NVIDIA A100 PCIe 40 GB vs NVIDIA RTX A4500 Mobile Comparison

NVIDIA’s Ampere architecture spans a wide range of products, from data center accelerators to mobile workstation GPUs. The A100 PCIe 40 GB and the RTX A4500 Mobile represent two very different endpoints of that spectrum. The A100 is a dual-slot server card built for massive compute throughput, while the A4500 Mobile is a laptop-class GPU designed for portable workstations. Benchmark data from the database shows a clear performance gap, but the differences go far beyond raw scores. This analysis breaks down the architecture, specifications, and real-world implications of choosing between these two very different Ampere GPUs.

FAQ

Q: Which GPU is faster in the recorded benchmarks?

A: The NVIDIA A100 PCIe 40 GB wins both benchmark tests. In Geekbench OpenCL, it scores 178,627 versus 105,307 for the RTX A4500 Mobile, a 69.6% advantage. In Geekbench Vulkan, the A100 scores 146,380 versus 76,960, a 90.2% lead.

Q: How do these GPUs rank against all other GPUs in the database?

A: The A100 PCIe 40 GB sits in the 97th percentile of all GPUs, while the RTX A4500 Mobile sits in the 93rd percentile. The A100’s average benchmark score is 162,504, compared to 91,134 for the A4500 Mobile.

Q: What are the closest rivals to the A100 in benchmark scores?

A: The A100’s nearest rivals include the AMD Radeon Pro W6800X (average score 160,671, 1.1% behind), the AMD Radeon PRO W7800 (164,894, 1.4% ahead), the NVIDIA RTX A5500 (165,217, 1.6% ahead), and the NVIDIA RTX 4500 Ada Generation (166,094, 2.2% ahead).

Q: What are the closest rivals to the RTX A4500 Mobile?

A: The A4500 Mobile’s nearest rivals include the NVIDIA RTX A4500 desktop card (average score 91,671, 0.6% ahead), the AMD Radeon Instinct MI60 (92,466, 1.4% ahead), the NVIDIA Quadro GP100 (87,445, 4.2% behind), and the AMD Radeon PRO W7600 (87,108, 4.6% behind).

Q: Do both GPUs support the same API features?

A: No. The RTX A4500 Mobile lists DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4 support. The A100 PCIe 40 GB has no listed DirectX, OpenGL, or Vulkan API support in the database, reflecting its compute-focused design with no display outputs.

Q: When were these GPUs released?

A: The A100 PCIe 40 GB was released on June 21, 2020. The RTX A4500 Mobile was released on March 21, 2022. Both are listed as end-of-life products.

Architecture Differences

The two GPUs share the Ampere architecture name, but they are built on fundamentally different chips and processes. The A100 uses the GA100 die, fabricated on a 7 nm process at TSMC. The RTX A4500 Mobile uses the GA104 die, fabricated on an 8 nm process at Samsung. This process difference is significant: the GA100 die measures 826 mm² and packs 54,200 million transistors, while the GA104 die measures 392 mm² and contains 17,400 million transistors. That translates to a transistor density of 65.6 million per mm² for the A100 versus 44.4 million per mm² for the A4500 Mobile.

The A100 is a data center accelerator with no display outputs. It is designed for compute workloads, not graphics rendering to a screen. The RTX A4500 Mobile is a mobile workstation GPU with display outputs that are portable device dependent, meaning the laptop manufacturer determines the actual ports. The A100 also lacks RT cores in the database listing, while the A4500 Mobile includes 46 RT cores. Tensor cores are present on both: 432 on the A100 and 184 on the A4500 Mobile.

Memory architecture is another major divergence. The A100 uses 40 GB of HBM2e on a 5120-bit bus, delivering 1.56 TB/s of bandwidth. The A4500 Mobile uses 16 GB of GDDR6 on a 256-bit bus, delivering 512.0 GB/s. The A100’s memory bandwidth is three times higher, which directly impacts compute-heavy tasks that rely on large data movement.

Clock speeds also differ. The A100 has a base clock of 765 MHz and a boost clock of 1410 MHz. The A4500 Mobile has a higher base clock at 930 MHz and a boost clock of 1500 MHz. Despite the higher clocks on the mobile part, the A100’s massive shader count and memory bandwidth give it the overall performance edge.

Head-to-Head Benchmarks

The database records two Geekbench tests for each GPU: OpenCL and Vulkan. In both, the A100 PCIe 40 GB is the winner.

In Geekbench OpenCL, the A100 scores 178,627 against 105,307 for the A4500 Mobile. That is a delta of 69.6% in favor of the A100. This is a substantial margin, reflecting the A100’s 6912 shading units and 432 tensor cores working through its 1.56 TB/s memory pipeline. The A4500 Mobile’s 5888 shading units and 184 tensor cores are still capable, but the memory bandwidth gap is decisive in OpenCL compute workloads.

In Geekbench Vulkan, the margin is even larger. The A100 scores 146,380, while the A4500 Mobile scores 76,960. That is a 90.2% advantage for the A100. Vulkan performance can be sensitive to driver optimization and memory latency, and the A100’s HBM2e memory likely provides an advantage in this test as well. The A4500 Mobile’s 96 ROPs and 184 TMUs are respectable, but they cannot compensate for the A100’s superior compute resources.

The A100 wins both tests, giving it a 2-0 record in head-to-head comparisons. The A4500 Mobile has zero wins. It is worth remembering the A100’s average benchmark score of 162,504 places it well above the A4500 Mobile’s average of 91,134. This difference is consistent across both individual tests.

Looking at percentile rankings, the A100 sits at the 97th percentile of all GPUs, meaning it outperforms 97% of the database. The A4500 Mobile sits at the 93rd percentile. While both are high performers, the A100 is in a different performance tier entirely.

Specification Differences

The two GPUs differ across nearly every specification field in the database.

• Chip and Process: GA100 on 7 nm (TSMC) versus GA104 on 8 nm (Samsung)
• Transistors: 54,200 million versus 17,400 million
• Die Size: 826 mm² versus 392 mm²
• Transistor Density: 65.6M per mm² versus 44.4M per mm²
• Base Clock: 765 MHz versus 930 MHz
• Boost Clock: 1410 MHz versus 1500 MHz
• Memory Clock: 1215 MHz (2.4 Gbps effective) versus 2000 MHz (16 Gbps effective)
• Memory Size: 40 GB versus 16 GB
• Memory Type: HBM2e versus GDDR6
• Memory Bus Width: 5120 bit versus 256 bit
• Memory Bandwidth: 1.56 TB/s versus 512.0 GB/s
• Shading Units: 6912 versus 5888
• TMUs: 432 versus 184
• ROPs: 160 versus 96
• RT Cores: None listed versus 46
• Tensor Cores: 432 versus 184
• Pixel Rate: 225.6 GPixel/s versus 144.0 GPixel/s
• Texture Rate: 609.1 GTexel/s versus 276.0 GTexel/s
• FP32 Performance: 19.49 TFLOPS versus 17.66 TFLOPS
• FP16 Performance: 77.97 TFLOPS (4:1) versus 17.66 TFLOPS (1:1)
• TDP: 250 W versus 140 W
• Slot Width: Dual-slot versus not specified
• Power Connectors: 8-pin EPS versus None
• Suggested PSU: 600 W versus not specified
• Display Outputs: No outputs versus Portable Device Dependent
• APIs: None listed versus DirectX 12 Ultimate (12_2), OpenGL 4.6, Vulkan 1.4
• Dimensions: 267 mm x 111 mm versus not specified
• Release Date: June 21, 2020 versus March 21, 2022
• Predecessor: Tesla Turing versus Quadro Turing-M
• Successor: Server Ada versus Ada-MW

The FP16 figures are particularly telling. The A100 delivers 77.97 TFLOPS in FP16 with a 4:1 ratio, meaning it can perform four times the FP16 operations compared to FP32. The A4500 Mobile delivers 17.66 TFLOPS in FP16 with a 1:1 ratio, matching its FP32 throughput. This makes the A100 dramatically more capable in mixed-precision workloads like AI inference and training.

Where Each One Wins

The A100 PCIe 40 GB wins in every measured benchmark, but its strengths point to specific use cases. The 40 GB HBM2e memory with 1.56 TB/s bandwidth is designed for large datasets that must reside in GPU memory. The 432 tensor cores and 77.97 TFLOPS FP16 performance make it well-suited for deep learning training, scientific simulation, and large-scale data processing. The 250 W TDP and dual-slot form factor indicate a server environment with adequate cooling and power delivery. The lack of display outputs means it is not intended for any interactive graphics work.

The RTX A4500 Mobile wins in portability and flexibility. Its 140 W TDP allows it to operate in a laptop chassis, and its display outputs make it usable for workstation graphics tasks. The presence of RT cores and full DirectX 12 Ultimate support means it can handle ray-traced rendering and modern graphics workloads. The 16 GB GDDR6 memory is sufficient for many professional applications like CAD, video editing, and 3D modeling. Its 17.66 TFLOPS FP32 performance is respectable for a mobile part, and the 1:1 FP16 ratio still supports AI workloads, though at a much lower throughput than the A100.

The A4500 Mobile also wins on API compatibility. It supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, making it usable across a wide range of software. The A100 lists no API support, reinforcing its role as a compute-only accelerator.

The Verdict

The data is unambiguous: the NVIDIA A100 PCIe 40 GB is the faster GPU by a wide margin. It wins both benchmark tests with deltas of 69.6% and 90.2% over the RTX A4500 Mobile. Its 97th percentile ranking, 40 GB of HBM2e memory, and 432 tensor cores place it in a performance class that the A4500 Mobile cannot reach.

However, the correct choice depends entirely on the use case. The A100 is for server racks, data centers, and compute clusters where power, space, and cooling are available. It has no display outputs and no consumer API support, so it cannot be used for everyday desktop graphics. The RTX A4500 Mobile is for mobile workstations, offering a balance of compute performance, graphics features, and portability. Its 93rd percentile ranking still places it above most GPUs in the database.

For a user running AI training, scientific computing, or massive data analytics, the A100 is the only logical choice. Its memory bandwidth alone is three times higher than the A4500 Mobile, and its FP16 throughput is more than four times higher. For a user doing 3D rendering, CAD, or video editing on a laptop, the A4500 Mobile is the practical option. It supports the full graphics API stack and includes RT cores for ray tracing.

The A100’s wins are decisive in raw performance, but the A4500 Mobile wins in versatility and deployment flexibility. Neither GPU is a bad choice within its intended environment. The A100 is end-of-life and succeeded by Server Ada parts, while the A4500 Mobile is also end-of-life, succeeded by Ada-MW. Both remain viable in the used market, but the data shows they serve entirely different purposes. Pick the A100 if you need maximum compute throughput in a server. Pick the A4500 Mobile if you need a capable workstation GPU that fits in a laptop.