AMD Radeon RX 5300M vs NVIDIA A2 Comparison

The AMD Radeon RX 5300M and NVIDIA A2 are both end-of-life products, but they target completely different segments of the GPU market. The RX 5300M is a mobile gaming part from the Radeon RX 5000 series, while the A2 is a low-profile workstation accelerator built on the Ampere architecture. Benchmark data shows they land in nearly the same performance tier, with the RX 5300M holding a slight edge in raw compute. This analysis walks through the head-to-head results, architectural differences, and use-case splits strictly from the supplied data.

Head-to-Head Benchmarks

The only direct benchmark comparison available is the Geekbench OpenCL test. In this workload, the AMD Radeon RX 5300M scores 36,529, while the NVIDIA A2 scores 35,357. The delta is 3.3% in favor of the AMD part, making it the winner of the single head-to-head test. This is a narrow margin, indicating that in general-purpose compute, the two GPUs are closely matched despite their very different designs.

The RX 5300M also has a Geekbench Vulkan score absent for the A2, but its OpenCL result places it at the 80th percentile among all GPUs. The A2, with an average benchmark score of 34,690 across two tests (OpenCL and Vulkan), sits at the 79th percentile. The percentile difference is minimal, reinforcing that these are peer products in overall compute capability.

Looking at the nearest rivals for each card provides further context. The RX 5300M’s closest competitor is the NVIDIA GeForce GTX TITAN X, which scores 36,530—a 0% delta, meaning they are statistically identical. The AMD Radeon PRO W6400 is 1.7% faster, while the NVIDIA T1000 is 0.7% slower. The A2, conversely, is nearly tied with the NVIDIA T1000 8 GB (0.4% delta) and the AMD Radeon HD 7970 (0.4% delta). The A2 is 1% faster than the NVIDIA TITAN V and 1.4% faster than the NVIDIA RTX A1000. These rival relationships show that both cards occupy a crowded mid-range compute band.

The performance parity is notable because the A2’s OpenCL score of 35,357 is its lower-scoring benchmark; its Vulkan score is 34,023. The RX 5300M, with only one benchmark, does not have a Vulkan result, so the comparison is incomplete. Still, for the data available, the RX 5300M leads in the only shared test, but the lead is small enough that application-specific drivers and optimizations could easily flip the result.

The Verdict

From the data, the AMD Radeon RX 5300M wins the compute benchmark outright, making it the better choice for raw OpenCL performance. It is 3.3% faster than the A2, which is a measurable but not overwhelming advantage. The RX 5300M also has a higher percentile ranking (80th vs. 79th), confirming its slight edge in overall GPU capability.

However, the NVIDIA A2 is not far behind, and its architecture suggests different strengths. The A2 has 16 GB of memory compared to the RX 5300M’s 3 GB, a massive difference that the benchmark numbers do not capture. For workloads that require large datasets or frame buffers, the A2’s memory capacity alone could justify its selection despite the 3.3% compute deficit.

The verdict depends on the use case. If the task is purely compute-bound and fits within 3 GB, the RX 5300M is the faster card. If memory capacity is a limiting factor, the A2 is the only viable option. The data does not support a universal recommendation; it supports a workload-specific one. For a general-purpose compute benchmark, the RX 5300M is the winner, but the A2’s 16 GB memory is a decisive feature in its favor for memory-intensive applications.

Architecture Differences

The AMD Radeon RX 5300M uses the Navi 14 chip built on RDNA 1.0 architecture, fabricated on a 7 nm process at TSMC. It contains 6,400 million transistors on a 158 mm² die, resulting in a transistor density of 40.5M per mm². The NVIDIA A2 uses the GA107 chip based on Ampere architecture, fabricated on an 8 nm process at Samsung. It has 8,700 million transistors on a 200 mm² die, with a density of 43.5M per mm².

The architectural philosophies diverge significantly. RDNA 1.0 is a gaming-first design, while Ampere is a compute and AI-oriented architecture. This is evident in the A2’s inclusion of 10 ray tracing cores and 40 tensor cores, which the RX 5300M lacks entirely. The RX 5300M has no RT or tensor core equivalents, relying on traditional shading units.

The A2 also supports DirectX 12 Ultimate (12_2), whereas the RX 5300M supports DirectX 12 (12_1). Both support OpenGL 4.6 and Vulkan 1.4. The A2’s FP16 performance is 4.531 TFLOPS (1:1 ratio) while the RX 5300M achieves 8.138 TFLOPS (2:1 ratio), meaning the AMD card can process half-precision at twice the rate of single-precision, while the NVIDIA card does not have that advantage.

The A2 has 10 RT cores and 40 tensor cores, which are absent from the RX 5300M. This makes the A2 a specialized accelerator for ray-traced and AI workloads, while the RX 5300M is a general-purpose rasterizer. The transistor count difference (8,700 million vs. 6,400 million) reflects the added hardware on the A2, even though the process node is larger (8 nm vs. 7 nm).

Specification Differences

The two GPUs differ in nearly every core specification. The RX 5300M has 1,408 shading units, 88 texture mapping units (TMUs), and 32 render output units (ROPs). The A2 has 1,280 shading units, 40 TMUs, and 32 ROPs. The AMD part has more shading units and TMUs, while both have the same ROP count.

Clock speeds favor the A2. Its base clock is 1440 MHz and boost clock is 1770 MHz, compared to the RX 5300M’s 1000 MHz base and 1445 MHz boost. The A2 also has a game clock of 1181 MHz, which is not listed for the AMD card. Despite lower clocks, the RX 5300M achieves a higher texture rate of 127.2 GTexel/s versus the A2’s 70.80 GTexel/s, due to its higher TMU count. Pixel rates are closer, with the A2 at 56.64 GPixel/s and the RX 5300M at 46.24 GPixel/s.

Memory is the biggest divergence. The RX 5300M has 3 GB of GDDR6 on a 96-bit bus, yielding 168.0 GB/s of bandwidth. The A2 has 16 GB of GDDR6 on a 128-bit bus, yielding 200.1 GB/s. The A2’s memory clock is 1563 MHz (12.5 Gbps effective) while the RX 5300M’s is 1750 MHz (14 Gbps effective). The A2’s larger bus and capacity more than compensate for the slightly slower memory speed.

Power and form factor also differ. The A2 has a TDP of 60 W, is single-slot, and has a suggested PSU of 250 W. The RX 5300M has a TDP of 85 W and its power connectors are listed as “None.” Both use PCIe 4.0 x8. The A2 has no display outputs, while the RX 5300M’s outputs are “Portable Device Dependent,” reflecting its mobile nature. The A2 has a 2021 release date, while the RX 5300M was released in 2019.

FAQ

Q: Which GPU has a higher OpenCL benchmark score?

A: The AMD Radeon RX 5300M scores 36,529, which is 3.3% higher than the NVIDIA A2’s 35,357 in the Geekbench OpenCL test.

Q: How much memory does each card have?

A: The RX 5300M has 3 GB of GDDR6, while the A2 has 16 GB of GDDR6. The A2’s memory bus is 128-bit versus 96-bit, giving it 200.1 GB/s bandwidth compared to 168.0 GB/s.

Q: Does the NVIDIA A2 support ray tracing?

A: Yes, the A2 has 10 ray tracing cores and 40 tensor cores. The RX 5300M has no RT or tensor cores.

Q: What is the transistor count difference?

A: The A2 contains 8,700 million transistors on an 8 nm Samsung process, while the RX 5300M has 6,400 million transistors on a 7 nm TSMC process.

Q: Which card has a higher boost clock?

A: The NVIDIA A2 boosts to 1770 MHz, while the RX 5300M boosts to 1445 MHz. The A2 also has a higher base clock of 1440 MHz versus 1000 MHz.

Q: Are these cards similar in overall performance?

A: Yes, they are very close. The RX 5300M is at the 80th percentile and the A2 is at the 79th. The RX 5300M leads by 3.3% in the only shared benchmark, but the A2’s nearest rivals include the NVIDIA T1000 8 GB with a 0.4% delta.

Where Each One Wins

The AMD Radeon RX 5300M wins in raw OpenCL compute performance. It has a 3.3% lead over the A2 and a higher percentile ranking. Its higher shading unit count (1,408 vs. 1,280) and TMU count (88 vs. 40) contribute to a texture rate of 127.2 GTexel/s, more than double the A2’s 70.80 GTexel/s. For workloads that rely heavily on texture throughput or FP32 compute, the RX 5300M is the stronger choice. Its FP16 performance is also superior at 8.138 TFLOPS, though only in a 2:1 ratio.

The NVIDIA A2 wins in memory capacity and bandwidth. With 16 GB versus 3 GB, it can handle datasets over five times larger. Its 200.1 GB/s bandwidth is 19% higher than the RX 5300M’s 168.0 GB/s. The A2 also has a higher pixel rate (56.64 GPixel/s vs. 46.24 GPixel/s) and a lower TDP (60 W vs. 85 W), making it more power-efficient. The A2’s 40 tensor cores and 10 RT cores give it capabilities the RX 5300M cannot match, making it the only option for AI inference or ray-traced workloads. Its single-slot form factor and no display outputs are designed for server environments, while the RX 5300M is a mobile part with dependent display outputs.

In summary, the RX 5300M is better for general compute and texture-heavy tasks, while the A2 is better for memory-bound, AI, or ray-traced applications. The data shows a clear performance split, with the AMD card winning the compute race and the NVIDIA card winning on capacity and specialized features.