AMD Radeon RX 5300M vs NVIDIA RTX A1000 Comparison

Head-to-Head Benchmarks

The single direct comparison available in the data is the Geekbench OpenCL compute test, and it is decisively in favor of the NVIDIA RTX A1000. The RTX A1000 scores 52,078 points, while the AMD Radeon RX 5300M manages 36,529 points. That translates to a deltaPct of -29.9% for the AMD part, meaning the NVIDIA GPU is roughly 30% faster in this OpenCL workload. This is a substantial margin, and it establishes the RTX A1000 as the clear compute winner between the two.

However, the story does not end there. The RTX A1000’s average benchmark score across all its tested workloads is 34,207, which is actually lower than the RX 5300M’s average of 36,529. This discrepancy is explained by the fact that the RTX A1000 has additional benchmark results—specifically, a 3DMark Steel Nomad DX12 score of 969 and a Geekbench Vulkan score of 49,574—which pull its average down when combined with the OpenCL result. The RX 5300M, by contrast, has only the single OpenCL score. The data does not provide a direct Vulkan or 3DMark comparison between the two, so the only apples-to-apples head-to-head remains the OpenCL test, where the NVIDIA card wins outright.

Looking at percentile rankings, the two GPUs are nearly tied in overall standing. The RX 5300M sits at the 80th percentile of all GPUs, while the RTX A1000 is at the 79th percentile. This suggests that despite the RTX A1000’s commanding OpenCL lead, its overall performance profile—when averaged across multiple benchmark types—places it in the same broad performance tier as the AMD part. The percentile data implies that the RX 5300M’s single strong OpenCL result is enough to keep it competitive in aggregate, even though the RTX A1000 wins the only direct test.

The nearest rivals for each GPU further contextualize these scores. The RX 5300M’s closest competitor is the NVIDIA GeForce GTX TITAN X, with an average score of 36,530—a deltaPct of 0%, essentially a statistical tie. The AMD card also edges out the NVIDIA T1000 (36,289, +0.7%) and the AMD Radeon Pro Duo (35,860, +1.9%), while trailing the AMD Radeon PRO W6400 (37,157, -1.7%). For the RTX A1000, its average score of 34,207 places it just ahead of the NVIDIA RTX A2000 12 GB (34,154, +0.2%) and the AMD Radeon RX 560 XT (34,133, +0.2%), while sitting slightly behind the NVIDIA TITAN V (34,355, -0.4%) and just ahead of the AMD Radeon RX 480 (33,997, +0.6%). These rivalries show that both cards are clustered in a tight performance band, with the RTX A1000’s average being dragged down by its DX12 result.

The Verdict

The data points to a clear but nuanced conclusion. For raw compute performance in OpenCL, the NVIDIA RTX A1000 is the definitive winner, delivering 30% higher scores than the AMD Radeon RX 5300M. The RTX A1000 also brings modern features like ray tracing cores and tensor cores, which the RX 5300M lacks entirely, making it the more capable card for workloads that leverage those accelerators. The RTX A1000’s 8 GB of VRAM versus 3 GB on the AMD part is another significant advantage for memory-intensive tasks.

However, the RX 5300M is not without its merits. Its average benchmark score of 36,529 is actually higher than the RTX A1000’s 34,207, and its 80th percentile ranking edges out the RTX A1000’s 79th. This suggests that for users who prioritize the specific workload represented by the OpenCL test—and who do not need ray tracing, tensor cores, or large memory buffers—the AMD card can still hold its own. The RX 5300M also has a higher texture rate (127.2 GTexel/s vs. 105.3 GTexel/s) and a higher boost clock in some scenarios, which could benefit certain rasterization tasks.

Who should pick which? The RTX A1000 is the choice for professionals or enthusiasts who need CUDA-accelerated compute, ray tracing, or AI workloads, and who require a larger memory pool. The RX 5300M is a viable option for those on a tighter performance budget who primarily run OpenCL-based applications and value the higher aggregate benchmark standing. The data does not declare an outright winner across all metrics; it reveals a trade-off between compute headroom and average performance.

Architecture Differences

The two GPUs come from fundamentally different architectural generations. The AMD Radeon RX 5300M is built on the RDNA 1.0 architecture, using the Navi 14 chip, and is fabricated on a 7 nm process at TSMC. The NVIDIA RTX A1000, in contrast, uses the Ampere architecture with the GA107 chip, manufactured on an 8 nm process at Samsung. The process node difference is notable—7 nm versus 8 nm—though both are modern nodes.

Transistor counts and die sizes also differ markedly. The RTX A1000 packs 8,700 million transistors onto a 200 mm² die, yielding a transistor density of 43.5M per mm². The RX 5300M has 6,400 million transistors on a 158 mm² die, with a density of 40.5M per mm². This means the NVIDIA chip is both larger and denser, which correlates with its higher shading unit count (2,304 vs. 1,408) and additional hardware features.

The most significant architectural divergence is the presence of specialized cores. The RTX A1000 includes 18 ray tracing cores and 72 tensor cores, while the RX 5300M has none of either. This is a fundamental capability gap: the RTX A1000 can accelerate ray-traced rendering and AI inference tasks, while the RX 5300M relies purely on traditional shading units. The RTX A1000 also supports DirectX 12 Ultimate (12_2), whereas the RX 5300M only supports DirectX 12 (12_1), indicating the NVIDIA card is better positioned for future game and application features.

Memory architecture differs as well. The RTX A1000 uses 8 GB of GDDR6 on a 128-bit bus, while the RX 5300M uses 3 GB of GDDR6 on a 96-bit bus. The NVIDIA card’s memory bandwidth of 192.0 GB/s exceeds the AMD card’s 168.0 GB/s, and its larger capacity is a substantial advantage for large datasets. The RX 5300M’s fp16 throughput of 8.138 TFLOPS (2:1 ratio) is higher than its fp32 rate, whereas the RTX A1000’s fp16 and fp32 are both 6.737 TFLOPS (1:1 ratio), reflecting different design priorities.

Specification Differences

The two cards differ on nearly every key specification. Clock speeds are one area of divergence: the RX 5300M has a base clock of 1000 MHz and a boost clock of 1445 MHz, while the RTX A1000 has a much lower base clock of 727 MHz but a slightly higher boost clock of 1462 MHz. The AMD card also lists a game clock of 1181 MHz, which the NVIDIA card does not have. Memory clocks differ too, with the RX 5300M running at 1750 MHz (14 Gbps effective) and the RTX A1000 at 1500 MHz (12 Gbps effective).

Shading units and texture units show an interesting inversion. The RTX A1000 has 2,304 shading units compared to the RX 5300M’s 1,408, a 64% advantage. However, the RX 5300M has 88 texture mapping units versus the RTX A1000’s 72, giving the AMD card a higher texture rate (127.2 GTexel/s vs. 105.3 GTexel/s). Both have 32 ROPs, and their pixel rates are nearly identical (46.24 GPixel/s for AMD vs. 46.78 GPixel/s for NVIDIA).

Power and physical specifications also differ sharply. The RX 5300M has a TDP of 85 W, while the RTX A1000 draws just 50 W—a 70% power efficiency advantage for the NVIDIA card. The RTX A1000 is a single-slot card with dimensions of 163 mm in length and 69 mm in height, and it suggests a 250 W power supply. The RX 5300M is listed as "Portable Device Dependent" for display outputs, while the RTX A1000 offers 4x mini-DisplayPort 1.4a. Both use PCIe 4.0 x8 interfaces and have no power connectors. The RX 5300M is end-of-life, released in November 2019, while the RTX A1000 is still active, released in April 2024.

FAQ

Q: Which GPU is faster in OpenCL compute?

A: The NVIDIA RTX A1000 scores 52,078 in Geekbench OpenCL, which is 29.9% higher than the AMD Radeon RX 5300M’s 36,529.

Q: Does the RX 5300M have a higher average benchmark score?

A: Yes. The RX 5300M’s average benchmark score is 36,529, while the RTX A1000’s average is 34,207, despite the RTX A1000 winning the direct OpenCL comparison.

Q: What is the memory capacity difference?

A: The RTX A1000 has 8 GB of GDDR6 memory, while the RX 5300M has 3 GB, a 5 GB difference in favor of the NVIDIA card.

Q: Are there any ray tracing or tensor core capabilities on either card?

A: Only the RTX A1000 has them, with 18 ray tracing cores and 72 tensor cores. The RX 5300M has neither.

Q: How do their power requirements compare?

A: The RTX A1000 has a TDP of 50 W, while the RX 5300M has a TDP of 85 W, making the NVIDIA card significantly more power-efficient.

Q: Which card has a higher transistor density?

A: The RTX A1000 has a density of 43.5M transistors per mm², slightly higher than the RX 5300M’s 40.5M per mm².

Where Each One Wins

The NVIDIA RTX A1000 wins in compute-heavy scenarios. Its OpenCL score of 52,078 versus 36,529 for the AMD card makes it the clear choice for applications that rely on GPGPU compute, such as scientific simulations, data processing, or rendering workloads that use OpenCL. The RTX A1000’s 18 ray tracing cores and 72 tensor cores give it capabilities the RX 5300M simply does not have, making it the only option here for ray-traced graphics or AI inference tasks. Its 8 GB of memory versus 3 GB is a decisive advantage for large models or high-resolution textures, and its 50 W TDP means it can fit into power-constrained systems where the 85 W RX 5300M might be too demanding.

The AMD Radeon RX 5300M wins in specific rasterization and efficiency metrics. Its texture rate of 127.2 GTexel/s exceeds the RTX A1000’s 105.3 GTexel/s, suggesting it may perform better in texture-bound workloads. Its higher base clock (1000 MHz vs. 727 MHz) and game clock (1181 MHz) indicate it can maintain higher sustained clocks in gaming scenarios, even if its boost clock is slightly lower. The RX 5300M’s average benchmark score of 36,529 is higher than the RTX A1000’s 34,207, and its 80th percentile ranking versus 79th suggests it is marginally better positioned in the overall GPU landscape. For users who only care about the OpenCL workload and do not need ray tracing, tensor cores, or large memory, the RX 5300M’s single-score dominance (36,529 vs. 34,207 average) makes it a defensible choice.