NVIDIA A10G vs NVIDIA Tesla V100 SXM2 16 GB Comparison

The data is unambiguous: the NVIDIA A10G is the superior card in this pairing, winning both head-to-head benchmarks and holding a commanding lead in average benchmark score. It is the clear choice for any workload where raw compute throughput, modern feature support, and higher memory capacity are paramount. The NVIDIA Tesla V100 SXM2 16 GB, while an older and less powerful part, still holds relevance in specific scenarios where its high-bandwidth HBM2 memory and massive tensor core count provide a legacy advantage, though the benchmark data does not show it winning any of the tested workloads.

The Verdict

The NVIDIA A10G is the definitive winner based on the provided data. Its average benchmark score of 151,963 places it in the 97th percentile of all GPUs, a full 37,568 points ahead of the Tesla V100 SXM2's average of 114,395. This is not a marginal difference; it represents a fundamental generational leap in computational power. In the Geekbench OpenCL test, the A10G's advantage is massive, scoring 158,063 against the V100's 87,454, an 80.7% delta. This indicates that for general-purpose compute and workloads that leverage OpenCL, the A10G is in a different performance class entirely.

The Tesla V100 SXM2, despite its 95th percentile ranking, is decisively outpaced. Its only competitive showing is in the Vulkan benchmark, where it scores 141,336 against the A10G's 145,863, a narrow 3.2% margin. This suggests that in API-specific or legacy software paths, the V100 can still hold its own, but it cannot overcome the A10G's overall superiority. For any buyer choosing between these two for a new deployment, the A10G is the only logical pick based on performance data alone. The V100 is a card for specific, niche applications or for systems already built around its SXM2 form factor.

Where Each One Wins

The A10G wins decisively in overall compute performance. Its victory in the OpenCL benchmark is the headline, but its 97th percentile ranking versus the V100's 95th reinforces its position as the higher-performing part in the database's aggregate view. The A10G also posts a win in Vulkan, the only other benchmark tested. Its two wins out of two head-to-head tests show broad applicability across different software interfaces.

The Tesla V100 SXM2's theoretical advantages do not translate to benchmark victories here. While it has a higher pixel rate (195.8 GPixel/s vs 164.2 GPixel/s) and texture rate (489.6 GTexel/s vs 492.5 GTexel/s, which is nearly identical), these do not lead to wins in the tests conducted. Its area of theoretical strength lies in memory bandwidth; its 897.0 GB/s of HBM2 bandwidth is significantly higher than the A10G's 600.2 GB/s. However, the data shows that in the two benchmarks performed, this bandwidth advantage did not manifest into a performance win. The V100's single "win" is in the specification sheet, not the benchmark results. It is the better choice only for a system that requires the SXM2 module form factor, as the A10G uses a standard single-slot PCIe design.

Architecture Differences

The A10G is built on the modern Ampere architecture, utilizing the GA102 chip manufactured on Samsung's 8 nm process. This is a stark contrast to the V100's Volta architecture, which uses the GV100 chip on TSMC's 12 nm process. The A10G is a newer, denser design, packing 28,300 million transistors into a 628 mm² die, achieving a transistor density of 45.1M per mm². The V100, by comparison, has 21,100 million transistors on a larger 815 mm² die, for a density of only 25.9M per mm². This density advantage is a key reason for the A10G's superior performance.

The compute architectures diverge significantly. The A10G has 9,216 shading units, 288 TMUs, and 96 ROPs. It also features 72 dedicated ray tracing cores and 288 tensor cores. The V100 has 5,120 shading units, 320 TMUs, and 128 ROPs, but no ray tracing cores. It does have a higher count of 640 tensor cores. The FP32 compute throughput tells the story: the A10G delivers 31.52 TFLOPS, exactly double the V100's 15.67 TFLOPS. In FP16, the A10G again delivers 31.52 TFLOPS (1:1 ratio), while the V100 achieves a comparable 31.33 TFLOPS, but only via a 2:1 ratio, meaning it processes two FP16 operations per clock to reach that number. This indicates the A10G is far more efficient and powerful for standard single-precision workloads.

Memory architecture is another major differentiator. The A10G uses 24 GB of GDDR6 memory on a 384-bit bus, while the V100 uses 16 GB of HBM2 on a massive 4096-bit bus. This gives the V100 a significant bandwidth advantage (897.0 GB/s vs 600.2 GB/s) but the A10G counters with 50% more capacity. The A10G also boasts a higher boost clock of 1710 MHz compared to the V100's 1530 MHz. In terms of connectivity, the A10G uses the newer PCIe 4.0 x16 interface, while the V100 is limited to PCIe 3.0 x16. The A10G supports DirectX 12 Ultimate, while the V100 is capped at DirectX 12 (12_1).

FAQ

Q: Which GPU has the higher average benchmark score?

A: The NVIDIA A10G has a significantly higher average benchmark score of 151,963, placing it in the 97th percentile, compared to the Tesla V100 SXM2's 114,395 score in the 95th percentile.

Q: How much faster is the A10G in the Geekbench OpenCL test?

A: The A10G scores 158,063 in Geekbench OpenCL, which is 80.7% higher than the V100 SXM2's score of 87,454.

Q: Does the Tesla V100 SXM2 win any benchmark?

A: Based on the head-to-head benchmark data, the V100 SXM2 does not win any tests. The A10G wins both the OpenCL and Vulkan benchmarks.

Q: What is the key difference in memory capacity?

A: The A10G offers 24 GB of GDDR6 memory, which is 50% more capacity than the 16 GB of HBM2 memory found on the V100 SXM2.

Q: Which GPU has more tensor cores?

A: The Tesla V100 SXM2 has more tensor cores, with 640, compared to the 288 tensor cores on the A10G. However, the A10G's newer architecture delivers higher FP32 and comparable FP16 throughput.

Q: What are the main architectural differences?

A: The A10G uses the Ampere architecture on an 8 nm process with a GA102 chip, while the V100 uses the older Volta architecture on a 12 nm process with a GV100 chip. The A10G also supports PCIe 4.0 and DirectX 12 Ultimate, whereas the V100 is limited to PCIe 3.0 and DirectX 12 (12_1).

Head-to-Head Benchmarks

The most striking result is in the Geekbench OpenCL test. The A10G achieves a score of 158,063, while the V100 SXM2 trails far behind at 87,454. This is an 80.7% difference, demonstrating a generational gap in raw compute power that is not reflected in any other metric. This result alone should be the deciding factor for any compute-intensive application that relies on OpenCL.

The second test, Geekbench Vulkan, is a much closer contest. The A10G still wins, but by a slim margin of 3.2%, scoring 145,863 against the V100's 141,336. This shows that the V100's architecture is still competitive in certain graphics or compute APIs, but it is not enough to overcome the A10G's overall performance lead. The aggregate data reinforces this, with the A10G's average score being 32.9% higher than the V100's. The A10G wins 2 out of 2 benchmarks, leaving no doubt as to which is the faster card in practice.

Specification Differences

The two cards differ across nearly every core specification. The A10G leads in process node (8 nm vs 12 nm), transistor density (45.1M / mm² vs 25.9M / mm²), base clock (1320 MHz vs 1312 MHz), and boost clock (1710 MHz vs 1530 MHz). It also has more shading units (9216 vs 5120) and TMUs (288 vs 320, where the V100 has more) and ROPs (96 vs 128, where the V100 has more).

The A10G has a higher FP32 performance at 31.52 TFLOPS, double the V100's 15.67 TFLOPS. It also has more memory (24 GB vs 16 GB) and a newer bus interface (PCIe 4.0 vs 3.0). The V100 counter-attacks with a wider memory bus (4096-bit vs 384-bit), higher memory bandwidth (897.0 GB/s vs 600.2 GB/s), more tensor cores (640 vs 288), and a higher pixel rate (195.8 GPixel/s vs 164.2 GPixel/s). The TDP is another major point of difference, with the A10G drawing 150 W compared to the V100's 250 W, making the A10G significantly more power-efficient. The A10G is a single-slot card with an 8-pin EPS connector, while the V100 is an SXM module with no power connectors. The A10G is also the newer product, with a release date in 2021, while the V100 was released in 2017.