NVIDIA A10 PCIe
NVIDIA graphics card specifications and benchmark scores
Ray Tracing
Tensor CoresAt a Glance
NVIDIANVIDIA A10 PCIe Specifications
A10 PCIe GPU Core
Shader units and compute resources
The NVIDIA A10 PCIe 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.
A10 PCIe Clock Speeds
GPU and memory frequencies
Clock speeds directly impact the A10 PCIe'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 A10 PCIe by NVIDIA dynamically adjusts frequencies based on workload, temperature, and power limits to maximize performance while maintaining stability.
NVIDIA's A10 PCIe Memory
VRAM capacity and bandwidth
VRAM (Video RAM) is dedicated memory for storing textures, frame buffers, and shader data. The A10 PCIe'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.
A10 PCIe by NVIDIA Cache
On-chip cache hierarchy
On-chip cache provides ultra-fast data access for the A10 PCIe, 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.
A10 PCIe Theoretical Performance
Compute and fill rates
Theoretical performance metrics provide a baseline for comparing the NVIDIA A10 PCIe 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.
A10 PCIe Ray Tracing & AI
Hardware acceleration features
The NVIDIA A10 PCIe 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 A10 PCIe capable of delivering both stunning graphics and smooth frame rates in modern titles.
Ampere Architecture & Process
Manufacturing and design details
The NVIDIA A10 PCIe is built on NVIDIA's Ampere 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 A10 PCIe will perform in GPU benchmarks compared to previous generations.
NVIDIA's A10 PCIe Power & Thermal
TDP and power requirements
Power specifications for the NVIDIA A10 PCIe 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 A10 PCIe to maintain boost clocks without throttling.
A10 PCIe by NVIDIA Physical & Connectivity
Dimensions and outputs
Physical dimensions of the NVIDIA A10 PCIe 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 A10 PCIe. 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.
A10 PCIe Product Information
Release and pricing details
The NVIDIA A10 PCIe 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 A10 PCIe by NVIDIA represents good value at current market prices. Predecessor and successor information aids in tracking generational improvements and planning future upgrades.
A10 PCIe Benchmark Scores
No benchmark data available for this GPU.
About NVIDIA A10 PCIe
Memory Subsystem
The NVIDIA A10 PCIe is equipped with 24 GB of GDDR6 memory, arranged across a 384-bit bus interface. This configuration yields a memory bandwidth of 600.2 GB/s, a figure that places the card in a comfortable position for high-resolution workloads, though it does not reach the extreme bandwidth tiers occupied by some HBM-equipped accelerators. The effective memory speed is cited at 12.5 Gbps, which is a standard operating point for GDDR6 of this generation.
For high-resolution rendering and large dataset processing, the 24 GB capacity is a more defining characteristic than raw bandwidth. At 4K and beyond, frame buffers and intermediate data structures expand rapidly; 24 GB provides a substantial cushion for scenes that would otherwise spill into system memory. The 600.2 GB/s bandwidth, while not record-breaking, is sufficient to feed the GPU's 31.24 TFLOPS FP32 compute throughput without creating an obvious bottleneck in typical server-side rendering or inference tasks. The 384-bit bus width is a direct contributor to this balance, allowing a wider path for data movement than narrower 256-bit designs common in lower-tier products.
The memory subsystem's design is oriented toward sustained throughput rather than burst performance. In synthetic bandwidth tests, the A10 PCIe's 600.2 GB/s would position it alongside other mid-to-high-end Ampere derivatives, but the benchmark percentile data (50th percentile across all GPUs) suggests that this memory configuration is neither a standout advantage nor a glaring weakness relative to the broader GPU landscape. For workloads that are memory-capacity-bound, such as large language model inference or multi-stream video processing, the 24 GB pool will be the primary asset; for bandwidth-bound tasks like real-time ray tracing at extreme resolutions, the 600.2 GB/s may prove adequate but not exceptional.
Ray Tracing and Feature Set
The A10 PCIe is built on the Ampere architecture, which incorporates dedicated ray tracing and tensor processing hardware. Specifically, the GPU contains 72 RT cores and 288 tensor cores. These are not incidental additions; they are fundamental to the card's capability set. The RT cores are designed to accelerate bounding volume hierarchy traversal and ray-triangle intersection tests, which are the compute-heavy components of ray-traced rendering. The 72 RT cores represent a substantial allocation for a server-oriented card, indicating that hardware-accelerated ray tracing was a design consideration rather than an afterthought.
The tensor cores, numbering 288, are equally significant. They enable accelerated matrix math operations, which are critical for AI inference, deep learning training, and increasingly for real-time denoising in ray-traced pipelines. The presence of these cores, combined with the 31.24 TFLOPS FP32 and matching FP16 throughput (31.24 TFLOPS 1:1), suggests that the card is equally comfortable with traditional graphics workloads and compute-heavy neural network tasks.
On the API front, the A10 PCIe supports DirectX 12 Ultimate (feature level 12_2), OpenGL 4.6, and Vulkan 1.4. DirectX 12 Ultimate compliance is notable because it guarantees support for hardware ray tracing, mesh shaders, and variable rate shading, features that are now staples of modern game engines and real-time visualization tools. Vulkan 1.4 support extends similar capabilities to cross-platform and Linux-based environments, which is relevant for server deployments running containerized workloads. OpenGL 4.6 ensures backward compatibility with legacy applications. Notably, the card has no display outputs, confirming its role as a compute or render-farm accelerator rather than a desktop graphics solution.
Benchmark Performance
The benchmark data for the NVIDIA A10 PCIe is sparse: the average benchmark score is listed as 0, and the nearestRivals array is empty. This absence of direct comparative scores means that performance analysis must rely on the architectural specifications and the single percentile data point available. The card sits at the 50th percentile across all GPUs, which is a median position, indicating that, in aggregate performance across all benchmark types, it is neither a top-tier performer nor a budget-oriented laggard.
The compute metrics provide a clearer picture of its capabilities. The FP32 throughput of 31.24 TFLOPS is a strong figure for a 150 W card, suggesting that the A10 PCIe punches above its weight in raw floating-point operations. The texture rate of 488.2 GTexel/s and pixel rate of 162.7 GPixel/s are consistent with a GPU that has 288 TMUs and 96 ROPs. These figures indicate that the card can sustain high fill rates, which is beneficial for rasterization-heavy tasks, though the lack of direct rival comparisons makes it difficult to contextualize these numbers against specific competitors.
The clock speeds, base 885 MHz and boost 1695 MHz, are modest by desktop gaming standards, but they are deliberately set to maintain a 150 W TDP within a single-slot form factor. The power efficiency implied by 31.24 TFLOPS at 150 W is a key selling point for dense server deployments. However, without benchmark scores or rival deltas, it is impossible to state a definitive percentage advantage or disadvantage. The data indicates that this is a mid-pack performer overall, but one with a specialized profile favoring compute density and memory capacity over raw graphics frame rates.
Who Should Consider It
Given the 24 GB memory capacity, 600.2 GB/s bandwidth, and 31.24 TFLOPS FP32 performance, the NVIDIA A10 PCIe is best suited for server-side workloads where memory capacity and compute throughput are prioritized over display output. The lack of display connectors means that it is not intended for direct-attached monitor use; instead, it is designed for render farms, virtual desktop infrastructure (VDI) backends, or AI inference servers where tasks are dispatched remotely.
For high-resolution rendering, whether for film, architecture, or product visualization, the 24 GB frame buffer is the primary draw. Scenes with heavy geometry, high-resolution textures, and multi-pass effects can easily exceed 8 GB or 16 GB of VRAM; the A10 PCIe's capacity allows such scenes to be processed without out-of-core memory swapping, which would otherwise cause severe performance degradation. The 600.2 GB/s bandwidth is sufficient for these tasks, though users pushing 8K resolutions or massive simulation datasets may find it to be a limiting factor.
For machine learning inference, the 288 tensor cores and 31.24 TFLOPS FP16 throughput (at 1:1 ratio) make this a viable option for batch inference jobs. The 24 GB memory can hold moderate-sized models or large batches, and the 150 W TDP allows for high-density deployment in multi-GPU servers. The single-slot design and 1x 8-pin power connector further enhance its suitability for dense configurations. However, for training large models from scratch, the lack of higher-bandwidth memory (like HBM2e) might constrain performance relative to more specialized AI accelerators.
How It Compares
The nearestRivals data is empty, meaning there are no direct competitor comparisons provided in the fact pack. This absence is unusual but not unprecedented for server-grade products that occupy niche positions. Without explicit rival names, scores, or deltaPct values, a comparative analysis cannot be constructed based on benchmark results.
What can be said is that the A10 PCIe's 50th percentile ranking across all GPUs provides a rough positional anchor. This means that in a mixed workload of gaming, professional, and compute tasks, the A10 PCIe performs better than half of all GPUs and worse than the other half. In the specific context of server accelerators, this percentile likely reflects a trade-off: the card offers more memory and compute efficiency than older Tesla Turing products (its predecessor generation) but lacks the sheer compute throughput of newer Server Ada parts (its successor generation).
The production status is listed as end-of-life, and the release date is April 2021. This suggests that the A10 PCIe is a mature product that has been superseded in the lineup. For organizations seeking a reliable, well-supported accelerator with a proven driver stack, this can be an advantage, the hardware has been in the field for years, and software optimizations have had time to mature. For those seeking the latest features or maximum performance, the successor generation would be the appropriate target. The predecessor, Tesla Turing, represented the prior architecture generation, and the A10 PCIe's Ampere architecture offers significant architectural improvements, including dedicated RT cores and third-generation tensor cores, which were absent or less capable in Turing.
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