AMD FirePro D500 vs NVIDIA Tesla K40m Comparison

The NVIDIA Tesla K40m and AMD FirePro D500 represent two distinct approaches to professional GPU computing from the same era, built on the same 28 nm TSMC process but with fundamentally different architectures. The Tesla K40m uses NVIDIA’s Kepler design with the GK110B chip, packing 7,080 million transistors into a 561 mm² die, while the FirePro D500 uses AMD’s GCN 1.0 architecture with the Tahiti chip, containing 4,313 million transistors on a 352 mm² die. This transistor disparity—the NVIDIA chip has roughly 64% more transistors—directly influences the performance envelope, as the Tesla K40m delivers 5.046 TFLOPS of FP32 compute versus 2.227 TFLOPS for the FirePro D500. The architectural split runs deeper: Kepler relies on a larger array of simpler cores (2,880 shading units, 240 TMUs, 48 ROPs) whereas GCN 1.0 uses fewer, wider compute units (1,536 shading units, 96 TMUs, 32 ROPs). Clock behavior also diverges, with the Tesla K40m running at a 745 MHz base and 876 MHz boost, while the FirePro D500 has no listed base or boost clocks, only a memory clock of 1270 MHz (5.1 Gbps effective). The Tesla’s memory subsystem operates at 1502 MHz (6 Gbps effective), yielding 288.4 GB/s of bandwidth across a 384-bit bus, compared to the FirePro’s 243.8 GB/s on the same 384-bit bus width but with slower memory.

Head-to-Head Benchmarks

The benchmark data presents a single comparison point for each card, and the results illustrate how differently these two GPUs perform depending on the workload. The Tesla K40m scores 19,885 in Geekbench OpenCL, placing it in the 65th percentile of all GPUs. The FirePro D500, meanwhile, posts a Geekbench Vulkan score of 18,533, which lands in the 62nd percentile. These are different APIs—OpenCL for NVIDIA and Vulkan for AMD—so a direct head-to-head comparison requires caution, but the percentile gap of three points suggests the Tesla holds a slight overall performance advantage. When placed against their nearest rivals, the Tesla K40m’s OpenCL score sits within a tight band: it trails the AMD FirePro W7000 (19,905) by just 0.1%, edges out the AMD Radeon RX 6650 XT (19,765) by 0.6%, leads the AMD FirePro D300 (19,637) by 1.3%, and beats the NVIDIA Quadro K5200 (19,602) by 1.4%. These deltas are remarkably small, indicating that the Tesla K40m is essentially performance-equivalent to its immediate competitors in OpenCL workloads. The FirePro D500’s Vulkan score of 18,533 is similarly clustered: it trails the AMD Radeon RX 560X (18,626) by 0.5%, falls behind the AMD Radeon Pro 5700 XT (18,685) by 0.8%, but leads the Intel Arc A770M (18,383) by 0.8% and the AMD Radeon RX 460 (18,373) by 0.9%. Again, the deltas are under one percent in either direction, showing that the FirePro D500 is competitively positioned within its Vulkan benchmark tier.

The raw compute numbers tell a more dramatic story than the benchmark scores. In pure FP32 throughput, the Tesla K40m delivers 5.046 TFLOPS—more than double the FirePro D500’s 2.227 TFLOPS. This 2.27x advantage in theoretical compute does not translate into a proportional benchmark lead, which highlights how real-world tests exercise memory bandwidth, driver efficiency, and API-specific optimizations rather than raw shader math. The pixel rate follows a similar pattern: the Tesla K40m achieves 52.56 GPixel/s versus 23.20 GPixel/s for the FirePro D500, a 2.27x gap that mirrors the FP32 ratio. Texture rate shows an even wider disparity, with the Tesla hitting 210.2 GTexel/s compared to the FirePro’s 69.60 GTexel/s—a 3.02x difference driven by the NVIDIA card’s 240 TMUs versus 96 on the AMD part. Memory bandwidth favors the Tesla by a narrower margin: 288.4 GB/s versus 243.8 GB/s, an 18% advantage that reflects the higher memory clock (6 Gbps effective versus 5.1 Gbps) despite identical 384-bit bus widths. The benchmark scores, however, compress these differences, suggesting that the Geekbench OpenCL and Vulkan tests are not purely compute-bound and instead reward balanced architectures.

The Verdict

From the data, the NVIDIA Tesla K40m is the clear choice for raw compute throughput. Its 5.046 TFLOPS FP32 performance, 210.2 GTexel/s texture rate, and 52.56 GPixel/s pixel rate are all more than double the FirePro D500’s corresponding figures. The Tesla also holds a slight edge in the percentile ranking (65th versus 62nd) and delivers 12 GB of memory versus 3 GB, which is a fourfold capacity advantage that matters for large datasets. The benchmark scores, while from different APIs, are close (19,885 versus 18,533), but the Tesla’s 65th percentile placement versus the FirePro’s 62nd suggests that across a broader test suite, the NVIDIA card would likely maintain a lead. The Tesla K40m’s nearest rivals are all within 1.4% of its score, meaning it is a well-optimized design for its era, while the FirePro D500’s closest competitors are similarly tight, indicating both cards are near the top of their respective performance classes.

The AMD FirePro D500, however, is not without justification. Its Vulkan score of 18,533 comes from a test that the Tesla K40m does not have a recorded result for, and the FirePro’s 62nd percentile is respectable. The AMD card offers 6x mini-DisplayPort 1.2 outputs plus 1x SDI, making it a viable option for display-centric workloads, whereas the Tesla K40m has no display outputs at all. The FirePro D500 also has a lower transistor count (4,313 million versus 7,080 million) and a smaller die (352 mm² versus 561 mm²), which could imply lower manufacturing complexity, though its TDP is higher at 274 W versus 245 W for the Tesla. For users who need compute density and memory capacity, the Tesla K40m is the data-backed winner. For those who require video outputs or prefer AMD’s GCN architecture, the FirePro D500 holds its own within a narrow benchmark band. The data does not support a runaway victory for either card in real-world tests, but the Tesla’s substantial hardware specifications give it the edge in compute-bound scenarios.

Specification Differences

The two cards diverge on nearly every major specification except process node, foundry, memory type, bus width, and bus interface. Both use 28 nm TSMC process technology and GDDR5 memory with a 384-bit bus, and both connect via PCIe 3.0 x16. Beyond that, the differences are substantial. The Tesla K40m uses the GK110B chip with 7,080 million transistors on a 561 mm² die, while the FirePro D500 uses Tahiti with 4,313 million transistors on a 352 mm² die. Transistor density is nearly identical (12.6M / mm² versus 12.3M / mm²), reflecting the same process generation. The Tesla has 2,880 shading units, 240 TMUs, and 48 ROPs, versus 1,536 shading units, 96 TMUs, and 32 ROPs on the FirePro. Clock speeds differ fundamentally: the Tesla has a 745 MHz base and 876 MHz boost, while the FirePro lists no base or boost clocks at all, only a memory clock of 1270 MHz (5.1 Gbps effective) compared to the Tesla’s 1502 MHz (6 Gbps effective). Memory capacity is a major differentiator—12 GB on the Tesla versus 3 GB on the FirePro—though bandwidth is closer at 288.4 GB/s versus 243.8 GB/s. Pixel rate (52.56 versus 23.20 GPixel/s), texture rate (210.2 versus 69.60 GTexel/s), and FP32 (5.046 versus 2.227 TFLOPS) all favor the Tesla by roughly 2-3x. TDP is higher on the FirePro at 274 W versus 245 W, with a suggested PSU of 600 W versus 550 W. The Tesla has no display outputs, while the FirePro has 6x mini-DisplayPort 1.2 and 1x SDI. Physical dimensions favor the Tesla at 267 mm (10.5 inches) versus 279 mm (11 inches) for the FirePro. API support is similar, with both supporting DirectX 12 (11_1) and OpenGL 4.6, but the Tesla has Vulkan 1.2.175 versus 1.2.170 on the FirePro. Release dates are close (November 2013 for the Tesla, January 2014 for the FirePro), and both are end-of-life. The Tesla has a launch MSRP of 7,699 USD; the FirePro has no listed launch MSRP.

FAQ

Q: Which card has higher FP32 compute performance?

A: The NVIDIA Tesla K40m delivers 5.046 TFLOPS of FP32 performance, which is more than double the AMD FirePro D500’s 2.227 TFLOPS.

Q: How do the benchmark scores compare between the two cards?

A: The Tesla K40m scores 19,885 in Geekbench OpenCL (65th percentile), while the FirePro D500 scores 18,533 in Geekbench Vulkan (62nd percentile). These are different APIs, so the scores are not directly comparable, but the percentile difference indicates the Tesla holds a slight edge.

Q: What is the memory capacity difference?

A: The Tesla K40m has 12 GB of GDDR5 memory, while the FirePro D500 has 3 GB. Both use a 384-bit bus, but the Tesla’s higher memory clock (6 Gbps effective versus 5.1 Gbps) gives it 288.4 GB/s bandwidth versus 243.8 GB/s.

Q: Do both cards support the same display outputs?

A: No. The FirePro D500 has 6x mini-DisplayPort 1.2 and 1x SDI outputs, while the Tesla K40m has no display outputs at all.

Q: Which card has a higher TDP and suggested PSU?

A: The FirePro D500 has a 274 W TDP with a 600 W suggested PSU, while the Tesla K40m has a 245 W TDP with a 550 W suggested PSU.

Q: How does the Tesla K40m compare to its nearest rivals?

A: The Tesla K40m trails the AMD FirePro W7000 by 0.1%, leads the AMD Radeon RX 6650 XT by 0.6%, leads the AMD FirePro D300 by 1.3%, and leads the NVIDIA Quadro K5200 by 1.4% in Geekbench OpenCL scores.