NVIDIA A10G vs NVIDIA RTX A5500 Mobile Comparison

# Head-to-Head Benchmarks

The benchmark data presents a clear picture: the NVIDIA A10G wins both head-to-head tests, but the margins tell a more interesting story. In Geekbench OpenCL, the A10G scores 158,063 against the RTX A5500 Mobile’s 124,287, a 27.2% advantage. The Vulkan gap is even wider—the A10G posts 145,863 versus 103,601, which translates to a commanding 40.8% lead. These are not marginal differences; they represent substantial performance tiers.

The OpenCL result is particularly revealing when placed in context. The A10G's 158,063 score sits just 1.1% above the NVIDIA Tesla V100 PCIe 32 GB (150,305), while trailing the AMD Radeon Pro W6800X (160,671) by 5.4% and the NVIDIA A100 PCIe 40 GB (162,504) by 6.5%. This places the A10G in the upper echelon of compute accelerators, firmly within striking distance of the A100 despite its lower power envelope. The RTX A5500 Mobile, by contrast, ranks near the NVIDIA Tesla V100 SXM2 16 GB (114,395) with a delta of -0.4%, and sits 2.7% behind the RTX 4000 SFF Ada Generation (117,088). The mobile part is competitive within its class, but that class is a full tier below the A10G.

The Vulkan numbers reinforce this hierarchy. The A10G's 145,863 is 40.8% higher than the A5500 Mobile's 103,601, and this delta suggests the desktop Ampere architecture scales better with the Vulkan API's draw-call overhead and multi-threaded command submission. The A5500 Mobile's closer gap in OpenCL (27.2%) versus Vulkan (40.8%) hints that the mobile chip's memory subsystem or driver optimization may be a bottleneck in API-heavy workloads—though the FACT PACK does not contain thermal or power throttling data to confirm this hypothesis.

# Architecture Differences

Both GPUs share the Ampere architecture and Samsung's 8 nm process, but they are fundamentally different chips. The A10G uses the GA102 die, while the RTX A5500 Mobile relies on the GA103. This die difference explains most of the performance gap. The GA102 packs 28,300 million transistors on a 628 mm² die, yielding a transistor density of 45.1M per mm². The GA103 is smaller on every metric: 22,000 million transistors, 496 mm², and 44.4M per mm² density. The A10G's larger die provides more physical resources for compute, and the density figures indicate the A5500 Mobile's smaller chip is slightly less efficient in transistor packing.

The compute unit counts diverge sharply. The A10G fields 9,216 shading units, 288 texture mapping units, 96 ROPs, 72 ray tracing cores, and 288 tensor cores. The A5500 Mobile counters with 7,424 shading units, 232 TMUs, 96 ROPs, 58 RT cores, and 232 tensor cores. The ROP count is identical at 96, which means pixel throughput is less differentiated than raw shader work. But the A10G's 31.52 TFLOPS FP32 and FP16 (1:1) performance dwarfs the A5500 Mobile's 22.27 TFLOPS in both precision formats. The 41.5% advantage in FP32 throughput (31.52 versus 22.27) tracks closely with the OpenCL benchmark delta, suggesting compute-limited workloads will see consistent scaling.

Clock speeds also favor the A10G. It runs at 1320 MHz base and 1710 MHz boost, while the A5500 Mobile operates at 975 MHz base and 1500 MHz boost. The A10G's higher boost clock, combined with more cores, produces its fillrate advantages: 164.2 GPixel/s versus 144.0 GPixel/s, and 492.5 GTexel/s versus 348.0 GTexel/s. The memory subsystem further separates them. The A10G uses 24 GB of GDDR6 on a 384-bit bus, achieving 600.2 GB/s bandwidth. The A5500 Mobile has 16 GB on a 256-bit bus, delivering 512.0 GB/s. The memory clock difference (1563 MHz versus 2000 MHz, or 12.5 Gbps versus 16 Gbps effective) partially compensates for the narrower bus, but the A10G still wins on total bandwidth by 17.2%.

# FAQ

Q: Which GPU has higher FP32 compute performance?

A: The NVIDIA A10G delivers 31.52 TFLOPS FP32, which is 41.5% higher than the RTX A5500 Mobile's 22.27 TFLOPS. Both maintain a 1:1 FP16 ratio, so the same percentage advantage applies to half-precision workloads.

Q: How does memory capacity and bandwidth compare?

A: The A10G offers 24 GB GDDR6 with 600.2 GB/s bandwidth, while the A5500 Mobile provides 16 GB GDDR6 with 512.0 GB/s. The A10G leads by 8 GB capacity and 88.2 GB/s bandwidth.

Q: What are the thermal design power (TDP) differences?

A: The A10G has a 150 W TDP and uses a single-slot design with an 8-pin EPS connector, requiring a 450 W suggested PSU. The A5500 Mobile has a 165 W TDP but uses no power connectors, as it is designed for portable devices.

Q: Which GPU has better Vulkan benchmark performance?

A: The A10G scores 145,863 in Geekbench Vulkan, a 40.8% advantage over the A5500 Mobile's 103,601. This is the largest performance delta between the two across all tested benchmarks.

Q: Are both GPUs based on the same architecture?

A: Yes, both use NVIDIA's Ampere architecture and are fabricated on Samsung's 8 nm process. However, the A10G uses the GA102 chip while the A5500 Mobile uses the GA103, with different transistor counts (28,300 million versus 22,000 million) and die sizes (628 mm² versus 496 mm²).

Q: What is the production status of these GPUs?

A: Both are end-of-life products. The A10G was released in April 2021 as part of the Server Ampere generation, and the A5500 Mobile followed in March 2022 under the Ampere-MW generation.

# Specification Differences

| Specification | NVIDIA A10G | NVIDIA RTX A5500 Mobile |

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

| Chip | GA102 | GA103 |

| Generation | Server Ampere (Axx) | Ampere-MW (Ax000) |

| Transistors | 28,300 million | 22,000 million |

| Die Size | 628 mm² | 496 mm² |

| Transistor Density | 45.1M / mm² | 44.4M / mm² |

| Base Clock | 1320 MHz | 975 MHz |

| Boost Clock | 1710 MHz | 1500 MHz |

| Memory Clock | 1563 MHz (12.5 Gbps effective) | 2000 MHz (16 Gbps effective) |

| Memory Size | 24 GB | 16 GB |

| Memory Bus Width | 384 bit | 256 bit |

| Memory Bandwidth | 600.2 GB/s | 512.0 GB/s |

| Shading Units | 9216 | 7424 |

| TMUs | 288 | 232 |

| RT Cores | 72 | 58 |

| Tensor Cores | 288 | 232 |

| Pixel Rate | 164.2 GPixel/s | 144.0 GPixel/s |

| Texture Rate | 492.5 GTexel/s | 348.0 GTexel/s |

| FP32 / FP16 | 31.52 TFLOPS | 22.27 TFLOPS |

| TDP | 150 W | 165 W |

| Slot Width | Single-slot | Not specified |

| Power Connectors | 8-pin EPS | None |

| Suggested PSU | 450 W | Not specified |

| Display Outputs | No outputs | Portable Device Dependent |

| Dimensions | 267 mm x 112 mm | Not specified |

| Release Date | 2021-04-11 | 2022-03-21 |

| Predecessor | Tesla Turing | Quadro Turing-M |

| Successor | Server Ada | Ada-MW |

# Where Each One Wins

The A10G wins decisively in compute-heavy workloads. Its 31.52 TFLOPS FP32 performance, 600.2 GB/s memory bandwidth, and 24 GB capacity make it suitable for large-model inference, scientific simulation, and rendering tasks that demand both raw throughput and memory headroom. The 40.8% Vulkan advantage suggests it handles graphics-adjacent compute APIs more gracefully, likely due to the higher core count and boost clock. Its single-slot form factor and 8-pin EPS power connector indicate a server-oriented design where density and predictable power delivery matter.

The RTX A5500 Mobile wins in portability and integration flexibility. It carries a 165 W TDP with no external power connectors, relying entirely on the host laptop's power delivery. Its "Portable Device Dependent" display outputs mean it can drive displays directly, whereas the A10G has no outputs at all—it is purely an accelerator. The A5500 Mobile's 16 GB memory and 512.0 GB/s bandwidth are still substantial, and its 94th percentile ranking among all GPUs shows it is no slouch. For mobile workstations handling CAD, video editing, or moderate AI workloads, the A5500 Mobile provides Ampere features like RT cores and tensor cores in a package that fits in a laptop.

The ROP count is identical at 96, so pixel fillrate-bound workloads see only a 14% gap (164.2 versus 144.0 GPixel/s), which is narrower than the shader-bound gap. This suggests the A5500 Mobile remains viable for display-oriented tasks, while the A10G dominates in compute-centric scenarios. The A10G's 97th percentile versus the A5500 Mobile's 94th percentile reinforces that the desktop part sits in a higher performance stratum overall.

# The Verdict

The data points to a clear conclusion: the NVIDIA A10G is the superior compute accelerator, and the RTX A5500 Mobile is the superior mobile solution. There is no ambiguity in the benchmark results—the A10G wins both head-to-head tests with deltas of 27.2% and 40.8%. Its larger die, higher core counts, greater memory capacity, and faster bandwidth make it the choice for anyone prioritizing raw performance over portability. The A10G's 97th percentile ranking and its proximity to the A100 and W6800X in rival comparisons confirm it belongs in the upper tier of server-grade GPUs.

The RTX A5500 Mobile, despite losing every benchmark here, still holds a 94th percentile ranking and trades blows with the Tesla V100 SXM2 and RTX 4000 SFF Ada Generation within a few percentage points. Its 16 GB memory and 512.0 GB/s bandwidth are nothing to dismiss, and its lack of power connectors and portable-device-dependent outputs make it the only viable option for laptop deployments. The 165 W TDP is actually higher than the A10G's 150 W, which is notable—the mobile chip consumes more power while delivering less performance, a trade-off inherent to its compact integration.

For a server rack, a data center node, or a dedicated workstation where space and power are manageable, the A10G is the obvious pick. Its 24 GB memory can hold larger datasets, its 600.2 GB/s bandwidth feeds the 9,216 shaders efficiently, and its single-slot design allows dense stacking. For a mobile workstation that needs to travel, the A5500 Mobile is the only choice between these two—but the data shows it will deliver roughly 27-41% less performance in compute benchmarks. The verdict is not close: the A10G wins on every measured performance metric, and the A5500 Mobile wins only on physical form factor and display connectivity.