GPU-192xCPU-1920GB-8xB200 is a GPU (192 vCPUs, 1920 GiB RAM, 8x B200) server offered by UpCloud with 192 vCPUs, 1920 GiB of memory and 0 GB of storage. The pricing starts at 41.2128 USD per hour.
A massive GPU-accelerated virtual server featuring eight NVIDIA Blackwell B200 GPUs and nearly two terabytes of system memory for AI workloads.
GPU AcceleratedMemory OptimizedCompute Optimized
UpCloud GPU-192xCPU-1920GB-8xB200 is an x86_64 KVM-based virtual server configured with 192 vCPUs under a shared allocation model and 1920.0 GB of system memory. The primary hardware feature is the integration of eight NVIDIA Blackwell B200 GPUs, delivering 1536 GB of total VRAM. This server does not include local storage, meaning all data persistence must be managed externally. While the shared CPU allocation presents a potential tradeoff for sustained CPU-intensive tasks, the massive GPU and system memory capacity makes this instance highly efficient for resource-dense parallel computing. It is designed for workloads such as large-scale AI model training, deep learning, and complex data science computations that require substantial VRAM and system memory.
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Workload Profiles
Precomputed compound score for Cache Intensive workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 50% Redis RPS (pipeline=1, SET), 20% Redis RPS (pipeline=16, SET), 10% PassMark Memory Mark (composite), 10% Memory bandwidth (read, 16 MB ~ L3), 10% PassMark single-thread CPU. Rationale for component selection: In-memory key-value store workload, mixing direct Redis performance metrics with memory speed and latency benchmarks, and single-core CPU performance profiles.
Precomputed compound score for CI/CD Build workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 50% Geekbench Clang compilation (multi-core), 10% Geekbench Clang compilation (single-core), 20% stress-ng div16 best-N cores, 5% PassMark integer math, 5% PassMark compression, 5% Brotli compression (multi-core, level 0), 5% PassMark string sorting. Rationale for component selection: Build performance is mainly driven by multi-core compilation throughput, but also bundles single-core compilation speed and general CPU performance, multi-core compression and text/scripting processing.
Precomputed compound score for Compute Heavy Applications workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 15% stress-ng div16 best-N cores, 10% stress-ng div16 single core, 20% PassMark CPU Mark (composite), 10% Memory bandwidth (read, 64 MB), 15% PassMark floating point, 15% PassMark AVX/SSE/FMA (SIMD), 10% PassMark integer math, 5% PassMark physics simulation. Rationale for component selection: Number-crunching workload augmenting raw CPU performance stressing, general CPU performance benchmarks, memory bandwidth, and pure math computation speed like floating point, integer, SIMD (AVX/SSE/FMA) operations.
Precomputed compound score for Data Analysis workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 70% PassMark CPU Mark (composite), 10% Gzip compression (single-core, level 5), 10% Memory bandwidth (read, 64 MB), 10% PassMark Memory Mark (composite). Rationale for component selection: Data analysis and ETL workloads are memory-bandwidth-bound and CPU-throughput-driven. The profile combines general CPU performance and memory bandwidth/latency as the primary drivers, supplemented by single-core compression speed as a proxy for serialisation-heavy ETL tasks.
Precomputed compound score for LLM Inference workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 15% LLM text generation (SmolLM-135M, 128 tok), 15% LLM prompt processing (SmolLM-135M, 512 tok), 15% LLM text generation (Llama 7B, 128 tok), 15% LLM prompt processing (Llama 7B, 512 tok), 15% LLM text generation (Llama-3.3 70B, 128 tok), 15% LLM prompt processing (Llama-3.3 70B, 512 tok), 5% Memory bandwidth (read, 256 MB), 2% PassMark AVX/SSE/FMA (SIMD), 2% PassMark floating point. Rationale for component selection: VRAM and memory-bandwidth-bound LLM inference workload, using direct LLM speed benchmarks at three model sizes, and supplementing with raw memory bandwidth and SIMD performance benchmarks.
Precomputed compound score for Web Server workloads. A weighted average (geometric mean) of benchmark scores compared to their medians: score = ∏ (x_i / m_i)^(w_i / Σw). The score of 1.0 represents a synthetic baseline server with the median performance of each component benchmark; 0.5 means roughly half the performance; and 2.0 means twice the performance of that reference profile. Component weights: 30% Static web RPS (1 kB, 8 conn/vCPU), 20% Static web RPS (64 kB, 8 conn/vCPU), 20% Static web throughput (256 kB, 8 conn/vCPU), 20% OpenSSL AES-256-CBC (16 kB blocks), 5% Gzip compression (multi-core, level 5), 5% PassMark string sorting. Rationale for component selection: Primary workloads drivers are single-process static HTTP serving speed and throughput, text processing, TLS termination, and asset compression.
GPU-192xCPU-1920GB-8xB200 is a GPU (192 vCPUs, 1920 GiB RAM, 8x B200) server offered by UpCloud with 192 vCPUs, 1920 GiB of memory and 0 GB of storage. The pricing starts at 41.2128 USD per hour.
The GPU-192xCPU-1920GB-8xB200 server is equipped with 192 logical CPU cores on unknown number of physical CPU core(s), 1920 GiB of memory, 0 GB of storage, and 8 NVIDIA Blackwell B200 GPUs. Additional block storage can be attached as needed.
The pricing for GPU-192xCPU-1920GB-8xB200 servers starts at 41.2128 USD per hour, but the actual price depends on the selected region, zone and server allocation method (e.g. on-demand versus spot pricing options): currently, we track the prices in 15 regions and zones every 5 minutes, and the maximum price stands at 41.2128 USD.
The GPU-192xCPU-1920GB-8xB200 server is offered by UpCloud, founded in 2012, headquartered in Uusimaa, Finland. For more information, visit the UpCloud homepage.
The GPU-192xCPU-1920GB-8xB200 server is available in 15 availability zones of the following 15 regions: Sydney #1 (AU), Frankfurt #1 (DE), Copenhagen #1 (DK), Madrid #1 (ES), Helsinki #1 (FI), Helsinki #2 (FI), Amsterdam #1 (NL), Stavanger #1 (NO), Warsaw #1 (PL), Stockholm #1 (SE), Singapore #1 (SG), London #1 (GB), Chicago #1 (US), New York #1 (US), San Jose #1 (US).
