AMD Radeon R7 M350 vs NVIDIA Quadro K620M Comparison

The AMD Radeon R7 M350 and NVIDIA Quadro K620M are both end-of-life mobile graphics solutions from 2015, aimed at very different audiences despite their similar performance class. The data shows the AMD part holds a clear performance lead in the one benchmark where both were tested, but the NVIDIA card brings a different set of trade-offs in power, interface, and API support that may matter more in specific workstation scenarios.

Where Each One Wins

The AMD Radeon R7 M350 wins the only direct benchmark comparison available. In Geekbench OpenCL, it scores 6991 against the Quadro K620M's 5957, a 17.4% advantage. This makes it the stronger choice for any OpenCL-accelerated compute workload, which is the primary metric recorded for both cards.

The NVIDIA Quadro K620M has no benchmark wins in the head-to-head data. Its advantage lies outside raw compute scores. The card's 30 W TDP is explicitly listed, while the AMD card's TDP is not provided — this suggests the Quadro is designed for more power-constrained environments where thermal and battery budgets are tight. Its MXM-A (3.0) bus interface and "Portable Device Dependent" display outputs indicate a modular, laptop-focused design that is more flexible for system integrators.

In terms of percentile ranking, the AMD card sits at the 36th percentile of all GPUs, above the Quadro K620M's 34th percentile. This aligns with the benchmark delta: the AMD part is marginally better positioned in the overall performance distribution.

Architecture Differences

The two cards come from different architectural generations. The AMD Radeon R7 M350 uses the Meso chip built on GCN 3.0 architecture, part of the "Gem System (R7 M300)" generation. The NVIDIA Quadro K620M uses the GM108S chip on Maxwell architecture, from the "Quadro Kepler-M (Kx200M)" generation. Both are fabricated on TSMC's 28 nm process, but the chips differ significantly in size and complexity.

AMD's Meso die measures 125 mm² and packs 1,550 million transistors, resulting in a transistor density of 12.4 million per mm². NVIDIA's GM108S is considerably smaller at 77 mm² with 1,020 million transistors, giving it a higher density of 13.2 million per mm². Despite the smaller die, the NVIDIA chip clocks higher: 1029 MHz base and 1124 MHz boost versus AMD's 1000 MHz base and 1015 MHz boost.

Memory configurations are similar in type but differ in capacity. Both use DDR3 with a 64-bit bus and roughly 16 GB/s bandwidth (16.00 GB/s for AMD, 16.02 GB/s for NVIDIA). The AMD card offers 4 GB of VRAM compared to the Quadro's 2 GB. Both run memory at effectively 2 Gbps effective speed.

Shader counts are identical at 384 shading units, but resource allocation differs. AMD provides 24 texture mapping units (TMUs) versus NVIDIA's 16, while both have 8 raster operation units (ROPs). This explains why AMD's texture rate is 24.36 GTexel/s versus NVIDIA's 17.98 GTexel/s, even though NVIDIA has a slightly higher pixel rate (8.992 GPixel/s vs 8.120 GPixel/s).

Head-to-Head Benchmarks

The sole benchmark result is Geekbench OpenCL, where the AMD Radeon R7 M350 scores 6991 against the Quadro K620M's 5957. The 17.4% delta is substantial for two cards in this class. This margin is larger than the difference between the AMD card and its nearest rivals: it sits just 0.7% above the NVIDIA Quadro K620 (desktop version) and 0.9% above the GeForce RTX 5070 Ti SUPER, which also scores 6270.

The Quadro K620M's score of 5957 places it nearly level with AMD Radeon HD 8730M (5955) and just 0.2% below the HD 8750M (5970). It edges out the Intel UHD Graphics 730 by 0.5%. This puts the NVIDIA card in a crowded mid-low tier, while the AMD card performs closer to professional workstation parts like the Radeon Pro WX 4100 (6330).

Breaking down the compute numbers explains the benchmark gap. AMD's FP32 throughput is 779.5 GFLOPS, and it also supports FP16 at the same rate (779.5 GFLOPS, 1:1). NVIDIA's FP32 is higher at 863.2 GFLOPS, but the data lists no FP16 support. The AMD card's advantage in OpenCL likely comes from its higher texture rate and larger memory buffer, even though its raw FP32 is lower than the Quadro's.

FAQ

Q: Which card is faster in OpenCL compute?

A: The AMD Radeon R7 M350 wins decisively with a Geekbench OpenCL score of 6991 versus 5957 for the NVIDIA Quadro K620M, a 17.4% advantage.

Q: Do both cards support the same graphics APIs?

A: No. AMD supports DirectX 12 (12_0), OpenGL 4.6, and Vulkan 1.2.170. NVIDIA also supports DirectX 12 but at the lower 11_0 feature level, plus OpenGL 4.6 and a newer Vulkan 1.4.

Q: Is the Quadro K620M better for mobile workstations because of its power draw?

A: The data lists the Quadro K620M at 30 W TDP, while the AMD card's TDP is not specified. The NVIDIA card also uses an MXM-A module with no power connectors, suggesting a more power-efficient, modular design.

Q: Which card has more memory?

A: The AMD Radeon R7 M350 has 4 GB of DDR3, double the 2 GB on the NVIDIA Quadro K620M. Both use a 64-bit bus with nearly identical bandwidth (16.00 vs 16.02 GB/s).

Q: How do these cards compare to their closest rivals?

A: The AMD card's average benchmark score of 6327 is 0% from the Radeon Pro WX 4100 (6330) and 0.7% above the desktop Quadro K620 (6282). The NVIDIA card's 5957 average is 0% from the Radeon HD 8730M (5955) and 0.5% above the Intel UHD Graphics 730 (5929).

Q: Which card has better pixel and texture throughput?

A: NVIDIA has a slightly higher pixel rate (8.992 GPixel/s vs 8.120 GPixel/s), but AMD has a much higher texture rate (24.36 GTexel/s vs 17.98 GTexel/s) due to its 24 TMUs versus NVIDIA's 16.

Specification Differences

| Specification | AMD Radeon R7 M350 | NVIDIA Quadro K620M |

|---|---|---|

| Architecture | GCN 3.0 | Maxwell |

| Chip | Meso | GM108S |

| Process Node | 28 nm | 28 nm |

| Transistors | 1,550 million | 1,020 million |

| Die Size | 125 mm² | 77 mm² |

| Base Clock | 1000 MHz | 1029 MHz |

| Boost Clock | 1015 MHz | 1124 MHz |

| Memory Size | 4 GB | 2 GB |

| Memory Type | DDR3 | DDR3 |

| Memory Bus | 64 bit | 64 bit |

| Memory Bandwidth | 16.00 GB/s | 16.02 GB/s |

| TMUs | 24 | 16 |

| ROPs | 8 | 8 |

| Pixel Rate | 8.120 GPixel/s | 8.992 GPixel/s |

| Texture Rate | 24.36 GTexel/s | 17.98 GTexel/s |

| FP32 | 779.5 GFLOPS | 863.2 GFLOPS |

| FP16 | 779.5 GFLOPS (1:1) | Not specified |

| TDP | Not specified | 30 W |

| Slot Width | Not specified | MXM Module |

| Power Connectors | Not specified | None |

| Bus Interface | PCIe 3.0 x8 | MXM-A (3.0) |

| Display Outputs | Not specified | Portable Device Dependent |

| DirectX | 12 (12_0) | 12 (11_0) |

| Vulkan | 1.2.170 | 1.4 |

| Release Date | 2015-05-04 | 2015-02-28 |

| Predecessor | Solar System | Quadro Fermi-M |

| Successor | Polaris Mobile | Quadro Maxwell-M |

The Verdict

The data points to a clear compute winner: the AMD Radeon R7 M350 outperforms the NVIDIA Quadro K620M by 17.4% in OpenCL, offers double the memory (4 GB vs 2 GB), and has a higher texture rate. Its 36th percentile ranking versus the Quadro's 34th confirms the AMD part sits slightly higher in the overall GPU hierarchy. For any task that relies on OpenCL compute or benefits from more VRAM, the R7 M350 is the straightforward choice.

However, the Quadro K620M is not without merit. Its 30 W TDP, MXM-A form factor, and "Portable Device Dependent" outputs make it a more practical option for thin, power-sensitive mobile workstations. Its higher FP32 throughput (863.2 GFLOPS vs 779.5 GFLOPS) and newer Vulkan 1.4 support are also notable, even if they don't translate to a win in the available benchmark. The Maxwell architecture's lower transistor count on a smaller die (77 mm² vs 125 mm²) suggests better efficiency per watt, though the actual TDP for AMD is not listed for direct comparison.

The choice comes down to workload priority. If raw compute performance and memory capacity are the deciding factors, the AMD Radeon R7 M350 wins decisively. If power efficiency, modularity, and a more recent API stack matter more than raw scores, the NVIDIA Quadro K620M is the safer bet for a specific niche. The data does not support calling the Quadro faster in any tested metric — it simply offers different strengths that are not captured in the Geekbench OpenCL run.