NVIDIA RTX A4500 vs NVIDIA Tesla P100 PCIe 12 GB Comparison

The NVIDIA RTX A4500 and the NVIDIA Tesla P100 PCIe 12 GB represent two distinct eras of NVIDIA’s professional GPU lineup. The A4500 is an Ampere-generation workstation card, while the P100 is a Pascal-generation compute accelerator. The data available for direct comparison is limited to a single benchmark, but that result, combined with architectural and specification differences, provides a clear picture of their respective positions.

Head-to-Head Benchmarks

The only head-to-head benchmark result available is the Geekbench OpenCL test. In this test, the NVIDIA RTX A4500 scores 141,837 points, while the NVIDIA Tesla P100 PCIe 12 GB scores 79,396 points. This represents a decisive victory for the A4500, with a delta of 78.6% — meaning the A4500 is roughly 78.6% faster in this specific workload. This is a massive performance gap that cannot be attributed to minor clock speed differences or memory bandwidth alone.

To contextualize this result, it’s useful to look at the average benchmark scores for each card. The A4500 has an average benchmark score of 91,671, while the P100 sits at 79,396. The discrepancy between the A4500’s average score and its OpenCL score suggests that its performance is particularly strong in compute-oriented tasks like OpenCL, or that the average is pulled down by other less favorable tests. The P100’s average score is identical to its OpenCL score, indicating that this single test is the only data point available for that card in the database.

The A4500’s lead in OpenCL is consistent with its hardware specifications. It features 7,168 shading units and 224 tensor cores, compared to the P100’s 3,584 shading units and no tensor cores. Furthermore, the A4500’s FP32 compute rate is 23.65 TFLOPS, while the P100’s is 9.526 TFLOPS. This 2.5x raw compute advantage is likely the primary driver behind the 78.6% OpenCL performance delta, as OpenCL often scales well with shader count and raw FP32 throughput.

Looking at the nearest rivals for each card provides additional context. The A4500’s closest competitor is the NVIDIA RTX A4500 Mobile, which scores 91,134 on average, just 0.6% lower than the desktop A4500. The AMD Radeon Instinct MI60 is 0.9% higher, and the NVIDIA Quadro GP100 is 4.8% lower. This shows that the A4500 sits in a competitive performance band. The P100’s nearest rival is the NVIDIA Tesla P100 PCIe 16 GB, which scores 79,605 on average, a mere 0.3% higher. Interestingly, the NVIDIA GeForce RTX 5090 is listed as a rival with an average score of 79,842, which is 0.6% higher than the P100. This suggests that despite its age, the P100’s compute-focused design keeps it relevant in certain aggregate metrics.

The Verdict

Based strictly on the available data, the NVIDIA RTX A4500 is the clear winner for anyone prioritizing raw compute performance in the Geekbench OpenCL test. The 78.6% lead is substantial and reflects the A4500’s modern architecture, higher core count, and significantly higher FP32 throughput. For workloads that are heavily parallel and rely on shader compute, such as rendering, simulation, or general-purpose GPU compute, the A4500 is demonstrably the superior choice.

The NVIDIA Tesla P100 PCIe 12 GB, however, is not without its merits. Its average benchmark score of 79,396 places it in the 92nd percentile of all GPUs, compared to the A4500’s 93rd percentile. This indicates that the P100 is still a highly capable card in absolute terms. Its nearest rivals include the RTX 5090, which is only 0.6% higher in average score, suggesting that the P100’s compute capabilities remain relevant even against modern consumer flagships in some aggregate metrics.

The P100’s primary advantage lies in its specific design goals. It is a compute-oriented accelerator with no display outputs, meaning it is intended for headless servers or dedicated compute nodes. Its HBM2 memory, while smaller in capacity (12 GB vs. 20 GB), offers a 3072-bit bus width that provides 549.1 GB/s of bandwidth. This is lower than the A4500’s 640.0 GB/s, but the architecture is different. The P100 also has a higher base clock (1190 MHz vs. 1050 MHz) but a lower boost clock (1329 MHz vs. 1650 MHz).

Who should pick which? A buyer needing a workstation card that can also drive displays and handle a variety of professional workloads should choose the RTX A4500. Its 4x DisplayPort 1.4a outputs and 20 GB of GDDR6 memory make it a versatile tool. A buyer with a purely compute-focused server environment, where display output is irrelevant and power consumption is a secondary concern, might consider the P100 if the price is right, but the benchmark data shows they would be leaving significant performance on the table.

FAQ

Q: Which GPU is faster in the Geekbench OpenCL benchmark?

A: The NVIDIA RTX A4500 is significantly faster, scoring 141,837 compared to the Tesla P100’s 79,396. This equates to a 78.6% performance advantage for the A4500.

Q: What is the average benchmark score for each card?

A: The NVIDIA RTX A4500 has an average benchmark score of 91,671, while the NVIDIA Tesla P100 PCIe 12 GB has an average score of 79,396.

Q: How do the two cards compare in terms of memory bandwidth?

A: The RTX A4500 offers 640.0 GB/s of bandwidth with 20 GB of GDDR6 memory. The Tesla P100 offers 549.1 GB/s of bandwidth with 12 GB of HBM2 memory.

Q: Which card has more shading units?

A: The NVIDIA RTX A4500 has 7,168 shading units, which is double the 3,584 shading units found on the Tesla P100.

Q: Does the Tesla P100 have tensor cores?

A: No, the Tesla P100 has no tensor or ray tracing cores. The RTX A4500 features 224 tensor cores and 56 RT cores.

Q: What is the launch MSRP of the Tesla P100?

A: The launch MSRP of the NVIDIA Tesla P100 PCIe 12 GB was 4,599 USD.

Specification Differences

The two cards differ substantially in their core specifications, reflecting their different generations and design goals.

• Process Node: The RTX A4500 is built on an 8 nm process from Samsung, while the Tesla P100 uses a 16 nm process from TSMC.
• Transistors: The A4500 has 28,300 million transistors on a 628 mm² die. The P100 has 15,300 million transistors on a 610 mm² die.
• Memory: The A4500 features 20 GB of GDDR6 memory on a 320-bit bus. The P100 features 12 GB of HBM2 memory on a 3072-bit bus.
• Memory Clock: The A4500’s memory runs at 2000 MHz (16 Gbps effective), while the P100’s runs at 715 MHz (1430 Mbps effective).
• Compute Units: The A4500 has 7,168 shading units, 224 TMUs, and 96 ROPs. The P100 has 3,584 shading units, 224 TMUs, and 96 ROPs.
• Specialized Cores: The A4500 includes 56 RT cores and 224 tensor cores. The P100 has none.
• Clock Speeds: The A4500 has a base clock of 1050 MHz and a boost clock of 1650 MHz. The P100 has a base clock of 1190 MHz and a boost clock of 1329 MHz.
• Power Draw: The A4500 has a TDP of 200 W, while the P100 has a TDP of 250 W. The suggested PSU is 550 W for the A4500 and 600 W for the P100.
• Bus Interface: The A4500 uses PCIe 4.0 x16, while the P100 uses PCIe 3.0 x16.
• Display Outputs: The A4500 has 4x DisplayPort 1.4a outputs. The P100 has no display outputs.

Architecture Differences

The architectural gap between Ampere and Pascal is vast, and this is reflected in the feature sets and performance characteristics of these two cards.

The RTX A4500 is based on the GA102 chip using the Ampere architecture. This architecture introduces dedicated hardware for ray tracing (56 RT cores) and AI acceleration (224 tensor cores), features entirely absent from the Pascal-based P100. Ampere also supports DirectX 12 Ultimate (12_2), while the P100 is limited to DirectX 12 (12_1). The A4500 supports Vulkan 1.4, whereas the P100 supports Vulkan 1.3. Both support OpenGL 4.6.

In terms of compute, the A4500 offers FP32 and FP16 performance at a 1:1 ratio (23.65 TFLOPS each). The P100 offers FP32 at 9.526 TFLOPS but its FP16 performance is 19.05 TFLOPS at a 2:1 ratio. This means the P100 can process FP16 data at roughly twice the rate of FP32, a design choice for certain HPC workloads. The A4500, however, provides equal throughput for both.

The transistor density also differs significantly. The A4500 packs 45.1 million transistors per mm², while the P100 has 25.1 million per mm². This is a direct result of the more advanced 8 nm process node. The P100’s 16 nm process is older and less efficient. The A4500’s architecture is also more modern, allowing for features like hardware-accelerated ray tracing and variable rate shading, which are part of the DirectX 12 Ultimate feature set.

Where Each One Wins

The data points to a clear split in use cases, driven by the benchmark results and the stark specification differences.

NVIDIA RTX A4500 Wins:

• General Compute: The 78.6% lead in Geekbench OpenCL makes this a dominant win for the A4500. Any workload that utilizes OpenCL for general-purpose computing will see a massive performance boost.
• Modern Workstation Tasks: The presence of RT cores and tensor cores makes the A4500 suitable for AI-assisted workflows, real-time ray tracing in professional visualization, and content creation applications that leverage these features.
• Multi-Display Setups: The 4x DisplayPort 1.4a outputs make it a direct fit for driving multiple high-resolution monitors, a task the P100 cannot perform at all.
• Energy Efficiency: The A4500 delivers significantly higher performance while drawing 50 W less power (200 W vs. 250 W), making it a more efficient solution per unit of performance.
• Higher Memory Capacity: With 20 GB of GDDR6, the A4500 can handle larger datasets than the P100’s 12 GB of HBM2, which is critical for modern deep learning models or large 3D scenes.

NVIDIA Tesla P100 PCIe 12 GB Wins:

• Raw FP16 Throughput: While the A4500 matches FP16 to FP32, the P100’s FP16 rate of 19.05 TFLOPS is higher than its FP32 rate. In workloads specifically tuned for 2:1 FP16 operations, the P100 may offer competitive throughput on a per-watt basis, though the A4500’s overall compute advantage is likely still dominant.
• Legacy Compute Environments: As a Pascal-generation card, it may have better compatibility with older software stacks and drivers that were specifically optimized for this architecture.
• Specific HPC Integrations: The P100’s design as a compute accelerator with no display output suggests it was built for specific high-performance computing clusters or server deployments that are already configured for its PCIe 3.0 interface and power profile.

In summary, the RTX A4500 is the superior product in nearly every measurable way, with a massive performance lead and modern features. The Tesla P100 remains a functional compute card, but its outdated architecture and lack of specialized cores make it a poor choice for any new deployment where the A4500 is available.