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NVIDIA Tesla V100 PCIe 32 GB

NVIDIA graphics card specifications and benchmark scores

32 GB
VRAM
1380
MHz Boost
250W
TDP
4096
Bus Width
🤖Tensor Cores

NVIDIA Tesla V100 PCIe 32 GB Specifications

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Tesla V100 PCIe 32 GB GPU Core

Shader units and compute resources

The NVIDIA Tesla V100 PCIe 32 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.

Shading Units
5,120
Shaders
5,120
TMUs
320
ROPs
128
SM Count
80
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Tesla V100 PCIe 32 GB Clock Speeds

GPU and memory frequencies

Clock speeds directly impact the Tesla V100 PCIe 32 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 PCIe 32 GB by NVIDIA dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.

Base Clock
1230 MHz
Base Clock
1,230 MHz
Boost Clock
1380 MHz
Boost Clock
1,380 MHz
Memory Clock
876 MHz 1752 Mbps effective
GDDR GDDR 6X 6X

NVIDIA's Tesla V100 PCIe 32 GB Memory

VRAM capacity and bandwidth

VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Tesla V100 PCIe 32 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.

Memory Size
32 GB
VRAM
32,768 MB
Memory Type
HBM2
VRAM Type
HBM2
Memory Bus
4096 bit
Bus Width
4096-bit
Bandwidth
897.0 GB/s
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Tesla V100 PCIe 32 GB by NVIDIA Cache

On-chip cache hierarchy

On-chip cache provides ultra-fast data access for the Tesla V100 PCIe 32 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.

L1 Cache
128 KB (per SM)
L2 Cache
6 MB
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Tesla V100 PCIe 32 GB Theoretical Performance

Compute and fill rates

Theoretical performance metrics provide a baseline for comparing the NVIDIA Tesla V100 PCIe 32 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.

FP32 (Float)
14.13 TFLOPS
FP64 (Double)
7.066 TFLOPS (1:2)
FP16 (Half)
28.26 TFLOPS (2:1)
Pixel Rate
176.6 GPixel/s
Texture Rate
441.6 GTexel/s

Tesla V100 PCIe 32 GB Ray Tracing & AI

Hardware acceleration features

The NVIDIA Tesla V100 PCIe 32 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 PCIe 32 GB capable of delivering both stunning graphics and smooth frame rates in modern titles.

Tensor Cores
640
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Volta Architecture & Process

Manufacturing and design details

The NVIDIA Tesla V100 PCIe 32 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 PCIe 32 GB will perform in GPU benchmarks compared to previous generations.

Architecture
Volta
GPU Name
GV100
Process Node
12 nm
Foundry
TSMC
Transistors
21,100 million
Die Size
815 mm²
Density
25.9M / mm²
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NVIDIA's Tesla V100 PCIe 32 GB Power & Thermal

TDP and power requirements

Power specifications for the NVIDIA Tesla V100 PCIe 32 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 PCIe 32 GB to maintain boost clocks without throttling.

TDP
250 W
TDP
250W
Power Connectors
2x 8-pin
Suggested PSU
600 W
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Tesla V100 PCIe 32 GB by NVIDIA Physical & Connectivity

Dimensions and outputs

Physical dimensions of the NVIDIA Tesla V100 PCIe 32 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.

Slot Width
Dual-slot
Bus Interface
PCIe 3.0 x16
Display Outputs
No outputs
Display Outputs
No outputs
🎮

NVIDIA API Support

Graphics and compute APIs

API support determines which games and applications can fully utilize the NVIDIA Tesla V100 PCIe 32 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.

DirectX
12 (12_1)
DirectX
12 (12_1)
OpenGL
4.6
OpenGL
4.6
Vulkan
1.4
Vulkan
1.4
OpenCL
3.0
CUDA
7.0
Shader Model
6.8
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Tesla V100 PCIe 32 GB Product Information

Release and pricing details

The NVIDIA Tesla V100 PCIe 32 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 PCIe 32 GB by NVIDIA represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.

Manufacturer
NVIDIA
Release Date
Mar 2018
Production
End-of-life
Predecessor
Tesla Pascal
Successor
Tesla Turing

Tesla V100 PCIe 32 GB Benchmark Scores

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No benchmark data available for this GPU.

About NVIDIA Tesla V100 PCIe 32 GB

The NVIDIA Tesla V100 PCIe 32 GB is a computational powerhouse built not for gaming, but for accelerating the most demanding professional and scientific workloads. Its Volta architecture, fabricated on a 12nm process, introduced groundbreaking Tensor Cores designed specifically for AI and deep learning, enabling unprecedented performance in training and inference. With a substantial 32 GB of cutting-edge HBM2 memory, this card offers immense bandwidth to feed its 5120 CUDA cores, which operate at boost clocks up to 1380 MHz. The Tesla V100 PCIe is engineered for data centers and research institutions, where its 250W TDP is managed within server-grade cooling solutions. Its raw computational throughput makes it a legend in high-performance computing (HPC), consistently delivering results where other GPUs falter. Benchmarks in AI research consistently placed this accelerator at the top of its class upon release, setting a new standard for parallel processing.

When evaluating this accelerator's capabilities, its memory subsystem is a defining feature. The 32 GB HBM2 stack provides a massive 900 GB/s of bandwidth, which is critical for processing enormous datasets in fields like computational fluid dynamics or genomic sequencing without bottlenecking. While it lacks dedicated ray tracing hardware, its modern rendering features for professional visualization, powered by its CUDA cores and vast VRAM, excel in GPU-accelerated rendering and simulation. Thermally, the PCIe version of the Tesla V100 is designed for optimal passive airflow in server chassis, relying on system fans for cooling, which is a key consideration for deployment. For optimal use cases, consider the following:

  1. Large-scale AI and Deep Learning model training.
  2. Scientific simulations and high-performance computing (HPC) clusters.
  3. GPU-accelerated data analytics and big data processing.
  4. Professional visualization and virtualized workstation environments.
This card's architecture is squarely focused on double-precision performance and tensor operations, not frame rates.

In terms of real-world application, the NVIDIA V100 32GB remains a relevant force in infrastructure where its specific strengths are leveraged. Its gaming performance is not a metric, as it lacks consumer-grade display outputs and driver optimizations for titles; its performance is measured in petaflops and training epochs. The card's longevity is a testament to its foundational Volta architecture, which continues to drive complex research projects. Deploying this Tesla GPU today means investing in proven stability and software maturity for enterprise CUDA applications. For teams running established CUDA-based HPC codes or needing massive VRAM for model parallelism, this processor delivers exceptional computational density per slot. Ultimately, the Tesla V100's benchmark is its impact on accelerating discovery and innovation across countless technical fields.

The AMD Equivalent of Tesla V100 PCIe 32 GB

Looking for a similar graphics card from AMD? The AMD Radeon RX 550X 640SP offers comparable performance and features in the AMD lineup.

AMD Radeon RX 550X 640SP

AMD • 2 GB VRAM

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