NVIDIA RTX 5000 Ada Generation vs NVIDIA Tesla P100 PCIe 12 GB Comparison

Head-to-Head Benchmarks

The database contains one direct head-to-head benchmark result between these two cards, and it is a decisive blowout. In the Geekbench OpenCL test, the NVIDIA RTX 5000 Ada Generation scores 175,286 points, while the NVIDIA Tesla P100 PCIe 12 GB scores 79,396 points. That works out to a 120.8% advantage for the RTX 5000 Ada, meaning it more than doubles the Tesla P100's compute output in this workload. This is not a marginal generational step; it is a complete overhaul of performance class.

Looking at the broader benchmark averages, the RTX 5000 Ada holds an average score of 184,664 across its recorded tests, which includes a Vulkan score of 194,041 in addition to the OpenCL result. The Tesla P100's average is identical to its single OpenCL score of 79,396, since that is the only benchmark recorded for it. The gap between the two averages is approximately 132.6% in favor of the newer card, a figure that aligns with the head-to-head delta.

When placed against its nearest rivals, the RTX 5000 Ada sits in a tight cluster of high-end accelerators. Its average of 184,664 is 0.5% above the NVIDIA A100 SXM4 80 GB (183,725), 1.3% below the NVIDIA A100 SXM4 40 GB (187,147), 1.4% above the NVIDIA RTX PRO 5000 Blackwell (182,109), and 3.7% above the NVIDIA GeForce RTX 4090 D (178,050). This places it at the 98th percentile among all GPUs in the database, a ranking that reflects its position near the very top of the performance stack.

The Tesla P100, by contrast, finds itself in more modest company. Its average of 79,396 is 0.3% below the NVIDIA Tesla P100 PCIe 16 GB (79,605), 0.6% below the NVIDIA GeForce RTX 5090 (79,842), 0.6% above the AMD Radeon RX 6850M XT (78,940), and 1.9% below the AMD Radeon Pro Vega 64X (80,959). It sits at the 92nd percentile among all GPUs, which is still a strong position, but the raw score gap to the RTX 5000 Ada is enormous. The percentile difference of 6 points understates how far apart these two cards actually are in absolute compute throughput.

The win count in the head-to-head section is 1 for the RTX 5000 Ada and 0 for the Tesla P100. There is no benchmark in the database where the older card comes out ahead. The data indicates that the RTX 5000 Ada is not merely faster; it is in a different performance tier altogether.

FAQ

Q: How much faster is the RTX 5000 Ada in the only shared benchmark?

A: In the Geekbench OpenCL test, the RTX 5000 Ada scores 175,286 versus the Tesla P100's 79,396, a 120.8% delta. The newer card delivers more than double the score.

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

A: The RTX 5000 Ada has an average benchmark score of 184,664, based on its OpenCL and Vulkan results. The Tesla P100 has an average of 79,396, based solely on its OpenCL score.

Q: How do these cards rank against all other GPUs?

A: The RTX 5000 Ada sits at the 98th percentile among all GPUs in the database. The Tesla P100 sits at the 92nd percentile.

Q: Which card has a higher transistor density?

A: The RTX 5000 Ada, built on a 5 nm process, has a transistor density of 125.3 million transistors per square millimeter. The Tesla P100, on a 16 nm process, has a density of 25.1 million per square millimeter.

Q: Does the Tesla P100 support ray tracing or tensor operations?

A: No. The Tesla P100 has no ray tracing cores and no tensor cores. The RTX 5000 Ada includes 100 ray tracing cores and 400 tensor cores.

Q: What is the memory configuration difference?

A: The RTX 5000 Ada has 32 GB of GDDR6 memory on a 256-bit bus with 576.0 GB/s bandwidth. The Tesla P100 has 12 GB of HBM2 memory on a 3072-bit bus with 549.1 GB/s bandwidth.

Architecture Differences

The two cards come from entirely different architectural eras. The RTX 5000 Ada is built on the Ada Lovelace architecture, using the AD102 chip, fabricated on a 5 nm process at TSMC. The Tesla P100 uses the Pascal architecture with the GP100 chip, fabricated on a 16 nm process, also at TSMC. The process node difference is stark: 5 nm versus 16 nm, which directly impacts transistor density. The AD102 packs 76,300 million transistors into a 609 mm² die, yielding a density of 125.3 million transistors per square millimeter. The GP100 contains 15,300 million transistors on a 610 mm² die, for a density of just 25.1 million per square millimeter. The die sizes are nearly identical, but the newer process allows roughly five times more transistors in the same footprint.

The compute architecture diverges sharply. The RTX 5000 Ada features 12,800 shading units, 400 texture mapping units, and 176 render output units. It also includes 100 dedicated ray tracing cores and 400 tensor cores, enabling hardware-accelerated ray tracing and AI workloads. The Tesla P100 has 3,584 shading units, 224 texture mapping units, and 96 render output units, with no ray tracing or tensor cores at all. This means the Pascal card cannot accelerate these workloads in hardware, relying entirely on software fallbacks.

The memory subsystem also reflects different design philosophies. The RTX 5000 Ada uses 32 GB of GDDR6 memory on a 256-bit bus, running at 18 Gbps effective, delivering 576.0 GB/s of bandwidth. The Tesla P100 uses 12 GB of HBM2 memory on a massive 3072-bit bus, running at 1430 Mbps effective, delivering 549.1 GB/s. The bus width difference is enormous, but the higher clock speed of the GDDR6 memory nearly closes the bandwidth gap. The RTX 5000 Ada still edges ahead in raw bandwidth by about 4.9%.

The floating-point capabilities tell the story of architectural focus. The RTX 5000 Ada delivers 65.28 TFLOPS of FP32 and 65.28 TFLOPS of FP16 with a 1:1 ratio. The Tesla P100 delivers 9.526 TFLOPS of FP32 and 19.05 TFLOPS of FP16 with a 2:1 ratio. The Pascal card's FP16 throughput is double its FP32, a design choice for early deep learning workloads, but the absolute numbers are far lower than the Ada card's unified throughput.

Specification Differences

The RTX 5000 Ada and Tesla P100 differ in nearly every measurable specification. The process node is 5 nm for the Ada card versus 16 nm for the Pascal card. Transistor count is 76,300 million versus 15,300 million. Transistor density is 125.3 million per square millimeter versus 25.1 million. The base clock is 1155 MHz versus 1190 MHz, but the boost clock is 2550 MHz versus 1329 MHz, giving the Ada card a massive clock advantage under load.

Memory specifications diverge completely: 32 GB of GDDR6 versus 12 GB of HBM2, with bus widths of 256-bit versus 3072-bit. Effective memory speed is 18 Gbps versus 1430 Mbps, resulting in bandwidth of 576.0 GB/s versus 549.1 GB/s. The shading unit count is 12,800 versus 3,584. Texture mapping units are 400 versus 224. Render output units are 176 versus 96. The RTX 5000 Ada has 100 ray tracing cores and 400 tensor cores, while the Tesla P100 has none of either.

Pixel and texture rates follow the compute gap: the Ada card achieves 448.8 GPixel/s and 1,020.0 GTexel/s, compared to 127.6 GPixel/s and 297.7 GTexel/s for the Pascal card. FP32 throughput is 65.28 TFLOPS versus 9.526 TFLOPS. FP16 throughput is 65.28 TFLOPS versus 19.05 TFLOPS.

Power and connectivity differ as well. Both cards have a 250 W TDP and a suggested PSU of 600 W. The RTX 5000 Ada uses a single 16-pin power connector, while the Tesla P100 uses a single 8-pin connector. The Ada card is PCIe 4.0 x16, while the Tesla P100 is PCIe 3.0 x16. Display outputs are completely different: the RTX 5000 Ada has 4x DisplayPort 1.4a, while the Tesla P100 has no display outputs at all, making it a compute-only accelerator.

API support also differs. The Ada card supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The Pascal card supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.3. The production status is Active for the RTX 5000 Ada and End-of-life for the Tesla P100.

Where Each One Wins

The RTX 5000 Ada wins in every recorded benchmark category. In OpenCL compute, it more than doubles the Tesla P100's score. In Vulkan, the Ada card posts a 194,041 score, a test the Pascal card has no recorded result for. The Ada card also wins on memory capacity, bandwidth, shading units, texture rate, pixel rate, FP32 throughput, and FP16 throughput.

The Tesla P100's advantages are narrow but real. It has a higher base clock at 1190 MHz versus 1155 MHz. Its HBM2 memory bus is 3072-bit versus 256-bit, which gives it a fundamentally different memory architecture. It also has a smaller die size at 610 mm² versus 609 mm², though this is negligible. The Tesla P100's 2:1 FP16 ratio means it can double its FP32 throughput in FP16 workloads, but even that doubled figure of 19.05 TFLOPS is far below the Ada card's 65.28 TFLOPS.

For practical use, the RTX 5000 Ada is the clear choice for any compute workload where raw throughput matters. Its 32 GB of memory also allows larger datasets to reside on the card. The Tesla P100, with its 12 GB of HBM2 memory and 549.1 GB/s bandwidth, remains a functional accelerator for workloads that fit within its memory footprint, but its end-of-life status and lack of modern features like ray tracing and tensor cores limit its future relevance.

The Verdict

The data points to a single conclusion: the RTX 5000 Ada Generation is the superior card in every recorded benchmark. Its OpenCL score of 175,286 versus the Tesla P100's 79,396 represents a 120.8% performance advantage. Its average benchmark score of 184,664 places it at the 98th percentile among all GPUs, while the Tesla P100's 79,396 sits at the 92nd percentile.

For builders or researchers selecting a card today, the RTX 5000 Ada offers modern architecture, active production status, ray tracing and tensor cores, 32 GB of GDDR6 memory, and double the compute throughput. The Tesla P100, while still a capable accelerator with 12 GB of HBM2 and a wide memory bus, is end-of-life, lacks display outputs, has no hardware ray tracing or tensor acceleration, and delivers less than half the compute performance.

The choice depends on workload fit. If the task requires maximum compute throughput, modern API support, or the ability to handle large memory footprints, the RTX 5000 Ada is the only rational option from the data. If the workload is legacy, fits within 12 GB of memory, and does not require modern features, the Tesla P100 remains functional, but the benchmark results show it is outclassed by a wide margin. The RTX 5000 Ada is the recommended pick for anyone prioritizing performance and longevity.