NVIDIA RTX A5500 vs NVIDIA Tesla V100 PCIe 16 GB Comparison

# NVIDIA RTX A5500 vs NVIDIA Tesla V100 PCIe 16 GB

The NVIDIA RTX A5500 and NVIDIA Tesla V100 PCIe 16 GB represent two distinct eras of NVIDIA professional computing, with the A5500 built on the Ampere architecture and the V100 on Volta. Benchmark data shows the A5500 holds a decisive overall advantage, winning both head-to-head tests with a substantial margin in Vulkan workloads. The A5500 achieves an average benchmark score of 165,217, placing it in the 97th percentile of all GPUs, while the V100 scores 138,063 on average, sitting in the 96th percentile. These are both high-end workstation and datacenter cards, but the generational gap is clear: the A5500 is 19.7% ahead in average score, and its lead is most pronounced in graphics-oriented tasks rather than pure compute.

Head-to-Head Benchmarks

The two available benchmark comparisons show a consistent winner, but the magnitude of the victory varies significantly by workload. In Geekbench OpenCL, the RTX A5500 scores 174,637 against the Tesla V100’s 163,063, a 7.1% advantage. This is a modest lead, suggesting that in raw compute-oriented OpenCL tasks, the V100’s HBM2 memory and Tensor Core configuration keep it competitive despite its older architecture. The A5500’s higher FP32 throughput (34.10 TFLOPS vs 14.13 TFLOPS) gives it an edge, but the V100’s 897.0 GB/s memory bandwidth versus the A5500’s 768.0 GB/s helps close the gap in memory-bound workloads.

The Vulkan test tells a very different story. The A5500 scores 155,797, while the V100 manages only 113,062 — a 37.8% delta in favor of the Ampere card. This is a massive difference, and it highlights how much the A5500 benefits from its graphics-focused feature set. The V100, designed as a compute accelerator with no display outputs, is not optimized for graphics APIs, and its DirectX 12 (12_1) support lags behind the A5500’s DirectX 12 Ultimate (12_2). For any workload that touches Vulkan or modern graphics pipelines, the A5500 is categorically faster.

The A5500 wins both tests, for a 2-0 record in head-to-head comparisons. The average benchmark score difference of 27,154 points (165,217 vs 138,063) reinforces this dominance, though the V100’s nearest rivals — the Tesla V100 SXM2 32 GB at 137,731 and AMD Instinct MI100 at 139,035 — show that the V100 is still competitive within its own generation. The A5500, meanwhile, sits close to the AMD Radeon PRO W7800 (164,894, only 0.2% behind) and the NVIDIA RTX 4500 Ada Generation (166,094, 0.5% ahead), indicating it is squarely in the middle of the current professional GPU pack.

Where Each One Wins

The RTX A5500 is the clear winner for graphics-inclusive workflows. Its Vulkan score advantage of 37.8% is the single largest gap between the two cards, and its support for DirectX 12 Ultimate (12_2) plus four DisplayPort 1.4a outputs means it can drive displays directly. The V100 has no display outputs at all, making it unsuitable for any interactive graphics work, CAD, or visualization tasks. For rendering, viewport performance, or any API-driven graphics workload, the A5500 is the only rational choice between these two.

The Tesla V100 does have one area of relative strength: memory bandwidth. At 897.0 GB/s, it exceeds the A5500’s 768.0 GB/s by 16.8%, and its 4096-bit HBM2 bus is far wider than the A5500’s 384-bit GDDR6 interface. In pure compute workloads that are memory-bandwidth limited — such as certain scientific simulations or large matrix operations — the V100’s bandwidth advantage can partially offset its lower raw compute throughput. However, the V100’s FP32 performance is only 14.13 TFLOPS compared to the A5500’s 34.10 TFLOPS, so the A5500 still wins most compute tasks outright. The V100’s FP16 performance of 28.26 TFLOPS (2:1 ratio) is closer to the A5500’s 34.10 TFLOPS (1:1), and with 640 Tensor Cores versus the A5500’s 320, the V100 can be competitive in mixed-precision AI inference workloads, though the A5500’s newer Tensor Core design may offer better efficiency.

For users who need PCIe 4.0 connectivity, the A5500 is the winner, as the V100 is limited to PCIe 3.0. The A5500 also has a lower TDP at 230 W versus 300 W, and requires only a single 8-pin power connector compared to the V100’s two 8-pin connectors, along with a lower suggested PSU of 550 W versus 700 W. This makes the A5500 easier to integrate into existing systems from a power delivery standpoint.

Architecture Differences

The architectural gap between these two GPUs is substantial. The RTX A5500 uses the GA102 chip built on Samsung’s 8 nm process, while the Tesla V100 uses the GV100 chip on TSMC’s 12 nm node. The A5500 packs 28,300 million transistors into a 628 mm² die, achieving a transistor density of 45.1 million per mm². The V100 has 21,100 million transistors on a larger 815 mm² die, with a density of just 25.9 million per mm². This density advantage is a direct result of the newer process node, allowing the A5500 to fit more compute units in less space.

The A5500 has 10,240 shading units, 320 TMUs, and 96 ROPs, while the V100 has 5,120 shading units, 320 TMUs, and 128 ROPs. The A5500 doubles the shader count but has fewer ROPs, which is a reflection of its graphics-oriented design. Pixel rates are similar — 159.8 GPixel/s for the A5500 and 176.6 GPixel/s for the V100 — but the A5500’s texture rate of 532.8 GTexel/s beats the V100’s 441.6 GTexel/s by 20.6%.

Ray tracing is a major differentiator. The A5500 includes 80 RT cores, while the V100 has none. This means the A5500 supports hardware-accelerated ray tracing, a feature entirely absent from the V100. Tensor Core counts differ as well: the V100 has 640 Tensor Cores, double the A5500’s 320, but the A5500’s Tensor Cores are from a newer generation and support the 1:1 FP16 ratio, whereas the V100’s FP16 is 2:1, indicating a different execution model.

Memory architecture is also fundamentally different. The A5500 uses 24 GB of GDDR6 on a 384-bit bus, while the V100 uses 16 GB of HBM2 on a 4096-bit bus. The V100’s memory bandwidth is higher at 897.0 GB/s versus 768.0 GB/s, but the A5500 has 50% more capacity. The A5500’s memory runs at 2000 MHz (16 Gbps effective), while the V100’s runs at 876 MHz (1752 Mbps effective). Clock speeds favor the A5500 on boost (1665 MHz vs 1380 MHz) but the V100 has a higher base clock (1245 MHz vs 1080 MHz).

FAQ

Q: Which GPU is faster in Vulkan benchmarks?

A: The NVIDIA RTX A5500 is significantly faster, scoring 155,797 versus the Tesla V100’s 113,062, a 37.8% advantage.

Q: Does the Tesla V100 support ray tracing?

A: No. The V100 has no RT cores, while the RTX A5500 includes 80 RT cores for hardware-accelerated ray tracing.

Q: How do their memory capacities and bandwidths compare?

A: The A5500 has 24 GB of GDDR6 with 768.0 GB/s bandwidth on a 384-bit bus. The V100 has 16 GB of HBM2 with 897.0 GB/s bandwidth on a 4096-bit bus. The V100 has 16.8% more bandwidth, but the A5500 has 50% more capacity.

Q: Which card has better FP32 compute performance?

A: The RTX A5500 delivers 34.10 TFLOPS of FP32 performance, which is 2.4 times the V100’s 14.13 TFLOPS.

Q: Are there differences in display output capability?

A: Yes. The A5500 has four DisplayPort 1.4a outputs, while the V100 has no display outputs at all, making it a compute-only accelerator.

Q: What are the power requirements for each card?

A: The A5500 has a 230 W TDP with a single 8-pin connector and a 550 W suggested PSU. The V100 has a 300 W TDP with two 8-pin connectors and a 700 W suggested PSU.

Specification Differences

| Specification | NVIDIA RTX A5500 | NVIDIA Tesla V100 PCIe 16 GB |

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

| Architecture | Ampere | Volta |

| Process Node | 8 nm (Samsung) | 12 nm (TSMC) |

| Transistors | 28,300 million | 21,100 million |

| Die Size | 628 mm² | 815 mm² |

| Transistor Density | 45.1M / mm² | 25.9M / mm² |

| Base Clock | 1080 MHz | 1245 MHz |

| Boost Clock | 1665 MHz | 1380 MHz |

| Memory Size | 24 GB | 16 GB |

| Memory Type | GDDR6 | HBM2 |

| Memory Bus Width | 384 bit | 4096 bit |

| Memory Bandwidth | 768.0 GB/s | 897.0 GB/s |

| Shading Units | 10240 | 5120 |

| ROPs | 96 | 128 |

| RT Cores | 80 | 0 |

| Tensor Cores | 320 | 640 |

| FP32 Performance | 34.10 TFLOPS | 14.13 TFLOPS |

| FP16 Performance | 34.10 TFLOPS (1:1) | 28.26 TFLOPS (2:1) |

| TDP | 230 W | 300 W |

| Power Connectors | 1x 8-pin | 2x 8-pin |

| Suggested PSU | 550 W | 700 W |

| Bus Interface | PCIe 4.0 x16 | PCIe 3.0 x16 |

| Display Outputs | 4x DisplayPort 1.4a | None |

| DirectX Support | 12 Ultimate (12_2) | 12 (12_1) |

| Release Date | 2022-03-21 | 2017-06-20 |

| Pixel Rate | 159.8 GPixel/s | 176.6 GPixel/s |

| Texture Rate | 532.8 GTexel/s | 441.6 GTexel/s |

The Verdict

The data is unambiguous: the NVIDIA RTX A5500 is the better GPU for nearly every use case. It wins both benchmark tests, offers a 19.7% higher average benchmark score, delivers more than double the FP32 compute performance, has 50% more memory, supports ray tracing, includes display outputs, and uses less power. The V100’s only meaningful advantages are higher memory bandwidth (897 vs 768 GB/s) and more Tensor Cores (640 vs 320), which matter only in specific narrow workloads.

For professionals who need a card that can handle graphics, rendering, or any interactive task, the A5500 is the only choice between these two — the V100 cannot even output video. For compute-focused users, the A5500’s superior FP32 and FP16 performance (34.10 TFLOPS in both, versus the V100’s 14.13 and 28.26 TFLOPS) makes it faster in most workloads, despite the V100’s bandwidth edge. The V100’s higher memory bandwidth could help in memory-bound scientific computing, but the A5500’s 24 GB capacity and newer architecture are more versatile.

The A5500’s nearest rivals — the AMD Radeon PRO W7800 (0.2% behind) and NVIDIA RTX 4500 Ada Generation (0.5% ahead) — show it is well-positioned in the current market. The V100, meanwhile, sits near the AMD Instinct MI100 (0.7% behind) and Tesla V100 SXM2 32 GB (0.2% behind), indicating it is competitive only within its own generation. Given the 2022 release date of the A5500 versus 2017 for the V100, the five-year architectural leap is evident in every benchmark and specification. For any new deployment, the RTX A5500 is the recommended purchase; the Tesla V100 is only worth considering if you have a specific need for its HBM2 bandwidth and already have a system built around its PCIe 3.0 and 2x 8-pin power requirements.