AMD Radeon R7 M350 vs AMD Radeon Vega 10 Mobile Comparison

AMD Radeon Vega 10 Mobile and AMD Radeon R7 M350 are both end-of-life mobile graphics solutions from AMD, but they target fundamentally different system designs. The Vega 10 Mobile is an integrated GPU (IGP) built into the Raven Ridge-M APU, while the R7 M350 is a discrete mobile GPU from the older Gem System generation. Benchmark data shows the R7 M350 holds a single head-to-head win, but the Vega 10 Mobile counters with a newer architecture and significantly higher transistor density. This analysis breaks down where each part actually competes, based strictly on the available facts.

Head-to-Head Benchmarks

The only direct benchmark comparison available is Geekbench OpenCL, and the results favor the discrete R7 M350. The R7 M350 scores 6991, while the Vega 10 Mobile scores 6476. That is a delta of -7.4% for the Vega 10 Mobile, meaning the R7 M350 is approximately 8% faster in this compute-oriented workload. This is a meaningful margin for an integrated part competing against a dedicated GPU, but it is not a landslide.

In the broader context of the benchmark database, the Vega 10 Mobile sits at percentile 37 among all GPUs, with an average benchmark score of 6476. Its nearest rivals are tightly clustered: the NVIDIA Quadro M5000M scores 6481 (just 0.1% higher), the GeForce GT 555M scores 6493 (0.3% higher), and the GeForce GTX 670M scores 6513 (0.6% higher). Interestingly, the NVIDIA RTX PRO 5000 72 GB Blackwell scores 6407, which is 1.1% lower than the Vega 10 Mobile — an extreme outlier in terms of class, but the data places them side by side.

The R7 M350, by contrast, has an average benchmark score of 6327 across its two recorded tests (OpenCL and Vulkan), placing it at percentile 36. Its nearest rivals include the AMD Radeon Pro WX 4100 at 6330 (0% delta), the NVIDIA Quadro K620 at 6282 (0.7% higher), and both the GeForce RTX 5070 Ti SUPER and RTX 4070 Ti SUPER AD102 at 6270 (0.9% higher). The R7 M350's single OpenCL score of 6991 is its high-water mark; its Vulkan score of 5662 is notably lower, indicating that API choice matters for this GPU.

The key takeaway from the head-to-head is that the discrete R7 M350 wins the compute race, but the Vega 10 Mobile is not far behind. The 7.4% deficit is small enough that in real-world mixed workloads, the integrated Vega part could hold its own, especially given the architectural advantages detailed below.

Architecture Differences

The most fundamental difference is the process node. The Vega 10 Mobile is built on a 14 nm process at GlobalFoundries, while the R7 M350 uses a 28 nm process at TSMC. This is a full node generation apart, and it shows in transistor density: the Vega 10 Mobile packs 4,940 million transistors into a 210 mm² die, yielding 23.5 million transistors per square millimeter. The R7 M350 has 1,550 million transistors on a 125 mm² die, for a density of just 12.4M/mm². That is nearly double the density advantage for the newer part.

Architecturally, the Vega 10 Mobile uses GCN 5.0, whereas the R7 M350 is based on GCN 3.0. This means the Vega part has access to newer instruction sets and efficiency improvements, even though both support DirectX 12 (12_1 vs 12_0 respectively). The Vega 10 Mobile also supports Vulkan 1.3, while the R7 M350 is limited to Vulkan 1.2.170. Both support OpenGL 4.6.

The Vega 10 Mobile has 640 shading units, 40 texture mapping units, and 8 ROPs. The R7 M350 has 384 shading units, 24 TMUs, and also 8 ROPs. The Vega part has 67% more shading units and 67% more TMUs, yet it still loses the OpenCL benchmark — a signal of the R7 M350's higher clock speeds and dedicated memory.

The memory subsystem is where the designs diverge completely. The Vega 10 Mobile uses system-shared memory, with bandwidth listed as "System Dependent." The R7 M350 has 4 GB of dedicated DDR3 memory on a 64-bit bus, delivering 16.00 GB/s of bandwidth. This dedicated memory is likely why the discrete part wins the compute test, as it does not contend with the CPU for memory access.

The Vega 10 Mobile is an IGP with a bus interface of IGP and no power connectors, rated at a 10 W TDP. The R7 M350 uses PCIe 3.0 x8, but its TDP and power connector are not listed in the data. The Vega part's clock speeds run from 300 MHz base to 1301 MHz boost, while the R7 M350 runs at 1000 MHz base and 1015 MHz boost. The R7 M350's memory clock is 1000 MHz (2 Gbps effective).

Pixel and texture rates reflect the compute differences: the Vega 10 Mobile delivers 10.41 GPixel/s and 52.04 GTexel/s, while the R7 M350 delivers 8.12 GPixel/s and 24.36 GTexel/s. The Vega part is substantially faster in fill-rate-limited scenarios. FP32 compute is 1.665 TFLOPS for the Vega 10 Mobile versus 779.5 GFLOPS for the R7 M350 — more than double. The Vega part also supports FP16 at 3.331 TFLOPS (2:1 ratio), while the R7 M350's FP16 is identical to its FP32 at 779.5 GFLOPS (1:1 ratio).

FAQ

Q: Which GPU has more shading units?

A: The AMD Radeon Vega 10 Mobile has 640 shading units, compared to 384 on the AMD Radeon R7 M350.

Q: Does the R7 M350 beat the Vega 10 Mobile in every benchmark?

A: No. In the single head-to-head test (Geekbench OpenCL), the R7 M350 wins with 6991 versus 6476, but the Vega 10 Mobile has no recorded Vulkan score to compare against.

Q: What is the memory configuration difference?

A: The R7 M350 has 4 GB of dedicated DDR3 memory on a 64-bit bus with 16.00 GB/s bandwidth. The Vega 10 Mobile uses system-shared memory with bandwidth that is system dependent.

Q: Which GPU supports a newer Vulkan version?

A: The Vega 10 Mobile supports Vulkan 1.3, while the R7 M350 supports Vulkan 1.2.170.

Q: How do their transistor counts compare?

A: The Vega 10 Mobile has 4,940 million transistors, while the R7 M350 has 1,550 million transistors.

Q: Is the R7 M350's average benchmark score higher than the Vega 10 Mobile's?

A: No. The R7 M350's average benchmark score is 6327, which is lower than the Vega 10 Mobile's 6476, despite the R7 M350 winning the single head-to-head OpenCL test.

Specification Differences

• Process Node: Vega 10 Mobile is 14 nm (GlobalFoundries); R7 M350 is 28 nm (TSMC).
• Transistors: Vega 10 Mobile has 4,940 million; R7 M350 has 1,550 million.
• Die Size: Vega 10 Mobile is 210 mm²; R7 M350 is 125 mm².
• Transistor Density: Vega 10 Mobile is 23.5M / mm²; R7 M350 is 12.4M / mm².
• Architecture: Vega 10 Mobile is GCN 5.0; R7 M350 is GCN 3.0.
• Base Clock: Vega 10 Mobile is 300 MHz; R7 M350 is 1000 MHz.
• Boost Clock: Vega 10 Mobile is 1301 MHz; R7 M350 is 1015 MHz.
• Memory Size: Vega 10 Mobile is system shared; R7 M350 is 4 GB.
• Memory Type: Vega 10 Mobile is system shared; R7 M350 is DDR3.
• Memory Bus Width: Vega 10 Mobile is system shared; R7 M350 is 64 bit.
• Memory Bandwidth: Vega 10 Mobile is system dependent; R7 M350 is 16.00 GB/s.
• Shading Units: Vega 10 Mobile has 640; R7 M350 has 384.
• TMUs: Vega 10 Mobile has 40; R7 M350 has 24.
• Pixel Rate: Vega 10 Mobile is 10.41 GPixel/s; R7 M350 is 8.12 GPixel/s.
• Texture Rate: Vega 10 Mobile is 52.04 GTexel/s; R7 M350 is 24.36 GTexel/s.
• FP32: Vega 10 Mobile is 1.665 TFLOPS; R7 M350 is 779.5 GFLOPS.
• FP16: Vega 10 Mobile is 3.331 TFLOPS (2:1); R7 M350 is 779.5 GFLOPS (1:1).
• TDP: Vega 10 Mobile is 10 W; R7 M350 is not listed.
• Bus Interface: Vega 10 Mobile is IGP; R7 M350 is PCIe 3.0 x8.
• DirectX: Vega 10 Mobile is 12 (12_1); R7 M350 is 12 (12_0).
• Vulkan: Vega 10 Mobile is 1.3; R7 M350 is 1.2.170.
• Release Date: Vega 10 Mobile is 2019-01-07; R7 M350 is 2015-05-04.
• Predecessor: Vega 10 Mobile is GCN 3.0 IGP; R7 M350 is Solar System.
• Successor: Vega 10 Mobile is Navi II IGP; R7 M350 is Polaris Mobile.

The Verdict

The data points to a clear split: the R7 M350 wins the only direct benchmark, but the Vega 10 Mobile is the superior part on almost every architectural metric. The R7 M350's 7.4% OpenCL advantage is real, but it comes from a 1000 MHz base clock and dedicated 4 GB DDR3 memory. The Vega 10 Mobile, despite its 300 MHz base clock and shared memory, delivers more than double the FP32 compute (1.665 TFLOPS vs 779.5 GFLOPS), higher pixel and texture rates, and nearly double the transistor density.

For a system builder choosing between these two, the decision hinges on memory architecture. If the workload is compute-heavy and benefits from dedicated memory bandwidth, the R7 M350's 16.00 GB/s is a tangible asset. However, the Vega 10 Mobile's 10 W TDP, newer GCN 5.0 architecture, and superior fill rates make it the better choice for integrated graphics scenarios where power draw and thermal envelope are critical. The R7 M350 is a discrete card, meaning it consumes additional power and requires a PCIe slot, whereas the Vega 10 Mobile is built into the APU with no additional connectors.

The percentile rankings are nearly identical (37 vs 36), and the average benchmark scores are within 2.3% of each other (6476 vs 6327). This is a statistical tie in overall capability. The R7 M350's single OpenCL win is offset by its weaker Vulkan performance (5662), which the Vega 10 Mobile does not have a recorded score for. Given that the Vega 10 Mobile supports Vulkan 1.3 and the R7 M350 only supports 1.2.170, the newer part is more future-proof for API compatibility.

Where Each One Wins

AMD Radeon R7 M350 wins in:

• OpenCL compute performance (6991 vs 6476, +7.4%)
• Dedicated memory scenarios (4 GB DDR3, 16.00 GB/s vs system shared)
• Higher base clock stability (1000 MHz vs 300 MHz)
• Systems where a discrete GPU is preferred over an IGP

AMD Radeon Vega 10 Mobile wins in:

• Raw compute throughput (1.665 TFLOPS FP32 vs 779.5 GFLOPS)
• Texture and pixel fill rates (52.04 GTexel/s vs 24.36 GTexel/s; 10.41 GPixel/s vs 8.12 GPixel/s)
• Power efficiency (10 W TDP vs unspecified but discrete-class power draw)
• Transistor density (23.5M / mm² vs 12.4M / mm²)
• Modern API support (Vulkan 1.3, DirectX 12_1 vs Vulkan 1.2.170, DirectX 12_0)
• FP16 performance (3.331 TFLOPS vs 779.5 GFLOPS)

The R7 M350 is the pick if you need a dedicated memory pool and slightly better OpenCL numbers. The Vega 10 Mobile is the pick if you want integrated graphics with double the compute throughput, better fill rates, and a much newer architectural foundation. The benchmark data does not support calling one a clear winner; it supports calling them different tools for different jobs.