NVIDIA A100 PCIe 80 GB vs NVIDIA A10M Comparison

The data places the NVIDIA A100 PCIe 80 GB and the NVIDIA A10M in the same server-class Ampere family, but the benchmark results show a decisive performance gap. In the sole head-to-head Geekbench OpenCL test, the A100 scores 207,124 against the A10M’s 135,230, a 53.2% delta. The A100 ranks in the 99th percentile of all GPUs, while the A10M sits in the 96th percentile. For workloads measured by this test, the A100 is the clear choice, but the A10M’s lower power draw and single-slot design make it the alternative for density-constrained deployments where peak compute is secondary.

The Verdict

The NVIDIA A100 PCIe 80 GB wins the only benchmark shared between the two cards, and it wins by a large margin. Its Geekbench OpenCL score of 207,124 is 53.2% higher than the A10M’s 135,230. The A100 also holds a stronger position against its own nearest rivals, sitting 5.7% above the NVIDIA RTX 6000D and 6.5% above the NVIDIA Tesla V100S PCIe 32 GB, while trailing the AMD Radeon PRO W7900D by 5.8% and the NVIDIA PG506-232 by 8%. The A10M, by contrast, is virtually tied with its nearest competitors: 0% from the NVIDIA RTX 4000 Ada Generation, -0.1% from the AMD Radeon PRO W6800, -0.4% from the AMD Radeon Pro W6800X Duo, and -0.9% from the AMD Radeon PRO V620.

From the data, the A100 is the pick for any user prioritizing raw compute throughput in a single card. It delivers a 53.2% advantage in the measured workload, which is a decisive gap. The A10M should be chosen only when its physical and power profile matters more than performance: it draws 150 W versus the A100’s 300 W, and it occupies a single slot rather than a dual-slot footprint. Both cards have identical 267 mm lengths and similar heights (111 mm for the A100, 112 mm for the A10M), but the A10M’s lower power requirement means a suggested PSU of 450 W versus 700 W for the A100. If the deployment has strict power or space limits, the A10M is the data-backed fallback, acknowledging a 53.2% performance sacrifice.

Architecture Differences

Both processors are built on NVIDIA’s Ampere architecture and belong to the Server Ampere (Axx) generation, but they are fundamentally different chips. The A100 uses the GA100 die, fabricated on a 7 nm TSMC process, while the A10M uses the GA102 die, fabricated on an 8 nm Samsung process. The A100 packs 54,200 million transistors into an 826 mm² die, yielding a transistor density of 65.6 million per mm². The A10M contains 28,300 million transistors on a 628 mm² die, for a density of 45.1 million per mm². The A100’s larger, denser chip reflects its data-center compute focus.

Memory architecture diverges sharply. The A100 carries 80 GB of HBM2e on a 5120-bit bus, delivering 1.94 TB/s of bandwidth. The A10M has 20 GB of GDDR6 on a 320-bit bus, yielding 500.2 GB/s. That is a 3.88x bandwidth advantage for the A100, which matters for memory-bound workloads. The A100’s memory clock is listed at 1512 MHz with 3 Gbps effective, while the A10M runs 1563 MHz with 12.5 Gbps effective, but the bus width difference overwhelms the clock speeds.

Compute resources also differ in configuration. The A100 has 6912 shading units, 432 TMUs, 160 ROPs, and 432 tensor cores, with no dedicated RT cores listed. The A10M has 7168 shading units, 224 TMUs, 80 ROPs, 224 tensor cores, and 56 RT cores. The A10M has more shading units but half the TMUs, half the ROPs, and roughly half the tensor cores. The A100’s FP32 throughput is 19.49 TFLOPS, lower than the A10M’s 23.44 TFLOPS, but the A100’s FP16 performance is 77.97 TFLOPS at a 4:1 ratio, versus the A10M’s 23.44 TFLOPS at a 1:1 ratio. The A100’s FP16 advantage is 3.33x, a critical factor for AI and deep learning inference.

Head-to-Head Benchmarks

The only direct comparison available is Geekbench OpenCL, and the A100 dominates. The A100 scores 207,124, while the A10M scores 135,230. The delta is 53.2%, meaning the A100 is more than half again as fast as the A10M in this test. Contextualizing against rivals, the A100’s score places it comfortably above the RTX 6000D (195,964, 5.7% slower) and Tesla V100S (194,415, 6.5% slower), while the A10M’s score is almost identical to the RTX 4000 Ada Generation (135,218, 0% delta) and slightly below the Radeon PRO W6800 (135,396, -0.1%).

The A100’s win is consistent with its hardware profile. Its 1.94 TB/s memory bandwidth is nearly 4x the A10M’s 500.2 GB/s, and its FP16 tensor throughput of 77.97 TFLOPS dwarfs the A10M’s 23.44 TFLOPS. Even in FP32, where the A10M leads (23.44 TFLOPS vs 19.49 TFLOPS), the A100’s advantage in memory and specialized cores appears to carry the OpenCL workload. The A10M’s higher boost clock (1635 MHz vs 1410 MHz) and greater shading unit count (7168 vs 6912) do not compensate for the memory bandwidth deficit in this test.

There are no other benchmark results in the data, so the 53.2% figure stands as the singular quantitative comparison. The A100 wins the only metric that exists, and it wins by a margin that dwarfs the A10M’s closest rival deltas.

FAQ

Q: Which GPU has higher memory bandwidth?

A: The NVIDIA A100 PCIe 80 GB, with 1.94 TB/s from HBM2e memory on a 5120-bit bus. The A10M’s GDDR6 memory on a 320-bit bus provides 500.2 GB/s, a 3.88x gap.

Q: Does the A10M have any compute advantage over the A100?

A: Yes, in raw FP32 throughput. The A10M delivers 23.44 TFLOPS versus the A100’s 19.49 TFLOPS. The A10M also has more shading units (7168 vs 6912) and a higher boost clock (1635 MHz vs 1410 MHz).

Q: How do their tensor core counts compare?

A: The A100 has 432 tensor cores, while the A10M has 224. In FP16 compute, the A100 reaches 77.97 TFLOPS (4:1 ratio) versus the A10M’s 23.44 TFLOPS (1:1 ratio).

Q: Which card is better for a single-slot installation?

A: The A10M is a single-slot card. The A100 is dual-slot. Both share the same 267 mm length, but the A10M’s 150 W TDP and 450 W suggested PSU make it far easier to fit in constrained chassis.

Q: What is the performance difference in the measured benchmark?

A: In Geekbench OpenCL, the A100 scores 207,124 versus the A10M’s 135,230, a 53.2% advantage for the A100. The A10M’s score is within 0.9% of its nearest rivals, while the A100 sits 5.7-6.5% above two of its rivals.

Q: Do both cards support the same graphics APIs?

A: No. The A10M lists DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4 support. The A100 has no listed API support for DirectX, OpenGL, or Vulkan, reflecting its compute-only orientation.

Where Each One Wins

The A100 wins the only benchmark in the data, taking the Geekbench OpenCL test by 53.2%. Its strengths are memory bandwidth (1.94 TB/s vs 500.2 GB/s), FP16 throughput (77.97 TFLOPS vs 23.44 TFLOPS), and tensor core count (432 vs 224). It also has double the VRAM (80 GB vs 20 GB) and a wider memory bus (5120-bit vs 320-bit). For workloads that stress memory capacity or bandwidth—large model inference, training datasets, or high-resolution tensor operations—the A100 is the data-backed winner. Its 99th percentile ranking among all GPUs reinforces this.

The A10M wins on power efficiency and physical footprint. It draws 150 W versus the A100’s 300 W, and it fits in a single slot versus the A100’s dual-slot design. The suggested PSU is 450 W versus 700 W. It also has a higher FP32 rating (23.44 TFLOPS vs 19.49 TFLOPS) and more shading units (7168 vs 6912), which could favor certain FP32-heavy workloads, though the only measured test does not support that. The A10M’s API support (DirectX 12 Ultimate, OpenGL 4.6, Vulkan 1.4) gives it a functional edge in environments requiring those interfaces, whereas the A100 has no listed graphics API support. The A10M’s 96th percentile ranking still places it above most GPUs, but its nearest rivals are all within 0.9%, indicating it is at parity with its class.

Specification Differences

| Field | NVIDIA A100 PCIe 80 GB | NVIDIA A10M |

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

| Chip | GA100 | GA102 |

| Process Node | 7 nm (TSMC) | 8 nm (Samsung) |

| Transistors | 54,200 million | 28,300 million |

| Die Size | 826 mm² | 628 mm² |

| Transistor Density | 65.6M / mm² | 45.1M / mm² |

| Base Clock | 1065 MHz | 975 MHz |

| Boost Clock | 1410 MHz | 1635 MHz |

| Memory Clock | 1512 MHz (3 Gbps effective) | 1563 MHz (12.5 Gbps effective) |

| Memory Size | 80 GB HBM2e | 20 GB GDDR6 |

| Memory Bus | 5120 bit | 320 bit |

| Memory Bandwidth | 1.94 TB/s | 500.2 GB/s |

| Shading Units | 6912 | 7168 |

| TMUs | 432 | 224 |

| ROPs | 160 | 80 |

| RT Cores | Not listed | 56 |

| Tensor Cores | 432 | 224 |

| Pixel Rate | 225.6 GPixel/s | 130.8 GPixel/s |

| Texture Rate | 609.1 GTexel/s | 366.2 GTexel/s |

| FP32 | 19.49 TFLOPS | 23.44 TFLOPS |

| FP16 | 77.97 TFLOPS (4:1) | 23.44 TFLOPS (1:1) |

| TDP | 300 W | 150 W |

| Slot Width | Dual-slot | Single-slot |

| Suggested PSU | 700 W | 450 W |

| Display Outputs | No outputs | No outputs |

| DirectX | Not listed | 12 Ultimate (12_2) |

| OpenGL | Not listed | 4.6 |

| Vulkan | Not listed | 1.4 |

| Height | 111 mm (4.4 inches) | 112 mm (4.4 inches) |

| Release Date | 2021-06-27 | Not listed |

| Geekbench OpenCL | 207,124 | 135,230 |

| Percentile | 99 | 96 |