--- title: "B200 rental in Uzbekistan: early access | UZ Dynamics" description: "NVIDIA B200: early access by request; availability, form factor pending. 180 GB HBM3e · 7.7 TB/s · NVLink. LLMs up to 123B in FP8 on one GPU (estimate)." url: "https://uzdynamics.ai/en/gpus/b200" lang: "en" image: "https://uzdynamics.ai/en/gpus/b200/opengraph-image/card?f08c4f789845417d" alternates: ru: "https://uzdynamics.ai/ru/gpus/b200" uz: "https://uzdynamics.ai/uz/gpus/b200" en: "https://uzdynamics.ai/en/gpus/b200" --- > 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 B200 rental: early access Blackwell · 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. B200 [Request B200](https://uzdynamics.ai/en/request?source=gpu-page%3Ab200&gpu=b200) We’ll reply with terms for your workload. Nothing to pay before the contract. - **Memory per GPU:** 180 GB HBM3e - **Memory bandwidth:** 7.7 TB/s - **GPU interconnect:** NVLink 1.8 TB/s B200 diagram: 180 GB HBM3e, chip maximum 192 GB; NVLink 1.8 TB/s Simplified diagram, not to scale ## NVIDIA B200 specifications - **Architecture:** Blackwell - **Announced:** 2024 - **Memory:** 180 GB Usable memory per NVIDIA. The chip’s maximum memory is 192 GB. - **Memory type:** HBM3e - **Memory bandwidth:** 7.7 TB/s Per NVIDIA’s Blackwell Technical Brief (HGX B200); NVIDIA’s DGX B200 materials give up to 8 TB/s. - **FP32:** 75 TFLOPS - **FP16/BF16, dense:** 2,250 TFLOPS - **FP8, dense:** 4,500 TFLOPS - **FP4, dense:** 9,000 TFLOPS - **FP64:** 37 TFLOPS - **FP64 Tensor Core:** 37 TFLOPS - **RT cores:** no - **NVENC/NVDEC:** NVENC 0, NVDEC 7 - **MIG:** up to 7 instances - **GPU interconnect:** NVLink 1.8 TB/s - **Power (TDP/TGP):** up to 1,000 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. The B200 form factor is still being confirmed. Specs from NVIDIA’s official materials, checked 26 September 2026. ## The B200 by workload - Inference: LLMs up to 123B in FP8 on one GPU - Fine-tuning: QLoRA up to 235B, LoRA up to 32B on one GPU - Training from scratch: models up to 8B on one GPU - Rendering: no RT cores - FP64 computing: 37 TFLOPS An estimate from open formulas, not a benchmark or an invoice. ## Servers with the NVIDIA B200 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%3Ab200&gpu=b200&count=more) ## Sources - [NVIDIA Blackwell Technical Brief](https://dam-cdn.nvd.orangelogic.com/AssetLink/gl2l4l4812s5fw0p614s6i8bv6mi3vx5.pdf) - [NVIDIA HGX Platform](https://www.nvidia.com/en-us/data-center/hgx/) - [NVIDIA DGX B200](https://www.nvidia.com/en-us/data-center/dgx-b200/) - [NVIDIA Multi-Instance GPU User Guide](https://docs.nvidia.com/datacenter/tesla/mig-user-guide/latest/supported-gpus.html) - [NVIDIA Video Encode and Decode Support Matrix](https://developer.nvidia.com/video-encode-decode-support-matrix) - [NVIDIA Omniverse Developer Guide: Technical Requirements](https://docs.omniverse.nvidia.com/dev-guide/latest/common/technical-requirements.html) - [NVIDIA Newsroom, March 18, 2024](https://nvidianews.nvidia.com/news/nvidia-blackwell-platform-arrives-to-power-a-new-era-of-computing) ## Similar GPUs - [NVIDIA H200](https://uzdynamics.ai/en/gpus/h200) 141 GB HBM3e · 4.8 TB/s · NVLink B200 leads on 6 of 7 metrics, H200 on 1. B200 has more FP16/BF16 (2,250 vs 989.4 TFLOPS) and FP8 (4,500 vs 1,978.9 TFLOPS). But H200 has more FP64 Tensor Core throughput (67 vs 37 TFLOPS). Without Tensor Cores, B200 has more FP64: 37 vs 34 TFLOPS. - [NVIDIA B300](https://uzdynamics.ai/en/gpus/b300) 270 GB HBM3e · 7.7 TB/s · NVLink B300 leads on 2 of 8 metrics, B200 on 1. B300 has more FP4 (14,000 vs 9,000 TFLOPS) and memory (270 vs 180 GB). But B200 has more FP64 (37 vs 1.2 TFLOPS). Equal: memory bandwidth, FP32, FP16/BF16, FP8, NVLink. - [NVIDIA RTX PRO 6000 Blackwell](https://uzdynamics.ai/en/gpus/rtx-pro-6000) 96 GB GDDR7 · 1.6 TB/s · PCIe 5 B200 leads on 5 of 6 metrics, RTX PRO 6000 on 1. B200 has more memory bandwidth (7.7 vs 1.6 TB/s) and FP16/BF16 (2,250 vs 467.8 TFLOPS). But RTX PRO 6000 has more FP32 (120 vs 75 TFLOPS). FP64: 37 TFLOPS on B200; not in NVIDIA’s card specs for RTX PRO 6000 (NVIDIA’s whitepaper gives 1/64 of FP32 for the GB202 chip). Dense FP16/BF16 and FP8 from the H100 SXM5 column of NVIDIA’s whitepaper: for the H200, NVIDIA lists only with-sparsity figures, the same as the H100 SXM’s. 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) - [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 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 B200](https://uzdynamics.ai/en/request?source=gpu-page-end%3Ab200&gpu=b200) We’ll reply with terms for your workload. 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