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NVIDIA Tesla V100 SXM3 32 GB

NVIDIA graphics card specifications and benchmark scores

32 GB
VRAM
1597
MHz Boost
250W
TDP
4096
Bus Width
๐Ÿค–Tensor Cores

NVIDIA Tesla V100 SXM3 32 GB Specifications

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Tesla V100 SXM3 32 GB GPU Core

Shader units and compute resources

The NVIDIA Tesla V100 SXM3 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 SXM3 32 GB Clock Speeds

GPU and memory frequencies

Clock speeds directly impact the Tesla V100 SXM3 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 SXM3 32 GB by NVIDIA dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.

Base Clock
1380 MHz
Base Clock
1,380 MHz
Boost Clock
1597 MHz
Boost Clock
1,597 MHz
Memory Clock
958 MHz 1916 Mbps effective
GDDR GDDR 6X 6X

NVIDIA's Tesla V100 SXM3 32 GB Memory

VRAM capacity and bandwidth

VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The Tesla V100 SXM3 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
981.0 GB/s
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Tesla V100 SXM3 32 GB by NVIDIA Cache

On-chip cache hierarchy

On-chip cache provides ultra-fast data access for the Tesla V100 SXM3 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 SXM3 32 GB Theoretical Performance

Compute and fill rates

Theoretical performance metrics provide a baseline for comparing the NVIDIA Tesla V100 SXM3 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)
16.35 TFLOPS
FP64 (Double)
8.177 TFLOPS (1:2)
FP16 (Half)
32.71 TFLOPS (2:1)
Pixel Rate
204.4 GPixel/s
Texture Rate
511.0 GTexel/s
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Tesla V100 SXM3 32 GB Ray Tracing & AI

Hardware acceleration features

The NVIDIA Tesla V100 SXM3 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 SXM3 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 SXM3 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 SXM3 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 mmยฒ
Density
25.9M / mmยฒ
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NVIDIA's Tesla V100 SXM3 32 GB Power & Thermal

TDP and power requirements

Power specifications for the NVIDIA Tesla V100 SXM3 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 SXM3 32 GB to maintain boost clocks without throttling.

TDP
250 W
TDP
250W
Power Connectors
None
Suggested PSU
600 W
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Tesla V100 SXM3 32 GB by NVIDIA Physical & Connectivity

Dimensions and outputs

Physical dimensions of the NVIDIA Tesla V100 SXM3 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
SXM Module
Bus Interface
PCIe 3.0 x16
Display Outputs
No outputs
Display Outputs
No outputs
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NVIDIA API Support

Graphics and compute APIs

API support determines which games and applications can fully utilize the NVIDIA Tesla V100 SXM3 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 SXM3 32 GB Product Information

Release and pricing details

The NVIDIA Tesla V100 SXM3 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 SXM3 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 SXM3 32 GB Benchmark Scores

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No benchmark data available for this GPU.

About NVIDIA Tesla V100 SXM3 32 GB

  1. When considering a purchase of the NVIDIA Tesla V100 SXM3 32 GB, cost analysis is a critical step, especially for professionals who require high-performance computing power. This card, built on the Volta architecture with a 12 nm process, offers 32 GB of HBM2 memory, which is essential for applications demanding massive parallel processing, such as deep learning and scientific research. While the initial investment can be significant, with a TDP of 250 W and a base clock of 1380 MHz, the Tesla V100 delivers unparalleled computational efficiency, potentially justifying the cost for long-term projects. Additionally, the PCIe 3.0 x16 interface ensures seamless integration into existing high-performance systems, making it a worthwhile consideration for those looking to future-proof their setup. With its cutting-edge technology, it remains a top choice for deep learning enthusiasts and researchers investing in the future of AI development.
  2. The segment placement of the NVIDIA Tesla V100 SXM3 32 GB targets the high-end market, primarily focusing on data centers, scientific simulations, and AI training environments where raw computational power is essential. In this segment, the cardโ€™s 32 GB HBM2 memory and Volta architecture provide a significant advantage over consumer-grade GPUs, delivering consistent performance for intensive workloads. For professionals evaluating hardware investments, the Tesla V100โ€™s 1597 MHz boost clock and 250 W TDP indicate a robust design capable of handling complex tasks without sacrificing stability. Its PCIe 3.0 x16 interface allows it to slot into enterprise systems seamlessly, reinforcing its role as a cornerstone for advanced computing needs. Ultimately, itโ€™s ideal for users who prioritize performance over cost, making it a strategic choice for scaling operations in data-intensive fields.
  3. Future-proofing is a key consideration when investing in hardware like the NVIDIA Tesla V100 SXM3 32 GB, which leverages the Volta architecture to ensure long-term relevance in high-demand applications. Its 32 GB HBM2 memory is particularly future-proof for emerging AI models and large-scale simulations, as it minimizes bottlenecks in data-heavy environments. With a PCIe 3.0 x16 connection, the Tesla V100 can easily adapt to evolving systems, supporting upgrades and integration with new technologies as they emerge. The cardโ€™s TDP of 250 W reflects a high-performance design that remains efficient despite demanding workloads, offering a balance between power and reliability. When paired with compatible systems, it can drive breakthroughs in machine learning and computational science, making it a wise investment for those aiming to stay ahead of technological advancements.
Pairing suggestions: For the NVIDIA Tesla V100 SXM3 32 GB, pairing it with a server-grade CPU and ample cooling solutions can maximize its potential in high-performance data centers or research labs. Complementary RAM and storage options should also be considered to ensure the system handles large datasets efficiently. Furthermore, integrating compatible frameworks and software, such as CUDA or cuDNN, can unlock the full power of the Tesla V100 for AI and deep learning applications.

The AMD Equivalent of Tesla V100 SXM3 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 โ€ข 2 GB VRAM

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