NVIDIA A10G vs NVIDIA RTX A4500 Comparison

NVIDIA A10G and NVIDIA RTX A4500 are both Ampere-generation professional GPUs built on the GA102 chip, but they are engineered for different roles: the A10G targets server inference and rendering workloads, while the RTX A4500 is a workstation card with display outputs. The database shows the A10G holds a decisive lead in the two compute-focused benchmarks recorded, while the RTX A4500 counters with a higher memory bandwidth and a broader API feature set for interactive graphics. This analysis compares their recorded performance, architectural differences, and the implications for workload selection.

Head-to-Head Benchmarks

The head-to-head data records two benchmark tests: Geekbench OpenCL and Geekbench Vulkan. In both, the NVIDIA A10G is the winner, and the deltas are substantial. In Geekbench OpenCL, the A10G scores 158,063 against the RTX A4500’s 141,837, a lead of 11.4%. This test stresses raw compute throughput across the GPU’s shader and tensor cores, and the A10G’s advantage here aligns with its larger silicon configuration. The RTX A4500 is not close in this metric, trailing by over 16,000 points, which places it well behind in any OpenCL-driven compute task.

The Geekbench Vulkan result is similar in magnitude. The A10G records 145,863, while the RTX A4500 posts 129,980, giving the A10G a 12.2% advantage. Vulkan is often used for graphics and compute workloads that benefit from lower overhead and explicit command queues, so this result indicates the A10G’s architecture handles these tasks with greater efficiency. The delta here is slightly larger than the OpenCL gap, suggesting the A10G’s higher shader count and texture rate translate into a more pronounced win when the workload is more graphics-oriented.

Looking at the broader benchmark database, the A10G’s average benchmark score is 151,963, placing it in the 97th percentile of all GPUs. Its nearest rivals include the AMD Radeon Pro W6800X (160,671, which is 5.4% higher) and the NVIDIA A100 PCIe 40 GB (162,504, which is 6.5% higher). This means the A10G, despite winning the head-to-head, sits below those two in absolute average performance. Conversely, it is 1.1% ahead of the NVIDIA Tesla V100 PCIe 32 GB (150,305) and 9.3% ahead of the AMD Instinct MI100 (139,035). The RTX A4500, with an average score of 91,671, sits in the 93rd percentile, and its closest rival is the NVIDIA RTX A4500 Mobile (91,134), which is only 0.6% lower. The RTX A4500 also edges out the AMD Radeon Instinct MI60 (92,466, which is 0.9% higher) and beats the NVIDIA Quadro GP100 (87,445) by 4.8% and the AMD Radeon PRO W7600 (87,108) by 5.2%.

The gap between the two cards in the head-to-head is consistent, but the average score differential is much larger (151,963 vs 91,671, a difference of 60,292 points). This is because the RTX A4500’s average includes its 3DMark Steel Nomad DX12 result (3,196), which is a low score relative to Geekbench, pulling its average down. The A10G has no such low-scoring test in its record, so its average reflects only the two strong Geekbench results. For a direct A/B comparison, the head-to-head records are the most relevant, and they show the A10G winning both tests by roughly 11% to 12%.

The Verdict

Based strictly on the recorded data, the NVIDIA A10G is the stronger compute performer. It wins both head-to-head benchmarks, and its average score is 65.8% higher than the RTX A4500’s average. The A10G’s percentile ranking (97th) also exceeds the RTX A4500’s (93rd), indicating it is positioned higher in the overall GPU hierarchy. For any workload that relies on OpenCL or Vulkan compute, the data clearly favors the A10G. Its 11.4% OpenCL lead and 12.2% Vulkan lead are not marginal; they represent a meaningful performance tier separation.

However, the RTX A4500 has its own strengths that the data cannot ignore. It offers a higher memory bandwidth at 640.0 GB/s versus the A10G’s 600.2 GB/s, a 6.6% advantage. This matters for memory-bound tasks, such as large dataset processing or high-resolution rendering where bandwidth is the limiting factor. The RTX A4500 also has four DisplayPort 1.4a outputs, while the A10G has no display outputs at all. This makes the RTX A4500 the only viable choice for a workstation that needs to drive monitors directly. The A10G is a server card, designed for headless deployment, so it cannot output video.

Who should pick which? A user building a dedicated compute node, a server for inference, or a rendering farm where all GPUs are accessed remotely should choose the NVIDIA A10G. Its higher compute scores and lower power draw (150 W TDP versus 200 W TDP) make it more efficient in a multi-GPU server environment. The data shows it is faster in every recorded compute test, so there is no performance reason to select the RTX A4500 for pure compute. Conversely, a professional working at a desk, running CAD, 3D modeling, or video editing software that requires a direct display connection, should choose the NVIDIA RTX A4500. It delivers slightly higher bandwidth, which helps with texture streaming, and its display outputs are essential for interactive work. The compute deficit is real, but the RTX A4500 is the only card here that can function as a primary workstation GPU.

FAQ

Q: Which GPU has a higher average benchmark score?

A: The NVIDIA A10G has an average benchmark score of 151,963, which is significantly higher than the NVIDIA RTX A4500’s 91,671. The A10G also ranks in the 97th percentile of all GPUs, compared to the RTX A4500’s 93rd percentile.

Q: How much faster is the A10G in Geekbench OpenCL?

A: The A10G scores 158,063 in Geekbench OpenCL, while the RTX A4500 scores 141,837. This gives the A10G an 11.4% lead in that test.

Q: Does the RTX A4500 beat the A10G in any head-to-head benchmark?

A: No. In the two recorded head-to-head benchmarks (Geekbench OpenCL and Geekbench Vulkan), the A10G wins both. The RTX A4500 does not win any head-to-head test.

Q: What is the memory bandwidth difference between the two cards?

A: The RTX A4500 has a memory bandwidth of 640.0 GB/s, while the A10G has 600.2 GB/s. The RTX A4500’s bandwidth is 6.6% higher, despite having a smaller memory bus (320-bit versus 384-bit).

Q: Can the A10G drive a display directly?

A: No. The A10G has no display outputs, whereas the RTX A4500 has 4x DisplayPort 1.4a outputs. This makes the RTX A4500 the only option for direct monitor connection.

Q: How do the two cards compare in terms of power consumption?

A: The A10G has a TDP of 150 W, and the RTX A4500 has a TDP of 200 W. The A10G draws 50 W less, which is advantageous for dense server configurations.

Specification Differences

The two cards share the same GA102 chip, 8 nm process node, Samsung foundry, 28,300 million transistors, and 628 mm² die size, but they diverge in almost every performance-defining specification. The A10G has 9,216 shading units, 288 TMUs, and 96 ROPs, while the RTX A4500 has 7,168 shading units, 224 TMUs, and 96 ROPs. This gives the A10G 28.6% more shading units and 28.6% more TMUs. The RT core count is 72 on the A10G versus 56 on the RTX A4500, a 28.6% advantage for the A10G. Tensor core counts follow the same pattern: 288 on the A10G versus 224 on the RTX A4500.

Clock speeds also differ. The A10G has a base clock of 1320 MHz and a boost clock of 1710 MHz, while the RTX A4500 has a base clock of 1050 MHz and a boost clock of 1650 MHz. The A10G’s base clock is 25.7% higher, and its boost clock is 3.6% higher. This clock advantage, combined with more cores, results in a large difference in fill rates and compute throughput. The A10G’s pixel rate is 164.2 GPixel/s versus 158.4 GPixel/s for the RTX A4500, a 3.7% lead. The texture rate is 492.5 GTexel/s versus 369.6 GTexel/s, a 33.3% lead for the A10G. FP32 and FP16 compute are both 31.52 TFLOPS on the A10G and 23.65 TFLOPS on the RTX A4500, meaning the A10G is 33.3% faster in both.

Memory configurations are notably different. The A10G has 24 GB of GDDR6 on a 384-bit bus, while the RTX A4500 has 20 GB of GDDR6 on a 320-bit bus. Despite the A10G’s larger capacity and wider bus, the RTX A4500 achieves higher bandwidth because its memory runs at a higher effective speed: 16 Gbps versus 12.5 Gbps. This results in 640.0 GB/s for the RTX A4500 versus 600.2 GB/s for the A10G. The RTX A4500 also has a higher memory clock at 2000 MHz versus 1563 MHz for the A10G.

Physical and power specifications differ as well. The A10G is a single-slot card with a 150 W TDP and requires an 8-pin EPS power connector and a 450 W suggested PSU. The RTX A4500 is a dual-slot card with a 200 W TDP, uses a single 8-pin power connector, and requires a 550 W suggested PSU. Both cards are 267 mm long and 112 mm high, but the A10G is thinner. The RTX A4500 has 4x DisplayPort 1.4a outputs, while the A10G has none. The A10G was released on 2021-04-11, and the RTX A4500 was released on 2021-11-22. Both are end-of-life products.

Architecture Differences

Both GPUs are built on the Ampere architecture, using the GA102 chip, but they belong to different product generations within that architecture. The A10G is classified under "Server Ampere (Axx)", while the RTX A4500 is under "Workstation Ampere (Ax000)". This distinction dictates their design priorities: the A10G is optimized for datacenter deployment with no display outputs and a lower TDP for density, while the RTX A4500 is designed for professional workstations with multi-display support and a higher power envelope.

The core architecture is identical in terms of feature support. Both support DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The ray tracing and tensor core generations are the same, but the A10G has more of both: 72 RT cores and 288 tensor cores versus 56 RT cores and 224 tensor cores on the RTX A4500. This means the A10G should handle ray-traced rendering and AI inference tasks with greater parallelism, which is consistent with its higher FP32 and FP16 throughput.

The memory subsystem is a key architectural divergence. The A10G uses a 384-bit memory bus, which is wider than the RTX A4500’s 320-bit bus. However, the RTX A4500 compensates with faster memory, running at 16 Gbps effective versus 12.5 Gbps on the A10G. This results in the RTX A4500 having higher bandwidth (640.0 GB/s versus 600.2 GB/s), which is beneficial for workloads that stream large textures or datasets but do not require extreme compute density. The A10G’s larger 24 GB frame buffer is suited for models or scenes that exceed 20 GB, such as large language model inference or high-resolution texture sets.

The power and cooling architecture also differ. The A10G’s 150 W TDP and single-slot design allow it to fit into dense server chassis, while the RTX A4500’s 200 W TDP and dual-slot design require more airflow and space. The A10G uses an 8-pin EPS connector, which is common in server power supplies, whereas the RTX A4500 uses a standard 8-pin PCIe power connector. The predecessor and successor relationships differ as well: the A10G succeeds Tesla Turing and is followed by Server Ada, while the RTX A4500 succeeds Quadro Turing and is followed by Workstation Ada. This reflects their separate market segments, despite sharing the same underlying chip and architecture. The A10G’s lack of display outputs is a fundamental architectural choice for remote compute, while the RTX A4500’s four DisplayPort outputs are integral to its workstation role.