NVIDIA Tesla V100 SXM2 16 GB
NVIDIA graphics card specifications and benchmark scores
NVIDIA Tesla V100 SXM2 16 GB Specifications
Tesla V100 SXM2 16 GB GPU Core
Shader units and compute resources
The NVIDIA Tesla V100 SXM2 16 GB GPU core specifications define its raw processing power for graphics and compute workloads. Shading units (also called CUDA cores, stream processors, or execution units depending on manufacturer) handle the parallel calculations required for rendering. TMUs (Texture Mapping Units) process texture data, while ROPs (Render Output Units) handle final pixel output. Higher shader counts generally translate to better GPU benchmark performance, especially in demanding games and 3D applications.
Tesla V100 SXM2 16 GB Clock Speeds
GPU and memory frequencies
Clock speeds directly impact the Tesla V100 SXM2 16 GB's performance in GPU benchmarks and real-world gaming. The base clock represents the minimum guaranteed frequency, while the boost clock indicates peak performance under optimal thermal conditions. Memory clock speed affects texture loading and frame buffer operations. The Tesla V100 SXM2 16 GB by NVIDIA dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.
NVIDIA's Tesla V100 SXM2 16 GB Memory
VRAM capacity and bandwidth
VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Tesla V100 SXM2 16 GB's memory capacity determines how well it handles high-resolution textures and multiple displays. Memory bandwidth, measured in GB/s, affects how quickly data moves between the GPU and VRAM. Higher bandwidth improves performance in memory-intensive scenarios like 4K gaming. The memory bus width and type (GDDR6, GDDR6X, HBM) significantly influence overall GPU benchmark scores.
Tesla V100 SXM2 16 GB by NVIDIA Cache
On-chip cache hierarchy
On-chip cache provides ultra-fast data access for the Tesla V100 SXM2 16 GB, reducing the need to fetch data from slower VRAM. L1 and L2 caches store frequently accessed data close to the compute units. AMD's Infinity Cache (L3) dramatically increases effective bandwidth, improving GPU benchmark performance without requiring wider memory buses. Larger cache sizes help maintain high frame rates in memory-bound scenarios and reduce power consumption by minimizing VRAM accesses.
Tesla V100 SXM2 16 GB Theoretical Performance
Compute and fill rates
Theoretical performance metrics provide a baseline for comparing the NVIDIA Tesla V100 SXM2 16 GB against other graphics cards. FP32 (single-precision) performance, measured in TFLOPS, indicates compute capability for gaming and general GPU workloads. FP64 (double-precision) matters for scientific computing. Pixel and texture fill rates determine how quickly the GPU can render complex scenes. While real-world GPU benchmark results depend on many factors, these specifications help predict relative performance levels.
Tesla V100 SXM2 16 GB Ray Tracing & AI
Hardware acceleration features
The NVIDIA Tesla V100 SXM2 16 GB includes dedicated hardware for ray tracing and AI acceleration. RT cores handle real-time ray tracing calculations for realistic lighting, reflections, and shadows in supported games. Tensor cores (NVIDIA) or XMX cores (Intel) accelerate AI workloads including DLSS, FSR, and XeSS upscaling technologies. These features enable higher visual quality without proportional performance costs, making the Tesla V100 SXM2 16 GB capable of delivering both stunning graphics and smooth frame rates in modern titles.
Volta Architecture & Process
Manufacturing and design details
The NVIDIA Tesla V100 SXM2 16 GB is built on NVIDIA's Volta architecture, which defines how the GPU processes graphics and compute workloads. The manufacturing process node affects power efficiency, thermal characteristics, and maximum clock speeds. Smaller process nodes pack more transistors into the same die area, enabling higher performance per watt. Understanding the architecture helps predict how the Tesla V100 SXM2 16 GB will perform in GPU benchmarks compared to previous generations.
NVIDIA's Tesla V100 SXM2 16 GB Power & Thermal
TDP and power requirements
Power specifications for the NVIDIA Tesla V100 SXM2 16 GB determine PSU requirements and thermal management needs. TDP (Thermal Design Power) indicates the heat output under typical loads, guiding cooler selection. Power connector requirements ensure adequate power delivery for stable operation during demanding GPU benchmarks. The suggested PSU wattage accounts for the entire system, not just the graphics card. Efficient power delivery enables the Tesla V100 SXM2 16 GB to maintain boost clocks without throttling.
Tesla V100 SXM2 16 GB by NVIDIA Physical & Connectivity
Dimensions and outputs
Physical dimensions of the NVIDIA Tesla V100 SXM2 16 GB are critical for case compatibility. Card length, height, and slot width determine whether it fits in your chassis. The PCIe interface version affects bandwidth for communication with the CPU. Display outputs define monitor connectivity options, with modern cards supporting multiple high-resolution displays simultaneously. Verify these specifications against your case and motherboard before purchasing to ensure a proper fit.
NVIDIA API Support
Graphics and compute APIs
API support determines which games and applications can fully utilize the NVIDIA Tesla V100 SXM2 16 GB. DirectX 12 Ultimate enables advanced features like ray tracing and variable rate shading. Vulkan provides cross-platform graphics capabilities with low-level hardware access. OpenGL remains important for professional applications and older games. CUDA (NVIDIA) and OpenCL enable GPU compute for video editing, 3D rendering, and scientific applications. Higher API versions unlock newer graphical features in GPU benchmarks and games.
Tesla V100 SXM2 16 GB Product Information
Release and pricing details
The NVIDIA Tesla V100 SXM2 16 GB is manufactured by NVIDIA as part of their graphics card lineup. Release date and launch pricing provide context for comparing GPU benchmark results with competing products from the same era. Understanding the product lifecycle helps evaluate whether the Tesla V100 SXM2 16 GB by NVIDIA represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.
Tesla V100 SXM2 16 GB Benchmark Scores
No benchmark data available for this GPU.
About NVIDIA Tesla V100 SXM2 16 GB
The NVIDIA Tesla V100 SXM2 16 GB is a compute powerhouse engineered for data centers and AI research, not consumer gaming. Its gaming performance, when tested in traditional titles, is underwhelming due to driver optimizations focused on computational workloads like CUDA and Tensor cores rather than DirectX or Vulkan gaming APIs. You won't find dedicated support for real-time ray tracing or DLSS here, as those features debuted in the later Turing and Ampere architectures. The card's immense single-precision compute power is simply misallocated for rendering game frames efficiently. Enthusiasts probing its capabilities will find it excels at GPU rendering in professional applications but stumbles in delivering consistent high frame rates. While technically capable of running games, the Tesla V100 SXM2 represents a severe misapplication of resources for a purely gaming rig.
Exploring ray tracing and upscaling technologies reveals a clear generational gap for this Tesla accelerator. NVIDIA's proprietary DLSS and AMD's FSR are completely irrelevant here, as the Volta architecture lacks the dedicated RT and Tensor cores necessary for such features. The card's computational brute force cannot compensate for the absence of the hardware-accelerated ray tracing pipeline introduced in later GPUs. Investigators will discover that any attempt at ray-traced workloads would be handled purely through software, resulting in prohibitively slow performance. This solidifies the understanding that the 16GB Tesla V100 is a specialist tool, designed for a pre-ray tracing era of computational science. Its value lies in raw parallel processing, not in the visual fidelity technologies that define modern gaming.
The memory subsystem of the Tesla V100 SXM2 16GB is a fascinating study in high-bandwidth design, leveraging 16GB of HBM2 (High Bandwidth Memory 2) on a 4096-bit interface. This configuration delivers staggering bandwidth crucial for feeding its 5120 CUDA cores in data-intensive tasks like scientific simulation or model training. For gaming scenarios, this immense bandwidth is largely wasted, as games rarely saturate such memory pipelines outside of extreme texture streaming cases. The HBM2 also contributes to a compact board design and relatively high power efficiency for its performance class. However, the fixed 16GB capacity, while substantial, may be limiting for some modern professional workloads compared to newer cards. This memory specification perfectly illustrates the card's identity: built for throughput-heavy compute, not for the asset-caching patterns of game engines.
Thermal performance and deployment scenarios are where the Tesla V100 SXM2 16 GB's design philosophy becomes fully apparent. With a 250W TDP and an SXM2 form factor, it is designed for server chassis with optimized, directed airflow, not the acoustics-conscious environment of a gaming PC. In a typical desktop case, this card would quickly throttle without extreme cooling modifications, making it impractical for most enthusiasts. The best scenarios for this hardware involve clustered compute nodes tackling machine learning, HPC, and GPU-accelerated analytics. For the investigating hardware fan, it serves as a remarkable piece of engineering history, showcasing NVIDIA's shift towards AI-focused silicon. Ultimately, the most compelling use case for the V100 SXM2 remains in the data center rack, not the gaming battlestation.
The AMD Equivalent of Tesla V100 SXM2 16 GB
Looking for a similar graphics card from AMD? The AMD Radeon RX 550 Mobile offers comparable performance and features in the AMD lineup.
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