NVIDIA A100 PCIe 40 GB vs NVIDIA A10M Comparison

The NVIDIA A100 PCIe 40 GB and the NVIDIA A10M are both server-oriented Ampere architecture GPUs, but benchmark data shows they occupy distinct performance tiers. The A100 PCIe 40 GB delivers a significantly higher average benchmark score of 162,504 compared to the A10M’s 135,230, a gap of approximately 20%. In the single head-to-head benchmark available, the A100 PCIe 40 GB wins the Geekbench OpenCL test decisively, scoring 178,627 against the A10M’s 135,230, a 32.1% advantage. The data indicates the A100 PCIe 40 GB is the superior choice for raw compute throughput, while the A10M offers a lower-power alternative with different architectural strengths.

The Verdict

The benchmark results are unequivocal: the NVIDIA A100 PCIe 40 GB is the faster GPU. Its Geekbench OpenCL score of 178,627 places it 32.1% ahead of the A10M’s 135,230 in the only direct comparison available. This performance advantage is also reflected in their overall standings; the A100 PCIe 40 GB sits at the 97th percentile among all GPUs, while the A10M ranks at the 96th percentile. The A100 PCIe 40 GB’s average benchmark score of 162,504 is substantially higher than the A10M’s 135,230, reinforcing its position as the more capable compute card.

However, the A10M is not without its own merits. Its boost clock of 1635 MHz is higher than the A100 PCIe 40 GB’s 1410 MHz, and it features a larger number of shading units (7168 versus 6912). The A10M also includes 56 ray tracing cores, a feature entirely absent from the A100 PCIe 40 GB. Furthermore, the A10M has a lower TDP of 150 W compared to the A100 PCIe 40 GB’s 250 W, and it occupies a single slot instead of dual slots. The A10M is the appropriate choice for environments where power efficiency, physical footprint, or ray tracing capability takes precedence over peak compute performance.

For users prioritizing maximum FP32 compute, memory bandwidth, or overall benchmark scores, the A100 PCIe 40 GB is the clear winner. The data shows a 32.1% lead in the OpenCL test, a 1.56 TB/s memory bandwidth versus 500.2 GB/s, and a higher texture rate of 609.1 GTexel/s against 366.2 GTexel/s. The A10M, by contrast, wins on architectural features like ray tracing support and a higher boost clock, making it suitable for workloads that leverage those specific capabilities. Strictly from the data, the A100 PCIe 40 GB is the performance pick, while the A10M serves a niche for lower-power, single-slot deployments with RT core needs.

FAQ

Q: Which GPU has a higher average benchmark score?

A: The NVIDIA A100 PCIe 40 GB has an average benchmark score of 162,504, which is significantly higher than the NVIDIA A10M’s average score of 135,230.

Q: How large is the performance difference in the head-to-head OpenCL benchmark?

A: In the Geekbench OpenCL test, the A100 PCIe 40 GB scored 178,627 versus the A10M’s 135,230, resulting in a 32.1% advantage for the A100 PCIe 40 GB.

Q: Does the A10M support ray tracing?

A: Yes, the NVIDIA A10M includes 56 ray tracing cores. The NVIDIA A100 PCIe 40 GB does not list any ray tracing cores in its specifications.

Q: What are the memory capacities and types of these two GPUs?

A: The A100 PCIe 40 GB has 40 GB of HBM2e memory with a 5120-bit bus, while the A10M has 20 GB of GDDR6 memory on a 320-bit bus.

Q: Which GPU has a higher boost clock speed?

A: The NVIDIA A10M has a boost clock of 1635 MHz, which is higher than the A100 PCIe 40 GB’s boost clock of 1410 MHz.

Q: What is the TDP difference between the two cards?

A: The A100 PCIe 40 GB has a TDP of 250 W and requires a suggested 600 W power supply, whereas the A10M has a TDP of 150 W and a suggested 450 W power supply.

Architecture Differences

The two GPUs are built on the same Ampere architecture but use entirely different chips and manufacturing processes. The NVIDIA A100 PCIe 40 GB is based on the GA100 chip, fabricated on a 7 nm process at TSMC. This chip contains 54,200 million transistors on an 826 mm² die, yielding a transistor density of 65.6 million transistors per square millimeter. In contrast, the NVIDIA A10M uses the GA102 chip, built on an 8 nm process at Samsung. The GA102 contains 28,300 million transistors on a 628 mm² die, resulting in a lower transistor density of 45.1 million per square millimeter. The A100 PCIe 40 GB’s use of a more advanced process node and a larger, denser chip explains its significant lead in memory bandwidth and compute throughput.

The compute core configurations differ markedly between the two. The A100 PCIe 40 GB features 6912 shading units, 432 texture mapping units (TMUs), and 160 raster output units (ROPs). It also includes 432 tensor cores but no ray tracing cores. The A10M, on the other hand, has 7168 shading units, 224 TMUs, and 80 ROPs. It includes 224 tensor cores and 56 ray tracing cores, making it the only one of the two with RT support. The A100 PCIe 40 GB’s higher TMU and ROP counts align with its superior texture rate of 609.1 GTexel/s and pixel rate of 225.6 GPixel/s, compared to the A10M’s 366.2 GTexel/s and 130.8 GPixel/s.

Memory architecture is another fundamental divergence. The A100 PCIe 40 GB uses 40 GB of HBM2e memory with a 5120-bit bus, providing a massive 1.56 TB/s of bandwidth. The A10M uses 20 GB of GDDR6 memory on a 320-bit bus, yielding 500.2 GB/s of bandwidth. This threefold difference in memory bandwidth is a key reason the A100 PCIe 40 GB outperforms the A10M in memory-intensive workloads. The A100 PCIe 40 GB also has a lower base clock of 765 MHz and boost clock of 1410 MHz, while the A10M operates at a higher 975 MHz base and 1635 MHz boost. Despite the A10M’s higher clocks, the A100 PCIe 40 GB’s architectural advantages in memory and texture throughput give it the overall performance edge.

Specification Differences

The specification sheets for the two GPUs show several direct differences. The most obvious is the process node: the A100 PCIe 40 GB is built on 7 nm, while the A10M uses 8 nm. This leads to different transistor counts and die sizes, with the A100 PCIe 40 GB having 54,200 million transistors on an 826 mm² die, versus the A10M’s 28,300 million transistors on a 628 mm² die. The memory subsystems are entirely different, with the A100 PCIe 40 GB offering 40 GB of HBM2e on a 5120-bit bus with 1.56 TB/s bandwidth, while the A10M offers 20 GB of GDDR6 on a 320-bit bus with 500.2 GB/s bandwidth.

Clock speeds also differ. The A100 PCIe 40 GB runs at a base clock of 765 MHz and boosts to 1410 MHz, with memory at 1215 MHz (2.4 Gbps effective). The A10M runs at a base clock of 975 MHz and boosts to 1635 MHz, with memory at 1563 MHz (12.5 Gbps effective). The compute unit counts are different as well: the A100 PCIe 40 GB has 6912 shading units, 432 TMUs, 160 ROPs, and 432 tensor cores; the A10M has 7168 shading units, 224 TMUs, 80 ROPs, 224 tensor cores, and 56 ray tracing cores. The A100 PCIe 40 GB has no RT cores listed, while the A10M supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4; the A100 PCIe 40 GB has no API data listed.

Power and physical specifications also separate the two. The A100 PCIe 40 GB has a TDP of 250 W with a suggested 600 W power supply, while the A10M has a TDP of 150 W with a suggested 450 W power supply. The A100 PCIe 40 GB is dual-slot, whereas the A10M is single-slot. Both use an 8-pin EPS power connector and have no display outputs. Their dimensions are nearly identical, with the A100 PCIe 40 GB measuring 267 mm in length and 111 mm in height, and the A10M measuring 267 mm in length and 112 mm in height. Both are end-of-life products with the same predecessor (Tesla Turing) and successor (Server Ada).

Head-to-Head Benchmarks

The only direct benchmark comparison available is the Geekbench OpenCL test, where the NVIDIA A100 PCIe 40 GB outperforms the NVIDIA A10M by a substantial margin. The A100 PCIe 40 GB scored 178,627, while the A10M scored 135,230. This represents a 32.1% performance advantage for the A100 PCIe 40 GB, a significant gap that underscores its superior compute capability. In this test, the A100 PCIe 40 GB is the clear winner, and the data shows no benchmark where the A10M comes out ahead.

Looking at the broader benchmark context, the A100 PCIe 40 GB also appears in a Geekbench Vulkan test with a score of 146,380, though no comparable Vulkan score exists for the A10M. The average benchmark scores further illustrate the gap: the A100 PCIe 40 GB averages 162,504 across its two benchmark entries, while the A10M’s single benchmark gives it an average of 135,230. The A100 PCIe 40 GB’s nearest rivals in the database include the NVIDIA RTX 4500 Ada Generation (avg score 166,094, delta -2.2%) and the NVIDIA RTX A5500 (avg score 165,217, delta -1.6%), showing it is competitive with newer Ada-generation cards. The A10M’s nearest rival is the NVIDIA RTX 4000 Ada Generation, which scores 135,218, a near-identical match with a 0% delta.

The performance differential in the OpenCL test aligns with the raw specification advantages of the A100 PCIe 40 GB. Its memory bandwidth of 1.56 TB/s is over three times that of the A10M’s 500.2 GB/s, and its texture rate of 609.1 GTexel/s is 66% higher than the A10M’s 366.2 GTexel/s. Even though the A10M has a higher boost clock and more shading units, the A100 PCIe 40 GB’s architectural efficiency and memory subsystem dominate in this compute-oriented benchmark. The data consistently points to the A100 PCIe 40 GB as the stronger performer in head-to-head testing.

Where Each One Wins

The NVIDIA A100 PCIe 40 GB wins decisively in raw compute performance. Its Geekbench OpenCL score of 178,627 is 32.1% higher than the A10M’s 135,230, and its average benchmark score of 162,504 versus 135,230 confirms its overall superiority. The A100 PCIe 40 GB excels in workloads that demand high memory bandwidth, given its 1.56 TB/s HBM2e memory, and high texture throughput, with a 609.1 GTexel/s rate. It also has a higher pixel rate of 225.6 GPixel/s and more TMUs (432 versus 224) and ROPs (160 versus 80). For FP32 compute, the A100 PCIe 40 GB delivers 19.49 TFLOPS, while the A10M delivers 23.44 TFLOPS; however, the A100 PCIe 40 GB’s FP16 performance of 77.97 TFLOPS (4:1) dwarfs the A10M’s 23.44 TFLOPS (1:1). The A100 PCIe 40 GB is the pick for AI training, scientific simulation, and any task where memory bandwidth and parallel FP16 throughput are critical.

The NVIDIA A10M, while losing the overall benchmark battle, has specific advantages that make it the better choice in certain scenarios. Its 56 ray tracing cores provide hardware support for RT workloads, a feature the A100 PCIe 40 GB lacks entirely. Its higher boost clock of 1635 MHz and larger shading unit count of 7168 give it a slight edge in pure FP32 throughput at 23.44 TFLOPS, which could benefit workloads that rely on single-precision math without needing massive memory bandwidth. The A10M also has a significantly lower TDP of 150 W versus 250 W, and it fits in a single slot, making it more suitable for dense server deployments with power or space constraints. The A10M’s suggested power supply of 450 W is also lower than the A100 PCIe 40 GB’s 600 W requirement.

In summary, the A100 PCIe 40 GB is the winner for maximum performance, particularly in memory-intensive and FP16-heavy workloads, as evidenced by its 32.1% lead in the OpenCL benchmark. The A10M is the winner for ray tracing support, lower power consumption, and a higher boost clock, making it a viable option for edge inference or visualization tasks where those features matter more than peak compute. The benchmark data shows one clear performance victor, but the A10M’s architectural features carve out a distinct niche that the A100 PCIe 40 GB cannot fill.