AMD Radeon R5 M255 vs AMD Radeon R7 M365X Comparison

Head-to-Head Benchmarks

The recorded data pits these two mobile GPUs against each other in two distinct workloads, and the results are surprisingly split. In the Geekbench OpenCL test, the AMD Radeon R7 M365X posts a score of 5939 against the R5 M255's 4650, a decisive 27.7% advantage. That is not a marginal gap; it is a substantial lead that suggests the R7 M365X handles compute-heavy OpenCL workloads with considerably more headroom. The R7 M365X's average benchmark score of 5416 further supports this, placing it in the 32nd percentile of all GPUs in the database. For context, its nearest rivals hover close: the AMD Radeon 610M scores 5444 (0.5% behind), the Intel UHD Graphics P630 scores 5370 (0.9% ahead of the R7 M365X), and the NVIDIA Quadro M4000 scores 5467 (0.9% behind the R7 M365X). The R7 M365X essentially sits in a tight cluster, but its OpenCL output is clearly the standout.

The Vulkan test tells a different story. Here, the R5 M255 edges out the R7 M365X with a score of 4925 versus 4893, a razor-thin 0.6% margin. This is effectively a statistical tie, but it flips the win column: the R5 M255 takes one benchmark, the R7 M365X takes the other. The R5 M255's average benchmark score of 4788 places it in the 28th percentile, and its nearest rivals include the NVIDIA GeForce RTX 3080 12 GB at 4791 (0.1% ahead), the AMD Radeon R5 M335 at 4752 (0.8% behind), and the NVIDIA GeForce 940MX at 4844 (1.2% ahead). The R5 M255's Vulkan showing is competitive with much newer hardware in this specific API, which is curious given its older release date and lower overall percentile.

What do these numbers imply? The R7 M365X delivers a massive OpenCL lead, while the R5 M255 counters with a marginal Vulkan victory. The delta between the two in OpenCL (27.7%) dwarfs the Vulkan delta (0.6%), so in terms of raw performance spread, the R7 M365X is the more volatile and, in one key metric, the far stronger part. The R5 M255, meanwhile, shows that its Vulkan driver or hardware configuration yields a slightly better result despite its lower average score. Benchmark results indicate that neither GPU dominates outright; the winner depends entirely on the workload's API.

The Verdict

From the data alone, the choice hinges on which API matters more to the user. The AMD Radeon R7 M365X wins the OpenCL test by 27.7%, a substantial margin that makes it the clear pick for applications leveraging OpenCL compute. Its average benchmark score of 5416 also exceeds the R5 M255's 4788 by roughly 13.1%, reinforcing its overall performance advantage. The R7 M365X sits at the 32nd percentile, four points higher than the R5 M255's 28th, so in the database's broader ranking, it is the better-positioned GPU.

However, the R5 M255 claims the Vulkan benchmark by 0.6%, and for users whose primary workload is Vulkan-based, that slight edge is the only measurable win. The R5 M255 also offers double the memory (2 GB versus 1 GB), which could matter for certain workloads even if the raw scores do not fully capture it. But the R7 M365X's memory is GDDR5 with 64.00 GB/s bandwidth, exactly double the R5 M255's DDR3 at 32.00 GB/s, so the R7 M365X compensates for its smaller capacity with much faster throughput.

Strictly from the recorded measurements, the R7 M365X is the stronger overall GPU. It wins the more decisive benchmark, holds a higher average score, and ranks higher in the percentile distribution. The R5 M255 is not without merit, its Vulkan win and larger memory pool are real, but they do not offset the OpenCL gap. Users prioritizing OpenCL or general compute should choose the R7 M365X. Users locked into Vulkan-specific applications might prefer the R5 M255, but the margin is so small (0.6%) that it borders on negligible.

FAQ

Q: Which GPU has the higher average benchmark score?

A: The AMD Radeon R7 M365X has an average benchmark score of 5416, while the AMD Radeon R5 M255 scores 4788. The R7 M365X leads by roughly 13.1%.

Q: How do the two GPUs compare in the OpenCL benchmark?

A: The R7 M365X scores 5939 in Geekbench OpenCL, while the R5 M255 scores 4650. That is a 27.7% advantage for the R7 M365X.

Q: Does the R5 M255 win any benchmark?

A: Yes. In the Geekbench Vulkan test, the R5 M255 scores 4925 against the R7 M365X's 4893, a 0.6% margin in favor of the R5 M255.

Q: What are the percentile rankings for each GPU?

A: The R7 M365X sits in the 32nd percentile of all GPUs in the database, while the R5 M255 sits in the 28th percentile.

Q: How much memory does each GPU have?

A: The R7 M365X has 1024 MB of GDDR5 memory, while the R5 M255 has 2 GB of DDR3 memory. The R7 M365X's bus width is 128 bit, and the R5 M255's bus width is also 128 bit.

Q: Which GPU has higher memory bandwidth?

A: The R7 M365X has a memory bandwidth of 64.00 GB/s, exactly double the R5 M255's 32.00 GB/s.

Specification Differences

The two GPUs diverge in several key specifications. The R7 M365X uses a chip named "Litho" with 950 million transistors on a 77 mm² die, while the R5 M255 uses a chip named "Topaz" with 1,550 million transistors on a 125 mm² die. Transistor density is nearly identical: 12.3M / mm² for the R7 M365X and 12.4M / mm² for the R5 M255. Both are built on a 28 nm process at TSMC, so the fabrication process is the same.

Clock speeds differ significantly. The R7 M365X has no base or boost clock listed in the database, but its memory clock is 1000 MHz with 4 Gbps effective data rate. The R5 M255 has a base clock of 925 MHz and a boost clock of 940 MHz, with a memory clock of 1000 MHz and 2 Gbps effective data rate. The R5 M255's memory effective rate is half that of the R7 M365X, which directly explains the bandwidth gap.

Memory configuration is a major differentiator. The R7 M365X has 1024 MB of GDDR5 on a 128 bit bus, yielding 64.00 GB/s bandwidth. The R5 M255 has 2 GB of DDR3 on a 128 bit bus, yielding 32.00 GB/s bandwidth. The R7 M365X has less capacity but twice the bandwidth. Pixel rate and texture rate also favor the R5 M255: it posts 7.520 GPixel/s and 22.56 GTexel/s, while the R7 M365X posts 6.600 GPixel/s and 19.80 GTexel/s. FP32 compute is higher on the R5 M255 at 721.9 GFLOPS versus 633.6 GFLOPS. The R5 M255 also lists FP16 at 721.9 GFLOPS (1:1), while the R7 M365X has no FP16 entry.

Release dates place the R7 M365X later, on 2015-05-04, versus the R5 M255's 2014-10-11. Both are end-of-life, share the same predecessor (Solar System) and successor (Polaris Mobile), and both use a PCIe 3.0 x8 bus interface.

Architecture Differences

The R7 M365X is built on GCN 1.0 architecture, while the R5 M255 uses GCN 3.0. This is a notable generational gap: GCN 3.0 is a more recent iteration of AMD's graphics core architecture, and the R5 M255's chip, Topaz, is physically larger with 1,550 million transistors versus the R7 M365X's 950 million. Despite this, both GPUs have the same shader configuration: 384 shading units, 24 texture mapping units, and 8 raster operation units. The architectural differences do not translate into a core count advantage for either side.

The API support differs slightly. The R7 M365X supports DirectX 12 (11_1), while the R5 M255 supports DirectX 12 (12_0). Both offer OpenGL 4.6 and Vulkan 1.2.170. The R7 M365X's lower DirectX feature level (11_1) could be a limitation for certain modern titles, even though it is nominally DirectX 12 compatible. The R5 M255's DirectX 12 (12_0) is the fuller implementation.

The R5 M255's GCN 3.0 architecture also enables FP16 compute at a 1:1 ratio with FP32, as indicated by its 721.9 GFLOPS FP16 figure. The R7 M365X, with GCN 1.0, has no FP16 listing, suggesting it lacks this capability. This could matter for workloads that leverage half-precision arithmetic, though the database does not record a benchmark for FP16 specifically.

Both chips are fabricated at TSMC on a 28 nm node, and both have a transistor density around 12.3 to 12.4 million transistors per square millimeter. The R5 M255's larger die (125 mm²) and higher transistor count indicate a more complex design, but the R7 M365X's smaller die (77 mm²) achieves nearly the same density with fewer transistors. The architecture differences are real, but the benchmark results do not show a clean generational superiority for GCN 3.0; the R7 M365X's GCN 1.0 design wins OpenCL decisively, while the R5 M255's GCN 3.0 design only edges ahead in Vulkan by 0.6%.

Where Each One Wins

The AMD Radeon R7 M365X is the winner in OpenCL compute. Its 5939 score versus the R5 M255's 4650, a 27.7% lead, makes it the preferred choice for OpenCL-accelerated applications such as certain rendering, scientific, or media tasks. Its higher average benchmark score (5416 versus 4788) and higher percentile ranking (32nd versus 28th) also position it as the better all-around performer in the database's aggregated metrics. The R7 M365X's GDDR5 memory with 64.00 GB/s bandwidth gives it a clear advantage in memory-intensive scenarios, even though its capacity is limited to 1024 MB. Its 6.600 GPixel/s pixel rate and 19.80 GTexel/s texture rate are lower than the R5 M255's, so it is not the winner in raw rasterization throughput.

The AMD Radeon R5 M255 wins in Vulkan, posting 4925 against the R7 M365X's 4893, a 0.6% edge. This makes it the better choice for Vulkan-based game engines or Vulkan compute workloads, though the margin is thin. The R5 M255 also offers 2 GB of memory, double the R7 M365X's 1 GB, which could be useful for larger textures or datasets that fit within memory. Its higher pixel rate (7.520 GPixel/s) and texture rate (22.56 GTexel/s) suggest it handles fill-rate-bound scenarios more efficiently, despite its lower memory bandwidth. The R5 M255's FP16 support at 721.9 GFLOPS (1:1) could be a deciding factor for workloads that use half-precision, a capability the R7 M365X does not list. Its DirectX 12 (12_0) support is also more complete than the R7 M365X's DirectX 12 (11_1), which may matter for newer DirectX 12 titles.

In practical terms, the R7 M365X suits users who prioritize OpenCL performance and are willing to trade memory capacity for bandwidth. The R5 M255 suits users who need Vulkan performance, larger memory capacity, or FP16 compute. The data does not crown a single winner across all metrics; it presents a trade-off between compute leadership and API-specific responsiveness.