AMD FirePro W4100 vs NVIDIA Quadro K620M Comparison

The AMD FirePro W4100 and NVIDIA Quadro K620M are both end-of-life mobile workstation graphics solutions, yet they represent fundamentally different design philosophies from their respective manufacturers. The data reveals a striking outcome: despite the FirePro W4100 having a larger die, more memory bandwidth, and a wider bus, the Quadro K620M emerges victorious in the only direct head-to-head benchmark available. This result challenges the assumption that raw hardware specifications directly translate to application performance, particularly in the professional graphics segment.

Head-to-Head Benchmarks

The sole direct comparison in the database is the Geekbench OpenCL test, where the NVIDIA Quadro K620M scores 5957 against the AMD FirePro W4100’s 5478. This translates to an 8% victory for the NVIDIA solution, a margin that is not trivial in the context of workstation tasks where every percentage point of compute throughput matters. The Quadro K620M’s advantage here is especially notable given that the FirePro W4100 posts a higher theoretical FP32 throughput of 645.1 GFLOPS compared to the K620M’s 863.2 GFLOPS. Wait, the data shows the opposite — the NVIDIA part actually has the higher FP32 figure. This means the K620M’s OpenCL win is consistent with its compute ceiling, but the magnitude of the delta (8%) is smaller than the 33.8% gap in raw FP32 would suggest, implying that the FirePro W4100’s architecture extracts relatively more real-world performance per GFLOP in this particular workload.

Looking at the broader benchmark context, the FirePro W4100 also has a Geekbench Vulkan score of 6496, a test that the Quadro K620M does not have a recorded result for. While this cannot be directly compared, it does indicate that the AMD card has a functional Vulkan driver stack capable of delivering a score that is 18.6% higher than its own OpenCL result. The average benchmark score for the FirePro W4100 is 5987, which is actually higher than the K620M’s single recorded average of 5957, suggesting that the AMD card’s Vulkan performance pulls its overall average above the NVIDIA card’s OpenCL-only figure. The wins tally is one for the K620M and zero for the W4100, but the absence of a Vulkan result for the NVIDIA card makes this a partial picture.

Architecture Differences

The architectural chasm between these two GPUs is wide. The AMD FirePro W4100 is built on the GCN 1.0 architecture using the Cape Verde chip, fabricated on a 28 nm process at TSMC. This chip packs 1,500 million transistors onto a 123 mm² die, yielding a transistor density of 12.2 million per square millimeter. In contrast, the NVIDIA Quadro K620M uses the Maxwell architecture with the GM108S chip, also on TSMC’s 28 nm node, but with 1,020 million transistors on a much smaller 77 mm² die, resulting in a higher density of 13.2 million per square millimeter. The smaller, denser NVIDIA chip is more efficient in terms of transistor packing, but the AMD chip has 47% more transistors overall.

The compute resources diverge sharply. The FirePro W4100 fields 512 shading units, 32 texture mapping units (TMUs), and 16 raster operation units (ROPs). The K620M counters with 384 shading units, 16 TMUs, and just 8 ROPs. The AMD card’s double the TMU and ROP counts suggest a design aimed at higher fill-rate and texture-heavy workloads, which is reflected in its pixel rate of 10.08 GPixel/s versus the K620M’s 8.992 GPixel/s, and texture rate of 20.16 GTexel/s versus 17.98 GTexel/s. Yet the K620M’s FP32 performance is higher at 863.2 GFLOPS versus 645.1 GFLOPS, indicating that NVIDIA’s Maxwell architecture achieves more compute per shading unit, proof of its improved instruction efficiency.

Memory subsystems tell another story of divergence. The FirePro W4100 uses 2 GB of GDDR5 on a 128-bit bus, delivering 64.00 GB/s of bandwidth at a memory clock of 1000 MHz (4 Gbps effective). The K620M uses 2 GB of DDR3 on a 64-bit bus, yielding only 16.02 GB/s at 1001 MHz (2 Gbps effective). The AMD card has a 4x bandwidth advantage, which should theoretically dominate memory-bound tasks. The fact that it still loses in OpenCL suggests that either the workload is not bandwidth-limited, or that the NVIDIA driver’s scheduling is superior. The K620M’s base clock of 1029 MHz and boost of 1124 MHz are notable, while the W4100’s clocks are not listed, making clock-speed comparison impossible.

FAQ

Q: Which GPU has the higher average benchmark score?

A: The AMD FirePro W4100 has an average benchmark score of 5987, which is 0.5% higher than the NVIDIA Quadro K620M’s 5957, despite the K620M winning the direct OpenCL comparison.

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

A: The FirePro W4100 has a 64.00 GB/s bandwidth from its 128-bit GDDR5 interface, while the K620M has only 16.02 GB/s from its 64-bit DDR3 bus, giving the AMD card a 4x advantage in raw bandwidth.

Q: What is the transistor count and die size difference?

A: The AMD chip has 1,500 million transistors on a 123 mm² die, while the NVIDIA chip has 1,020 million transistors on a 77 mm² die. The AMD die is 59.7% larger by area, but the NVIDIA die has a higher transistor density of 13.2M per mm².

Q: Which card supports Vulkan, and what are the scores?

A: The FirePro W4100 has a Geekbench Vulkan score of 6496, while the K620M has no recorded Vulkan benchmark. Both cards support DirectX 12, but the W4100 is listed as 12 (11_1) while the K620M is 12 (11_0).

Q: What are the power consumption figures?

A: The FirePro W4100 has a TDP of 50 W, while the Quadro K620M is rated at 30 W. The AMD card also lists a suggested PSU of 250 W, whereas no such figure is provided for the NVIDIA card.

Q: How do the nearest rivals position these GPUs in the market?

A: The FirePro W4100’s closest rival is the NVIDIA Quadro K4000M with an average score of 5986 (0% delta), while the K620M’s nearest rival is the AMD Radeon HD 8730M at 5955 (0% delta), indicating both cards sit in a very tight performance band around the 5950-5990 mark.

Specification Differences

The two cards differ across nearly every measurable specification. The FirePro W4100 is an AMD GCN 1.0 architecture part using the Cape Verde chip, while the K620M is NVIDIA Maxwell using GM108S. The FirePro has 512 shading units, 32 TMUs, and 16 ROPs, versus the K620M’s 384, 16, and 8 respectively. FP32 compute is 645.1 GFLOPS for the AMD card versus 863.2 GFLOPS for the NVIDIA card. Pixel rate is 10.08 GPixel/s versus 8.992 GPixel/s, and texture rate is 20.16 GTexel/s versus 17.98 GTexel/s.

Memory configuration is starkly different: the W4100 uses 2 GB GDDR5 on a 128-bit bus at 1000 MHz with 64.00 GB/s bandwidth, while the K620M uses 2 GB DDR3 on a 64-bit bus at 1001 MHz with 16.02 GB/s. The TDP is 50 W for the AMD card versus 30 W for the NVIDIA card. The W4100 is a single-slot, 171 mm long PCIe 3.0 x16 card with four mini-DisplayPort 1.2 outputs, whereas the K620M is an MXM module using MXM-A (3.0) with portable-device-dependent outputs. The DirectX support differs: 12 (11_1) for the AMD card versus 12 (11_0) for the NVIDIA card, with both supporting OpenGL 4.6. Vulkan support is 1.2.170 for the W4100 and 1.4 for the K620M.

The Verdict

The data points to a nuanced conclusion. In the only head-to-head test (Geekbench OpenCL), the NVIDIA Quadro K620M is the clear winner with an 8% margin. This is the decisive metric for a direct comparison. However, the AMD FirePro W4100 has a higher average benchmark score (5987 versus 5957) because its Vulkan performance of 6496 is not matched by any recorded Vulkan result for the NVIDIA card. For users running OpenCL-centric professional workloads, the K620M is the superior choice based on the direct evidence. The W4100’s massive memory bandwidth advantage (64.00 GB/s versus 16.02 GB/s) and higher pixel/texture rates suggest it would excel in memory-bound or fill-rate-limited scenarios, but the OpenCL result implies that the NVIDIA architecture’s compute efficiency overcomes this handicap.

For those prioritizing compute density per watt, the K620M’s 30 W TDP versus the W4100’s 50 W TDP makes it a more power-efficient solution in a mobile workstation context. The K620M also has a higher transistor density on a smaller die, indicating a more modern design approach. The W4100’s superior display output (four mini-DisplayPort versus portable-device-dependent) makes it more suitable for multi-monitor fixed installations. Ultimately, the verdict is that the K620M wins on measured compute performance, while the W4100 wins on memory bandwidth and display connectivity. Neither card is a universal victor, but the single benchmark result gives the NVIDIA product the edge in direct comparison.

Where Each One Wins

The AMD FirePro W4100 wins in scenarios that depend on memory bandwidth and fill rates. Its 64.00 GB/s GDDR5 bandwidth is four times that of the K620M’s 16.02 GB/s, making it the obvious pick for large texture datasets or high-resolution rendering that saturates the memory bus. Its pixel rate of 10.08 GPixel/s and texture rate of 20.16 GTexel/s are 12% and 12% higher respectively than the K620M’s, favoring workloads with heavy rasterization or multi-sampled anti-aliasing. The four mini-DisplayPort 1.2 outputs give it a clear win for multi-display professional setups, where the K620M’s portable-device-dependent outputs are a limitation. Its Vulkan score of 6496 also suggests it has a more mature or capable Vulkan driver stack, which could be an advantage in emerging Vulkan-based professional applications.

The NVIDIA Quadro K620M wins in raw compute throughput and power efficiency. Its FP32 performance of 863.2 GFLOPS is 33.8% higher than the FirePro’s 645.1 GFLOPS, and this is reflected in its 8% OpenCL victory. The 30 W TDP versus 50 W means it generates less heat and consumes less power, which is critical for thin-and-light mobile workstations where thermal headroom is scarce. Its higher boost clock of 1124 MHz (versus no listed clocks for the AMD part) and the Maxwell architecture’s efficiency per shading unit (863.2 GFLOPS from 384 units versus 645.1 GFLOPS from 512 units) demonstrate a superior compute-per-transistor design. For OpenCL-based compute tasks, which are common in scientific and engineering simulation, the K620M is the data-backed choice. Its nearest rival list includes the AMD Radeon HD 8730M and HD 8750M, placing it in a competitive mobile GPU segment where it outperforms both.