AMD Radeon Pro 5300 vs NVIDIA A2 Comparison

AMD Radeon Pro 5300 and NVIDIA A2 are both compact, low-power graphics cards aimed at professional workloads, yet they occupy different positions in the database’s performance hierarchy. The Radeon Pro 5300, built on AMD’s RDNA 1.0 architecture, targets Mac-centric compute and rendering tasks, while the NVIDIA A2, based on the Ampere architecture, is designed for inference and virtualized environments. This analysis compares their recorded benchmark results, architectural layouts, and practical strengths using only the database’s measurements.

Head-to-Head Benchmarks

The database includes two direct benchmark comparisons between these cards: Geekbench OpenCL and Geekbench Vulkan. In both tests, the AMD Radeon Pro 5300 comes out ahead, though the margins are modest.

In Geekbench OpenCL, the Radeon Pro 5300 scores 38,747 points against the NVIDIA A2’s 35,357 points. That is a 9.6% advantage for the AMD card. OpenCL is a common compute API used across professional applications, so this result indicates that the Radeon Pro 5300 can deliver more raw compute throughput in mixed workloads when both cards are operating under the same API constraints. The 9.6% delta is not trivial, but it is far from a decisive gap.

In Geekbench Vulkan, the Radeon Pro 5300 again wins, scoring 35,793 versus the A2’s 34,023 points. This translates to a 5.2% lead for AMD. Vulkan is increasingly used for cross-platform rendering and compute, and the smaller margin here suggests that the NVIDIA A2’s architecture closes some of the gap in graphics-oriented tasks, though it still trails.

The head-to-head tally shows 2 wins for the AMD Radeon Pro 5300 and 0 wins for the NVIDIA A2. Neither card appears in the other’s nearest rival list, which means the database places them in different performance tiers. The Radeon Pro 5300’s average benchmark score is 40,870, placing it at the 82nd percentile of all GPUs. Its nearest rivals include the NVIDIA GeForce RTX 3080 Ti (average score 41,187, delta -0.8%), the NVIDIA GeForce RTX 5070 (40,377, delta 1.2%), and the AMD Radeon Pro 580 (40,318, delta 1.4%). This means the Radeon Pro 5300 sits within 2% of several much larger cards, which is impressive for its compact form factor.

The NVIDIA A2, meanwhile, has an average benchmark score of 34,690 and sits at the 79th percentile. Its nearest rivals are the NVIDIA T1000 8 GB (34,561, delta 0.4%), AMD Radeon HD 7970 (34,541, delta 0.4%), NVIDIA TITAN V (34,355, delta 1%), and NVIDIA RTX A1000 (34,207, delta 1.4%). The A2 is effectively clustered with these cards, all within a 1.4% range, so it does not stand out from its immediate competition.

Interpreting these numbers in context, the Radeon Pro 5300 is roughly 18% faster than the A2 in average benchmark score (40,870 versus 34,690). That is a meaningful gap for professional users who rely on compute performance. However, the A2’s lower power draw and different feature set may compensate in specific deployment scenarios, which the architecture section will address.

Architecture Differences

The two cards diverge significantly in their underlying designs. The AMD Radeon Pro 5300 uses the Navi 14 chip on the RDNA 1.0 architecture, manufactured on a 7 nm process at TSMC. The NVIDIA A2 uses the GA107 chip on the Ampere architecture, built on Samsung’s 8 nm process. The process node difference gives AMD a smaller die: the Radeon Pro 5300’s die measures 158 mm², while the A2’s is 200 mm². Transistor counts tell a more complex story: the Radeon Pro 5300 packs 6,400 million transistors into its smaller die, resulting in a density of 40.5 million transistors per mm². The A2 has 8,700 million transistors across its larger die, yielding a slightly higher density of 43.5 million per mm².

Clock speeds favor the NVIDIA A2. Its base clock is 1440 MHz, boosting to 1770 MHz. The Radeon Pro 5300 starts at 1000 MHz and boosts to 1650 MHz. Despite lower clocks, the AMD card achieves comparable raw throughput due to its architecture. Memory clocks also differ: the Radeon Pro 5300 runs its GDDR6 memory at 1750 MHz, translating to 14 Gbps effective, while the A2 runs at 1563 MHz, or 12.5 Gbps effective. Yet the A2 has more memory and slightly lower bandwidth, which we will examine next.

The memory subsystems are a major differentiator. The Radeon Pro 5300 has 4 GB of GDDR6 on a 128-bit bus, providing 224.0 GB/s of bandwidth. The NVIDIA A2 offers 16 GB of GDDR6, also on a 128-bit bus, but with 200.1 GB/s of bandwidth. The A2’s 4x capacity is critical for large datasets in inference or virtual GPU workloads. The bandwidth reduction is minor (about 11% less), but the capacity advantage is substantial.

Compute resources show a mixed picture. Both cards have 1280 shading units, but the Radeon Pro 5300 has 80 texture mapping units (TMUs) versus the A2’s 40. Both have 32 raster output units (ROPs). This gives the AMD card a higher texture fill rate of 132.0 GTexel/s versus 70.80 GTexel/s for the A2. Pixel rates are similar: 52.80 GPixel/s for AMD and 56.64 GPixel/s for NVIDIA.

Floating-point performance favors the A2 in FP32: 4.531 TFLOPS versus 4.224 TFLOPS. The FP16 comparison is more complex. The Radeon Pro 5300 achieves 8.448 TFLOPS in FP16 with a 2:1 ratio, meaning it can double its throughput for half-precision work. The NVIDIA A2 offers 4.531 TFLOPS in FP16 with a 1:1 ratio, meaning no speedup over FP32. This is a notable architectural difference: AMD’s card is better suited to FP16-heavy workloads, while NVIDIA’s card treats FP16 as a passthrough, likely relying on its tensor cores for accelerated AI tasks.

The A2 includes 10 ray tracing cores and 40 tensor cores, features completely absent from the Radeon Pro 5300. Tensor cores enable accelerated deep learning inference, and ray tracing cores support real-time ray-traced rendering. The Radeon Pro 5300 has neither, reflecting its focus on traditional compute and graphics.

API support also differs. The Radeon Pro 5300 supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The NVIDIA A2 supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The 12_2 feature level on the A2 includes additional ray tracing and mesh shading capabilities, aligning with its hardware features.

Power consumption is a clear win for the NVIDIA A2. Its TDP is 60 W, while the Radeon Pro 5300 draws 85 W. Both have no power connectors and suggest a 250 W power supply, but the A2’s lower draw makes it more suitable for passively cooled or power-constrained environments. The A2 is a single-slot card, while the Radeon Pro 5300 is listed as IGP, meaning it is integrated into a system board rather than a standalone card. Neither card has display outputs, confirming their headless compute or server roles.

Where Each One Wins

Based on the recorded benchmark data and architectural specifications, the two cards serve different primary use cases.

The AMD Radeon Pro 5300 wins in compute tasks that prioritize raw throughput across common APIs. Its 9.6% lead in OpenCL and 5.2% lead in Vulkan indicate that it is the stronger general-purpose compute card in this comparison. For FP16 workloads, its 2:1 ratio doubles its throughput to 8.448 TFLOPS, making it a better choice for applications that use half-precision arithmetic, such as some machine learning training tasks or certain visualization pipelines. Its higher texture fill rate (132.0 GTexel/s) also benefits graphics-heavy workloads that rely on texture sampling. The Radeon Pro 5300’s higher average benchmark score (40,870 versus 34,690) and higher percentile rank (82nd versus 79th) further support its overall performance advantage.

The NVIDIA A2 wins in memory capacity and power efficiency. Its 16 GB of VRAM is four times the Radeon Pro 5300’s 4 GB, making it far better suited for workloads that require large model residency, such as inference on sizable neural networks or handling large datasets without frequent data transfers. Its 60 W TDP is 30% lower than the Radeon Pro 5300’s 85 W, which reduces thermal output and enables denser server deployments. The A2’s tensor cores provide dedicated hardware for AI inference, a feature the Radeon Pro 5300 lacks entirely. In ray tracing workloads, the A2’s 10 RT cores also give it an advantage, though neither card is positioned as a high-end rendering solution.

The A2’s FP32 throughput is slightly higher (4.531 TFLOPS versus 4.224 TFLOPS), so for pure FP32 compute, the NVIDIA card has a small edge. Its DirectX 12 Ultimate support also means it can handle newer graphics features, though its lower texture rate limits its rasterization performance.

FAQ

Q: Which card has a higher average benchmark score?

A: The AMD Radeon Pro 5300 has an average benchmark score of 40,870, while the NVIDIA A2 scores 34,690. This puts the Radeon Pro 5300 at the 82nd percentile of all GPUs, compared to the A2’s 79th percentile.

Q: How much faster is the Radeon Pro 5300 in OpenCL?

A: In Geekbench OpenCL, the Radeon Pro 5300 scores 38,747 versus the NVIDIA A2’s 35,357, giving AMD a 9.6% advantage.

Q: Does the NVIDIA A2 have more memory?

A: Yes, the NVIDIA A2 has 16 GB of GDDR6 memory, while the AMD Radeon Pro 5300 has 4 GB. The A2’s memory operates at 200.1 GB/s bandwidth, compared to the Radeon Pro 5300’s 224.0 GB/s.

Q: What is the FP16 performance difference?

A: The Radeon Pro 5300 achieves 8.448 TFLOPS in FP16 due to a 2:1 ratio, while the NVIDIA A2 delivers 4.531 TFLOPS in FP16 with a 1:1 ratio. The AMD card doubles its FP32 throughput for half-precision, whereas the A2 does not.

Q: Which card has tensor cores?

A: Only the NVIDIA A2 includes tensor cores, with 40 available. The AMD Radeon Pro 5300 has no tensor cores or ray tracing cores.

Q: What is the power draw difference?

A: The NVIDIA A2 has a TDP of 60 W, while the AMD Radeon Pro 5300 has a TDP of 85 W. Both cards have no power connectors and a suggested power supply of 250 W.

Specification Differences

The following table summarizes the key specification differences between the two cards, based only on the database fields where they diverge:

| Specification | AMD Radeon Pro 5300 | NVIDIA A2 |

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

| Architecture | RDNA 1.0 | Ampere |

| Process Node | 7 nm | 8 nm |

| Foundry | TSMC | Samsung |

| Transistors | 6,400 million | 8,700 million |

| Die Size | 158 mm² | 200 mm² |

| Transistor Density | 40.5M / mm² | 43.5M / mm² |

| Base Clock | 1000 MHz | 1440 MHz |

| Boost Clock | 1650 MHz | 1770 MHz |

| Memory Clock | 1750 MHz (14 Gbps effective) | 1563 MHz (12.5 Gbps effective) |

| Memory Size | 4 GB | 16 GB |

| Memory Type | GDDR6 | GDDR6 |

| Memory Bandwidth | 224.0 GB/s | 200.1 GB/s |

| TMUs | 80 | 40 |

| RT Cores | None | 10 |

| Tensor Cores | None | 40 |

| Texture Rate | 132.0 GTexel/s | 70.80 GTexel/s |

| FP32 | 4.224 TFLOPS | 4.531 TFLOPS |

| FP16 | 8.448 TFLOPS (2:1) | 4.531 TFLOPS (1:1) |

| TDP | 85 W | 60 W |

| Slot Width | IGP | Single-slot |

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

| Release Date | 2020-08-03 | 2021-11-09 |

| Predecessor | None listed | Quadro Turing |

| Successor | None listed | Workstation Ada |

| Geekbench OpenCL | 38,747 | 35,357 |

| Geekbench Vulkan | 35,793 | 34,023 |

| Average Benchmark Score | 40,870 | 34,690 |

| Percentile vs All GPUs | 82 | 79 |

The Radeon Pro 5300 offers better texture throughput and FP16 compute, while the NVIDIA A2 counters with more memory, lower power draw, and dedicated tensor and ray tracing hardware. The database’s benchmark results show the AMD card as the faster option in general compute, but the A2’s specifications suggest it is optimized for specialized AI and memory-intensive tasks.