GPU Comparison

AMD Radeon RX 5300M and NVIDIA T1000 are both end-of-life mobile graphics solutions that land in the same performance tier, separated by a razor-thin margin in aggregate scoring. The data places the AMD part at an average benchmark score of 36,371, while the NVIDIA card averages 36,282, a difference of only 0.2%. Both occupy the 80th percentile among all GPUs, indicating they deliver broadly similar compute throughput in real-world OpenCL workloads. The single head-to-head benchmark available, Geekbench OpenCL, tells a slightly different story than the averages, with the NVIDIA T1000 pulling ahead by 3.4% (37,634 vs. 36,371). This places the two cards in a near-dead heat, where the choice between them hinges on architectural trade-offs and specific workload characteristics rather than a dominant overall winner.

Head-to-Head Benchmarks

The only direct benchmark comparison in the data is Geekbench OpenCL, and it favors the NVIDIA T1000. The T1000 scores 37,634 against the RX 5300M’s 36,371, a 3.4% advantage for the NVIDIA part. This is a meaningful margin in a compute-oriented test, suggesting that the T1000’s Turing architecture extracts slightly more efficiency from its hardware configuration under OpenCL. However, the aggregate average scores across all recorded benchmarks narrow this gap dramatically: the RX 5300M averages 36,371, while the T1000 averages 36,282, making the AMD part 0.2% ahead on average. This discrepancy indicates that the T1000’s OpenCL win is not necessarily representative of its overall performance profile, as other workloads may favor the RX 5300M’s higher raw throughput metrics.

Looking at the nearest rivals for each card provides additional context. The RX 5300M’s closest competitor is the NVIDIA GeForce GTX TITAN X, which scores 36,305, a 0.2% delta in favor of the AMD part. The T1000 sits just behind the RX 5300M in this grouping, with a 0.2% deficit. Both cards also trade places with the AMD Radeon RX 7900 GRE, which scores 36,101; the RX 5300M leads it by 0.7%, while the T1000 leads it by 0.5%. The AMD Radeon Pro Duo trails both by 1.4% (RX 5300M) and 1.2% (T1000), respectively. These deltas are all within a 1.5% band, underscoring that neither card has a decisive edge in synthetic compute benchmarks, they are effectively interchangeable in aggregate performance, with the T1000’s single-test win being the most notable divergence.

The T1000’s 3.4% lead in Geekbench OpenCL is its only recorded win in the head-to-head data, while the RX 5300M has no direct wins. This asymmetry suggests that the NVIDIA card may have a slight advantage in OpenCL-specific workloads, possibly due to driver optimizations or architectural scheduling differences. Yet the average scores, which pull from a broader set of benchmarks, nearly erase this gap, implying that the RX 5300M compensates in other areas. For a buyer prioritizing OpenCL compute, the T1000 is the safer bet based on this data; for general-purpose performance, the two are statistically tied.

The Verdict

From the data alone, the NVIDIA T1000 emerges as the pick for OpenCL-centric tasks, as it leads the RX 5300M by 3.4% in the only head-to-head benchmark. Its average score of 36,282 is within 0.2% of the AMD part, so the overall performance difference is negligible, but the specific OpenCL advantage gives it a tangible edge in that workload. The T1000 also offers a larger memory pool (4 GB vs. 3 GB) and a wider 128-bit memory bus, which could benefit applications with higher memory pressure, though the RX 5300M counters with higher bandwidth (168.0 GB/s vs. 160.0 GB/s). Users who run OpenCL-based rendering, simulation, or data processing should favor the T1000 based on the benchmark delta.

The AMD Radeon RX 5300M, despite losing the head-to-head, holds its own in average scores, matching the T1000’s 80th percentile ranking. Its higher texture rate (127.2 GTexel/s vs. 78.12 GTexel/s) and FP32 throughput (4.069 TFLOPS vs. 2.500 TFLOPS) suggest it could outperform the T1000 in workloads that are shader-bound or texture-heavy, even if those scenarios are not captured in the available OpenCL test. The RX 5300M’s 7 nm process node also implies better power efficiency per transistor, though the T1000’s lower TDP (50 W vs. 85 W) means it draws less power overall. For users who prioritize raw compute density or work in environments favoring AMD’s RDNA architecture, the RX 5300M is a defensible choice, but the data does not provide a benchmark to confirm that advantage.

Strictly from the numbers, the NVIDIA T1000 is the recommended option for OpenCL applications, while the RX 5300M is a reasonable alternative for those who value its higher theoretical compute rates or need the extra bandwidth. Neither card dominates; the 0.2% average difference is within noise, and the 3.4% OpenCL gap is the only statistically significant divergence. Choose the T1000 if OpenCL is your primary workload; otherwise, the RX 5300M’s specs offer no proven downside in the available data.

Architecture Differences

The AMD Radeon RX 5300M is built on the RDNA 1.0 architecture, using the Navi 14 chip fabricated on a 7 nm process at TSMC. This node packs 6,400 million transistors into a 158 mm² die, yielding a transistor density of 40.5 million per mm². The RDNA 1.0 design is a departure from AMD’s older GCN-based mobile parts, focusing on higher clock efficiency and improved instructions per clock. In contrast, the NVIDIA T1000 uses the Turing architecture with the TU117 chip on a 12 nm process, also at TSMC. This older node results in 4,700 million transistors spread across a larger 200 mm² die, with a lower density of 23.5 million per mm². The architectural gap is significant: RDNA 1.0 is designed for gaming and compute efficiency, while Turing’s TU117 is a professional-focused chip with a different scheduling approach.

The RX 5300M features 1,408 shading units, 88 texture mapping units, and 32 ROPs, giving it a pixel rate of 46.24 GPixel/s and a texture rate of 127.2 GTexel/s. Its FP32 throughput is 4.069 TFLOPS, with FP16 at 8.138 TFLOPS using a 2:1 ratio. The T1000, by comparison, has only 896 shading units, 56 TMUs, and 32 ROPs, resulting in a lower pixel rate of 44.64 GPixel/s and a texture rate of 78.12 GTexel/s. Its FP32 is 2.500 TFLOPS, and FP16 is 5.000 TFLOPS (2:1). The RX 5300M’s nearly 63% higher shading unit count and 63% higher texture rate indicate a fundamentally more parallel architecture, though the T1000’s lower clocks (boost 1395 MHz vs. 1445 MHz) partially offset this. Neither card includes ray tracing or tensor cores, so both are limited to traditional rasterization and compute.

The memory subsystems also differ architecturally. The RX 5300M uses 3 GB of GDDR6 on a 96-bit bus, delivering 168.0 GB/s bandwidth. The T1000 uses 4 GB of GDDR6 on a 128-bit bus, but with lower effective memory clocks (10 Gbps vs. 14 Gbps), its bandwidth is 160.0 GB/s. The RX 5300M’s higher bandwidth per byte of memory could help in bandwidth-sensitive tasks, while the T1000’s larger capacity benefits multi-tasking or larger datasets. The RX 5300M connects via PCIe 4.0 x8, while the T1000 uses PCIe 3.0 x16, which affects host-to-device transfer speeds; the newer PCIe 4.0 standard offers higher theoretical bandwidth per lane, though the x8 width halves the lane count.

Specification Differences

The most direct specification differences between the two cards are in their process nodes, transistor counts, and die sizes. The RX 5300M uses a 7 nm process with 6,400 million transistors on a 158 mm² die, while the T1000 uses a 12 nm process with 4,700 million transistors on a 200 mm² die. This results in a transistor density of 40.5M/mm² for AMD versus 23.5M/mm² for NVIDIA, reflecting the newer manufacturing technology. Clock speeds differ: the RX 5300M has a base of 1000 MHz and boost of 1445 MHz, with a game clock of 1181 MHz, while the T1000 has a base of 1065 MHz and boost of 1395 MHz, with no game clock listed. The AMD card’s memory runs at 1750 MHz (14 Gbps effective), while the T1000’s memory runs at 1250 MHz (10 Gbps effective).

Memory configuration is a key differentiator: the RX 5300M has 3 GB of GDDR6 on a 96-bit bus with 168.0 GB/s bandwidth, whereas the T1000 has 4 GB of GDDR6 on a 128-bit bus with 160.0 GB/s bandwidth. The RX 5300M has more shading units (1,408 vs. 896), more TMUs (88 vs. 56), and the same number of ROPs (32). Its pixel rate is higher at 46.24 GPixel/s vs. 44.64 GPixel/s, and its texture rate is significantly higher at 127.2 GTexel/s vs. 78.12 GTexel/s. FP32 performance is 4.069 TFLOPS for AMD versus 2.500 TFLOPS for NVIDIA, and FP16 is 8.138 TFLOPS versus 5.000 TFLOPS, respectively.

Power and physical specifications diverge notably. The RX 5300M has a TDP of 85 W with no power connectors required, while the T1000 has a TDP of 50 W and also requires no power connectors, but lists a suggested PSU of 250 W. The T1000 is a single-slot card with dimensions of 156 mm in length and 69 mm in height, while the RX 5300M has no listed dimensions or slot width. The bus interface differs: PCIe 4.0 x8 for AMD versus PCIe 3.0 x16 for NVIDIA. Display outputs also differ, the T1000 has 4x mini-DisplayPort 1.4a, while the RX 5300M’s outputs are listed as portable device dependent. The T1000 has a successor (Workstation Ampere), while the RX 5300M lists no successor. Release dates are distinct: the RX 5300M launched on 2019-11-12, and the T1000 on 2021-05-05.

FAQ

Q: Which GPU has higher raw FP32 compute performance?

A: The AMD Radeon RX 5300M delivers 4.069 TFLOPS FP32, which is 63% higher than the NVIDIA T1000’s 2.500 TFLOPS. This suggests the AMD part has a theoretical advantage in compute-heavy shader workloads, though the OpenCL benchmark shows the T1000 winning by 3.4%.

Q: How do memory capacities and bandwidth compare?

A: The T1000 has a larger 4 GB memory pool on a 128-bit bus, but the RX 5300M’s 3 GB on a 96-bit bus offers higher bandwidth at 168.0 GB/s versus 160.0 GB/s. The T1000’s extra capacity may help with larger datasets, while the RX 5300M’s bandwidth edge could benefit streaming workloads.

Q: What is the performance gap in Geekbench OpenCL?

A: The NVIDIA T1000 scores 37,634 versus the RX 5300M’s 36,371, a 3.4% advantage for the T1000. This is the only direct head-to-head benchmark available, and it favors NVIDIA.

Q: Are these cards comparable in overall performance percentiles?

A: Both the RX 5300M and T1000 sit at the 80th percentile among all GPUs, indicating they are in the same performance tier. Their average scores differ by only 0.2% (36,371 vs. 36,282), making them statistically equivalent on average.

Q: Which card has a lower power draw?

A: The NVIDIA T1000 has a TDP of 50 W, substantially lower than the RX 5300M’s 85 W. This makes the T1000 more suitable for power-constrained environments, though both cards require no additional power connectors.

Q: Do either of these GPUs support ray tracing or tensor cores?

A: No. Both the AMD Radeon RX 5300M and NVIDIA T1000 list null values for ray tracing cores and tensor cores, meaning they lack dedicated hardware for these features and rely on traditional rasterization and compute pipelines.