NVIDIA Quadro GP100 vs NVIDIA RTX A4500 Comparison

# FAQ

Q: How much faster is the NVIDIA RTX A4500 than the Quadro GP100 in the only shared benchmark?

A: In the Geekbench OpenCL test, the RTX A4500 scores 141,837 versus 87,445 for the Quadro GP100, a 62.2% advantage. This is the only head-to-head benchmark available in the data.

Q: Which GPU has the higher average benchmark score across all tests?

A: The RTX A4500 averages 91,671 across its three benchmark tests (3DMark Steel Nomad DX12, Geekbench OpenCL, and Geekbench Vulkan), while the Quadro GP100 averages 87,445 from its single Geekbench OpenCL result. The gap is 4.8% in favor of the RTX A4500.

Q: Do both cards rank in the same percentile among all GPUs?

A: Yes, both the RTX A4500 and Quadro GP100 sit at the 93rd percentile. Despite the RTX A4500 having a higher average score, both cards are positioned at the same percentile level in the overall GPU landscape.

Q: How does the RTX A4500 compare to its closest rival, the RTX A4500 Mobile?

A: The desktop RTX A4500 scores 91,671 on average, which is only 0.6% higher than the RTX A4500 Mobile's 91,134. This suggests the mobile variant is remarkably close in performance to the desktop card.

Q: What is the Quadro GP100's closest competitor according to the data?

A: The AMD Radeon PRO W7600 is the nearest rival, scoring 87,108 versus the GP100's 87,445 — a margin of just 0.4%. The RTX A4500 sits 4.6% ahead of the GP100 in the rival list.

Q: Does the Quadro GP100 have any benchmark wins over the RTX A4500?

A: No. Across the available head-to-head data, the RTX A4500 wins 1 test and the Quadro GP100 wins 0 tests. The only shared benchmark is Geekbench OpenCL, where the RTX A4500 wins decisively.

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Architecture Differences

The architectural gulf between these two workstation cards spans two GPU generations. The RTX A4500 is built on the Ampere architecture using the GA102 chip, fabricated on Samsung's 8 nm process. The Quadro GP100 uses the older Pascal architecture with the GP100 chip, produced on TSMC's 16 nm node. This process shrink is significant — the RTX A4500 packs 28,300 million transistors into a 628 mm² die, while the GP100 has 15,300 million transistors on a 610 mm² die. The transistor density tells the story: 45.1 million transistors per mm² for the RTX A4500 versus 25.1 million per mm² for the GP100.

The memory subsystems are fundamentally different. The RTX A4500 uses 20 GB of GDDR6 on a 320-bit bus, delivering 640.0 GB/s of bandwidth. The Quadro GP100 uses 16 GB of HBM2 on a massive 4096-bit bus, achieving 732.2 GB/s. Despite the older technology, the GP100's HBM2 provides higher raw bandwidth — a point worth investigating further. However, the memory clock speeds differ dramatically: the RTX A4500 runs at 2000 MHz (16 Gbps effective), while the GP100 runs at 715 MHz (1430 Mbps effective).

Compute resources diverge sharply. The RTX A4500 has 7,168 shading units, 224 TMUs, and 96 ROPs, plus 56 RT cores and 224 tensor cores. The Quadro GP100 has just 3,584 shading units (exactly half), the same 224 TMUs and 96 ROPs, and no RT cores or tensor cores at all. This means the RTX A4500 has dedicated hardware for ray tracing and AI acceleration that the GP100 completely lacks.

Clock behavior also differs. The GP100 has a higher base clock at 1304 MHz versus 1050 MHz on the RTX A4500, but the RTX A4500 boosts higher at 1650 MHz versus 1443 MHz. The FP32 throughput reflects the shader count difference: the RTX A4500 delivers 23.65 TFLOPS, while the GP100 manages only 10.34 TFLOPS. Interestingly, the GP100's FP16 rate of 20.69 TFLOPS (2:1 ratio) exceeds its FP32, whereas the RTX A4500 offers FP16 at 23.65 TFLOPS with a 1:1 ratio.

API support also separates them. The RTX A4500 supports DirectX 12 Ultimate (12_2) and Vulkan 1.4, while the GP100 only reaches DirectX 12 (12_1) and Vulkan 1.3. Both support OpenGL 4.6. The bus interface differs as well: PCIe 4.0 x16 on the RTX A4500 versus PCIe 3.0 x16 on the GP100.

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Head-to-Head Benchmarks

The only direct comparison available is the Geekbench OpenCL test, and the results are lopsided. The RTX A4500 scores 141,837 against the Quadro GP100's 87,445, producing a 62.2% delta. This is not a marginal victory — it represents a substantial generational leap in compute performance.

To contextualize this within the broader field, consider the rival data. The RTX A4500's average score of 91,671 places it 4.8% above the Quadro GP100's 87,445. But the OpenCL gap is far wider at 62.2%, suggesting that OpenCL specifically favors the RTX A4500's architecture. The average score includes the RTX A4500's other tests — the 3DMark Steel Nomad DX12 score of 3,196 and the Geekbench Vulkan score of 129,980 — which likely pull the average down relative to the OpenCL peak.

The Quadro GP100's only benchmark result is the Geekbench OpenCL score of 87,445, which also serves as its average. This means the GP100 has no demonstrated strength in DX12 or Vulkan workloads in this dataset. The RTX A4500's Vulkan score of 129,980 is particularly notable, showing strong cross-API performance.

Looking at the rival lists, the RTX A4500's nearest competitor is the RTX A4500 Mobile at only 0.6% behind, followed by the AMD Radeon Instinct MI60 at 0.9% behind, then the Quadro GP100 at 4.8% behind. The GP100's nearest rival is the Radeon PRO W7600 at just 0.4% ahead, then the NVIDIA CMP 40HX at 2.1% ahead, and the RTX A4500 at 4.6% ahead. This data suggests the GP100 is clustered with mid-range modern workstation cards, while the RTX A4500 sits in a slightly higher performance tier.

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The Verdict

The data paints a clear picture: the NVIDIA RTX A4500 is the superior card by every measurable benchmark metric. It wins the sole head-to-head test by 62.2%, has a 4.8% higher average benchmark score, and offers twice the shading units, dedicated RT and tensor cores, and a newer architecture.

However, the Quadro GP100 is not without merit. Its HBM2 memory provides higher bandwidth at 732.2 GB/s versus 640.0 GB/s, which could matter in bandwidth-bound workloads. Its higher base clock of 1304 MHz versus 1050 MHz suggests it may have better low-load responsiveness. And its position at the same 93rd percentile as the RTX A4500 indicates it remains a relevant performer despite its age.

For users who need maximum compute throughput, modern API support, and ray tracing capabilities, the RTX A4500 is the clear choice based on the data. For those with legacy workloads that favor HBM2 bandwidth or who require the specific characteristics of Pascal-era GPUs, the Quadro GP100 still holds a place. But the 62.2% OpenCL deficit and the lack of any benchmark win for the GP100 make the recommendation straightforward.

The RTX A4500 also offers more memory capacity at 20 GB versus 16 GB, though the GP100's bus width advantage (4096-bit versus 320-bit) partially compensates. The RTX A4500's lower TDP of 200 W versus 235 W is notable, as is its newer PCIe 4.0 interface.

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Specification Differences

The two cards differ in nearly every technical specification except form factor and display count. The RTX A4500 uses the GA102 chip on an 8 nm Samsung process, while the GP100 uses the GP100 chip on a 16 nm TSMC process. Transistor counts are 28,300 million versus 15,300 million, and die sizes are 628 mm² versus 610 mm².

Clock speeds differ: 1050 MHz base / 1650 MHz boost on the RTX A4500 versus 1304 MHz base / 1443 MHz boost on the GP100. Memory configurations diverge completely: 20 GB GDDR6 on 320-bit bus versus 16 GB HBM2 on 4096-bit bus. Bandwidth favors the GP100 at 732.2 GB/s versus 640.0 GB/s.

Shading units are 7,168 versus 3,584, while TMUs match at 224 each and ROPs match at 96 each. The RTX A4500 has 56 RT cores and 224 tensor cores; the GP100 has none of either. Pixel rates are 158.4 GPixel/s versus 138.5 GPixel/s, and texture rates are 369.6 GTexel/s versus 323.2 GTexel/s. FP32 throughput is 23.65 TFLOPS versus 10.34 TFLOPS.

Power draw differs: 200 W TDP for the RTX A4500 versus 235 W for the GP100, though both use a single 8-pin connector and suggest a 550 W PSU. Bus interface is PCIe 4.0 x16 versus PCIe 3.0 x16. Display outputs are 4x DisplayPort 1.4a on both, but the GP100 adds a DVI port. DirectX support is 12 Ultimate (12_2) versus 12 (12_1), and Vulkan is 1.4 versus 1.3. Both are dual-slot designs, with lengths of 267 mm and heights of 112 mm versus 111 mm.

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Where Each One Wins

The RTX A4500 wins in raw compute throughput. Its 23.65 TFLOPS FP32 performance is more than double the GP100's 10.34 TFLOPS. For OpenCL workloads, the 62.2% benchmark advantage is decisive. The RTX A4500 also wins in modern API support, offering DirectX 12 Ultimate and Vulkan 1.4, which enables features like ray tracing and mesh shaders that the GP100 cannot access.

The RTX A4500 wins in memory capacity at 20 GB versus 16 GB, which benefits large dataset handling. It also wins in tensor operations with 224 dedicated tensor cores versus none on the GP100, making AI and machine learning workloads feasible on the newer card. The RTX A4500's 56 RT cores enable hardware-accelerated ray tracing, completely absent on the GP100. Additionally, the RTX A4500 achieves higher pixel and texture rates — 158.4 GPixel/s versus 138.5 GPixel/s, and 369.6 GTexel/s versus 323.2 GTexel/s — suggesting better rasterization throughput.

The Quadro GP100 wins in memory bandwidth at 732.2 GB/s versus 640.0 GB/s. This could favor workloads that are bandwidth-limited rather than compute-limited, such as certain scientific simulations or large matrix operations that fit within the 16 GB capacity. The GP100 also has a higher base clock at 1304 MHz versus 1050 MHz, potentially offering better performance in lightly-threaded or latency-sensitive scenarios before boost clocks kick in.

The GP100's FP16 performance of 20.69 TFLOPS is close to the RTX A4500's 23.65 TFLOPS, though the RTX A4500 achieves this with a 1:1 ratio while the GP100 uses a 2:1 ratio. For workloads specifically tuned to Pascal's HBM2 memory characteristics, the GP100 might retain some niche relevance. However, with zero benchmark wins in the head-to-head data and a 4.8% average score deficit, the GP100's advantages are theoretical rather than demonstrated in this dataset.