rtx-pro-6000) 96 GB GDDR7 · 1.6 TB/s · PCIe 5 RTX PRO 6000 leads on 3 of 4 metrics, A100 on 1. RTX PRO 6000 has more FP32 (120 vs 19.5 TFLOPS) and FP16/BF16 (467.8 vs 312 TFLOPS). But A100 has more memory bandwidth (2.04 vs 1.6 TB/s). FP64: 9.7 TFLOPS on A100; not in NVIDIA’s card specs for RTX PRO 6000 (NVIDIA’s whitepaper gives 1/64 of FP32 for the GB202 chip). The RTX PRO 6000’s FP16, FP8 and FP4 are derived figures. Derived: NVIDIA’s whitepaper per-SM Tensor Core rate × the 2,430 MHz boost clock in the product brief. For the Server Edition, NVIDIA gives FP16/FP8/FP4 only as rounded 1/2/4 PFLOPS peaks, the level of sparse figures; it publishes no dense ones. ## 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) - [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 6000 Ada](https://uzdynamics.ai/en/gpus/rtx-6000-ada) - [RTX A6000](https://uzdynamics.ai/en/gpus/rtx-a6000) - [RTX A5000](https://uzdynamics.ai/en/gpus/rtx-a5000) [Request A100](https://uzdynamics.ai/en/request?source=gpu-page-end%3Aa100&gpu=a100) We’ll reply with terms for your workload. 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