NVIDIA RTX 4000 SFF Ada Generation vs NVIDIA Tesla P100 PCIe 16 GB Comparison

Head-to-Head Benchmarks

The recorded data contains a single direct benchmark comparison between these two accelerators, and it is decisive. In the Geekbench OpenCL test, the NVIDIA RTX 4000 SFF Ada Generation scores 124,812, while the NVIDIA Tesla P100 PCIe 16 GB trails at 79,605. That is a 56.8% advantage for the RTX 4000 SFF Ada Generation, a substantial margin that places the two cards in entirely different performance tiers despite both being professional NVIDIA products.

This result aligns with their broader database standings. The RTX 4000 SFF Ada Generation sits at the 95th percentile among all GPUs, with an average benchmark score of 117,088 across its recorded tests. The Tesla P100 PCIe 16 GB, by contrast, holds the 92nd percentile with an average score of 79,605. The percentile gap is narrow, only three points, but the raw score difference is large because the distribution of GPU scores widens considerably at the top end.

Looking at the RTX 4000 SFF Ada Generation's nearest rivals in the database, its standing is tight. The NVIDIA GB10 averages 117,393, which is only 0.3% higher. The AMD Radeon PRO W7700 averages 118,976, a 1.6% lead. The NVIDIA Tesla V100 SXM2 16 GB averages 114,395, meaning the RTX 4000 SFF Ada Generation is 2.4% ahead of that card. The NVIDIA RTX A5500 Mobile averages 113,944, putting the RTX 4000 SFF Ada Generation 2.8% ahead. These are all close competitors within a few percentage points, which makes the 56.8% lead over the Tesla P100 PCIe 16 GB all the more striking.

The Tesla P100 PCIe 16 GB's nearest rivals tell a similar story from the other side. The Tesla P100 PCIe 12 GB averages 79,396, a 0.3% deficit to the 16 GB version. The GeForce RTX 5090 averages 79,842, which is 0.3% higher. The AMD Radeon RX 6850M XT averages 78,940, putting the P100 0.8% ahead. The AMD Radeon Pro Vega 64X averages 80,959, which is 1.7% higher than the P100. None of these rivals approach the performance level of the RTX 4000 SFF Ada Generation; they are all clustered near the P100's own score.

The OpenCL result is the only head-to-head test recorded, so the performance comparison rests on that single measurement. It is a clean and unambiguous data point. The RTX 4000 SFF Ada Generation also has a Geekbench Vulkan score of 109,364, for which no direct Tesla P100 comparison exists in the database. That Vulkan result is lower than its OpenCL result by roughly 12.4%, which is typical for workloads where driver and API overhead differ.

Architecture Differences

The two cards come from different architectural generations and manufacturing processes. The RTX 4000 SFF Ada Generation uses the AD104 chip built on Ada Lovelace architecture, fabricated by TSMC on a 5 nm process. It packs 35,800 million transistors into a 294 mm² die, yielding a transistor density of 121.8 million per square millimeter. The Tesla P100 PCIe 16 GB uses the GP100 chip on Pascal architecture, also TSMC-fabricated but on a 16 nm process. It contains 15,300 million transistors spread across a much larger 610 mm² die, giving a density of only 25.1 million per square millimeter.

The process advantage is clear: the Ada card crams more than twice the transistors into less than half the die area. This explains how the RTX 4000 SFF Ada Generation achieves far higher compute throughput while consuming dramatically less power.

Compute resources differ sharply. The RTX 4000 SFF Ada Generation has 6,144 shading units, 192 texture mapping units, and 64 raster output units. It also includes 48 ray tracing cores and 192 tensor cores, features entirely absent from the Tesla P100. The Pascal card has 3,584 shading units, 224 TMUs, and 96 ROPs. Fewer shaders but more TMUs and ROPs means the P100's fixed-function throughput is proportionally stronger relative to its compute, but its raw shader count is far lower.

Clock speeds tell another part of the story. The RTX 4000 SFF Ada Generation runs at a 720 MHz base clock and 1,560 MHz boost. The Tesla P100 runs at 1,190 MHz base and 1,329 MHz boost. The P100's base clock is substantially higher, but the Ada card's boost clock is 17.4% higher. More importantly, the Ada card sustains that boost across a 70 W power envelope, while the P100 requires 250 W.

Memory subsystems are fundamentally different. The RTX 4000 SFF Ada Generation uses 20 GB of GDDR6 on a 160-bit bus, delivering 280.0 GB/s of bandwidth. The Tesla P100 uses 16 GB of HBM2 on a massive 4096-bit bus, delivering 732.2 GB/s. The P100 has 2.6 times the bandwidth, which is significant for memory-bound workloads. However, the Ada card has 25% more capacity, which matters for holding larger models or datasets in memory.

The API support also differs. The RTX 4000 SFF Ada Generation supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The Tesla P100 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.3. The Ada card's newer DirectX feature level and newer Vulkan version reflect its more recent architecture.

Where Each One Wins

The RTX 4000 SFF Ada Generation wins in overall compute performance, as shown by the 56.8% OpenCL advantage. It also wins on raw FP32 throughput: 19.17 TFLOPS versus 9.526 TFLOPS for the P100, a 101.2% advantage. Its FP16 performance is 19.17 TFLOPS with a 1:1 ratio, while the P100 reaches 19.05 TFLOPS with a 2:1 ratio. In FP16, the two are nearly identical, but the Ada card achieves parity without relying on the 2:1 rate that the Pascal architecture uses.

The Ada card wins decisively on efficiency. Its 70 W TDP is 72% lower than the P100's 250 W. It requires no power connectors, while the P100 needs a single 8-pin connector. The suggested power supply is 250 W for the Ada card versus 600 W for the P100. For dense workstations or multi-GPU configurations, this difference is enormous. The Ada card is also much shorter at 168 mm versus 267 mm for the P100.

The Tesla P100 wins on memory bandwidth. Its 732.2 GB/s is more than 2.5 times the Ada card's 280.0 GB/s. For workloads that stream large amounts of data through memory, the P100's HBM2 implementation provides a clear advantage, despite its lower compute throughput. The P100 also has a wider memory bus at 4096-bit versus 160-bit, which is why its bandwidth is so much higher.

The P100 wins on texture and pixel throughput in absolute terms. Its texture rate is 297.7 GTexel/s versus 299.5 GTexel/s for the Ada card, essentially a tie. Its pixel rate is 127.6 GPixel/s versus 99.84 GPixel/s for the Ada card, a 27.8% advantage for the P100. These fixed-function rates come from the P100's higher ROP and TMU counts combined with its higher base clock.

The P100 also has display output differences in the opposite direction: it has no display outputs at all, while the Ada card has four mini-DisplayPort 1.4a connectors. The Ada card can drive displays directly, making it suitable for workstation use that requires visual output.

FAQ

Q: Which card is faster in OpenCL?

A: The NVIDIA RTX 4000 SFF Ada Generation scores 124,812 versus 79,605 for the Tesla P100 PCIe 16 GB, a 56.8% advantage.

Q: How do their memory bandwidths compare?

A: The Tesla P100 PCIe 16 GB has 732.2 GB/s of bandwidth from its 4096-bit HBM2 interface, while the RTX 4000 SFF Ada Generation has 280.0 GB/s from a 160-bit GDDR6 interface.

Q: What is the power consumption difference?

A: The RTX 4000 SFF Ada Generation has a 70 W TDP and requires no power connectors, while the Tesla P100 PCIe 16 GB has a 250 W TDP and requires a single 8-pin connector. The suggested PSU is 250 W for the Ada card and 600 W for the P100.

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

A: No. The Tesla P100 has no ray tracing cores and no tensor cores. The RTX 4000 SFF Ada Generation has 48 ray tracing cores and 192 tensor cores.

Q: Can the Tesla P100 drive displays?

A: No, the Tesla P100 has no display outputs. The RTX 4000 SFF Ada Generation has four mini-DisplayPort 1.4a outputs.

Q: Which card has more memory?

A: The RTX 4000 SFF Ada Generation has 20 GB of GDDR6, while the Tesla P100 PCIe 16 GB has 16 GB of HBM2. The Ada card has 25% more capacity.

The Verdict

The data points to a clear overall winner for general compute: the NVIDIA RTX 4000 SFF Ada Generation. It delivers 56.8% higher OpenCL performance, has more than double the FP32 throughput, supports ray tracing and tensor cores, offers 20 GB of memory, and does all of this within a 70 W envelope. The 5 nm Ada Lovelace architecture, with its 35,800 million transistors, represents a generational leap over the 16 nm Pascal design.

The Tesla P100 PCIe 16 GB retains one meaningful advantage: memory bandwidth. At 732.2 GB/s, it offers 2.6 times the bandwidth of the Ada card. For workloads that are purely memory-bound and do not require modern compute features, the P100 could still hold its own. Its 16 GB of HBM2 capacity and 4096-bit bus are impressive even by current standards.

However, the P100's advantages are narrow. Its texture rate is essentially identical to the Ada card, its pixel rate is higher, but its compute throughput is less than half. It has no display outputs, no ray tracing, no tensor cores, and it is end-of-life. The RTX 4000 SFF Ada Generation is active, smaller, more efficient, and faster in the only direct benchmark recorded.

Who should pick the RTX 4000 SFF Ada Generation: anyone running OpenCL workloads, mixed compute and graphics tasks, AI inference that can use tensor cores, or any environment where power and space are constrained. Its dual-slot, 168 mm length and no power connector requirement make it exceptionally easy to integrate.

Who should pick the Tesla P100 PCIe 16 GB: only those whose workloads are dominated by memory bandwidth and who already have the 250 W power budget and 600 W PSU capacity. Its 732.2 GB/s bandwidth is a genuine asset for large streaming data, but the compute deficit and lack of modern features are difficult to overlook.

The launch MSRP for the Tesla P100 PCIe 16 GB was 5,699 USD. The RTX 4000 SFF Ada Generation has no recorded launch MSRP in the database.

Specification Differences

The two cards differ in nearly every major specification category.

Chip and architecture: AD104 on Ada Lovelace versus GP100 on Pascal.

Process node: 5 nm versus 16 nm, both TSMC.

Transistors: 35,800 million versus 15,300 million.

Die size: 294 mm² versus 610 mm².

Transistor density: 121.8M per mm² versus 25.1M per mm².

Base clock: 720 MHz versus 1,190 MHz.

Boost clock: 1,560 MHz versus 1,329 MHz.

Memory size: 20 GB GDDR6 versus 16 GB HBM2.

Memory bus width: 160-bit versus 4096-bit.

Memory bandwidth: 280.0 GB/s versus 732.2 GB/s.

Memory clock: 1750 MHz (14 Gbps effective) versus 715 MHz (1430 Mbps effective).

Shading units: 6,144 versus 3,584.

TMUs: 192 versus 224.

ROPs: 64 versus 96.

Ray tracing cores: 48 versus none.

Tensor cores: 192 versus none.

Pixel rate: 99.84 GPixel/s versus 127.6 GPixel/s.

Texture rate: 299.5 GTexel/s versus 297.7 GTexel/s.

FP32 performance: 19.17 TFLOPS versus 9.526 TFLOPS.

FP16 performance: 19.17 TFLOPS (1:1) versus 19.05 TFLOPS (2:1).

TDP: 70 W versus 250 W.

Power connectors: None versus 1x 8-pin.

Suggested PSU: 250 W versus 600 W.

Bus interface: PCIe 4.0 x16 versus PCIe 3.0 x16.

Display outputs: 4x mini-DisplayPort 1.4a versus no outputs.

DirectX support: 12 Ultimate (12_2) versus 12 (12_1).

Vulkan support: 1.4 versus 1.3.

Dimensions: 168 mm length versus 267 mm length.

Production status: Active versus end-of-life.

Release date: 2023-03-20 versus 2016-06-19.

Predecessor: Workstation Ampere versus Tesla Maxwell.

Successor: Blackwell PRO W versus Tesla Volta.