AMD Radeon RX 7900M vs NVIDIA A10G Comparison

Head-to-Head Benchmarks

The recorded data shows a split decision between the NVIDIA A10G and the AMD Radeon RX 7900M, with each card claiming one decisive victory in the two shared benchmark tests. The head-to-head comparison is based on Geekbench OpenCL and Geekbench Vulkan scores, which measure different compute workloads and API efficiencies.

In Geekbench OpenCL, the NVIDIA A10G posts a score of 158063 against the AMD Radeon RX 7900M's 129499. This represents a 22.1% advantage for the A10G, a substantial margin that highlights the NVIDIA card's strength in general-purpose compute tasks. The A10G's OpenCL result is not just a narrow win; it is a commanding lead that places it firmly ahead of its rival in this specific workload. The delta of 22.1% is significant enough to suggest that the A10G's architecture is better optimized for the OpenCL compute path, likely due to its server-oriented design and driver maturity in professional environments.

The Geekbench Vulkan test tells a different story. Here, the AMD Radeon RX 7900M scores 158760, while the NVIDIA A10G manages 145863. The AMD card wins by 8.1%, a clear but less overwhelming margin compared to the A10G's OpenCL victory. This result indicates that the RX 7900M's RDNA 3.0 architecture excels in Vulkan-based workloads, which often favor higher clock speeds and efficient geometry processing. The RX 7900M's Vulkan score is also higher than its own OpenCL score, while the A10G shows the opposite trend, suggesting the two cards have fundamentally different performance profiles depending on the API in use.

Looking at the broader database context, the NVIDIA A10G's average benchmark score is 151963, placing it in the 97th percentile of all GPUs. Its nearest rivals include the NVIDIA Tesla V100 PCIe 32 GB, which scores 150305 and trails by only 1.1%, and the AMD Radeon Pro W6800X, which leads the A10G by 5.4% with a score of 160671. The A10G also sits 6.5% behind the NVIDIA A100 PCIe 40 GB, which scores 162504, and 9.3% ahead of the AMD Instinct MI100, which scores 139035. These figures show that the A10G is a high-end compute card, competitive with the best accelerators of its generation.

The AMD Radeon RX 7900M, by contrast, has an average benchmark score of 97487, placing it in the 94th percentile. Its nearest rivals include the AMD Radeon Pro VII, which scores 97131 and is nearly identical at 0.4% ahead, and the NVIDIA Quadro RTX 6000, which leads by 4.3% with a score of 101872. The RX 7900M sits 5.4% ahead of the AMD Radeon Instinct MI60, which scores 92466, and 6.3% ahead of the NVIDIA RTX A4500, which scores 91671. This positioning shows that the RX 7900M, despite being a mobile part, holds its own against professional desktop cards, though its average score is dragged down by the absence of a Vulkan result in its own benchmark set (the average is based only on its OpenCL and 3DMark scores).

The head-to-head data reveals a clear pattern: the A10G dominates in OpenCL compute, while the RX 7900M takes the Vulkan crown. For users who rely heavily on OpenCL for tasks like scientific simulation, machine learning inference, or render farms, the A10G is the obvious choice based on pure performance. For those working in Vulkan-centric environments, such as modern game engines or cross-platform graphics development, the RX 7900M offers a measurable edge.

FAQ

Q: Which GPU has the higher average benchmark score?

A: The NVIDIA A10G has an average benchmark score of 151963, which is significantly higher than the AMD Radeon RX 7900M's 97487. The A10G also ranks in the 97th percentile of all GPUs, while the RX 7900M ranks in the 94th percentile.

Q: How do the two cards compare in Geekbench OpenCL?

A: The NVIDIA A10G wins decisively with a score of 158063 versus 129499 for the AMD Radeon RX 7900M, a 22.1% advantage. This is the largest margin in any head-to-head test between the two.

Q: What about Geekbench Vulkan performance?

A: The AMD Radeon RX 7900M takes the win with a score of 158760, beating the NVIDIA A10G's 145863 by 8.1%. This is the only test where the RX 7900M comes out ahead.

Q: Which GPU has better raw compute throughput in FP32 operations?

A: The AMD Radeon RX 7900M has a higher FP32 rating at 38.52 TFLOPS, compared to the NVIDIA A10G's 31.52 TFLOPS. The RX 7900M also offers FP16 performance of 77.05 TFLOPS (2:1 ratio), while the A10G provides 31.52 TFLOPS in FP16 (1:1 ratio).

Q: What is the memory configuration difference?

A: The NVIDIA A10G has 24 GB of GDDR6 memory on a 384-bit bus, yielding 600.2 GB/s bandwidth. The AMD Radeon RX 7900M has 16 GB of GDDR6 on a 256-bit bus, yielding 576.0 GB/s bandwidth. The A10G offers both more capacity and higher bandwidth.

Q: Which GPU is more power-efficient based on recorded specifications?

A: The NVIDIA A10G has a lower TDP at 150 W compared to the AMD Radeon RX 7900M's 180 W. Relative to their average scores, the A10G delivers 151963 points at 150 W, while the RX 7900M delivers 97487 points at 180 W, indicating the A10G achieves higher performance per watt in the database's measurements.

The Verdict

The data points to a clear split based on workload. The NVIDIA A10G is the superior choice for OpenCL-based compute tasks, as evidenced by its 22.1% lead over the RX 7900M in that benchmark. Its higher average score (151963 vs 97487) and 97th percentile ranking also make it the stronger overall performer in the database's aggregate metrics. For users running scientific simulations, data analytics, or any workload that leverages OpenCL, the A10G's architecture and driver support deliver measurably better results.

The AMD Radeon RX 7900M, however, is the better option for Vulkan-centric workloads. Its 8.1% advantage in Geekbench Vulkan, combined with a higher FP32 throughput (38.52 TFLOPS vs 31.52 TFLOPS), makes it attractive for real-time graphics applications, game development, or any environment that prioritizes the Vulkan API. The RX 7900M also benefits from a newer architecture (RDNA 3.0 vs Ampere) and a more advanced process node (5 nm vs 8 nm), which may offer long-term driver optimization potential.

For users who need a single card for mixed workloads, the NVIDIA A10G is the safer bet due to its higher average score and stronger OpenCL showing. However, the RX 7900M's Vulkan victory cannot be ignored, especially for those whose software stack is built around that API. The choice ultimately hinges on which benchmark aligns with the user's primary use case, as both cards win exactly one head-to-head test.

Specification Differences

The two GPUs differ across nearly every major specification. The NVIDIA A10G uses the GA102 chip with the Ampere architecture, fabricated on an 8 nm process at Samsung, while the AMD Radeon RX 7900M uses the Navi 31 chip with RDNA 3.0 architecture, fabricated on a 5 nm process at TSMC. The A10G has 28,300 million transistors on a 628 mm² die, resulting in a density of 45.1M per mm², while the RX 7900M packs 57,700 million transistors on a 529 mm² die, achieving a density of 109.1M per mm².

Clock speeds differ substantially: the A10G has a base clock of 1320 MHz and a boost clock of 1710 MHz, while the RX 7900M runs at 1825 MHz base and 2090 MHz boost. Memory configurations also diverge: the A10G offers 24 GB of GDDR6 on a 384-bit bus with 600.2 GB/s bandwidth, whereas the RX 7900M offers 16 GB of GDDR6 on a 256-bit bus with 576.0 GB/s bandwidth. The A10G's memory operates at 1563 MHz (12.5 Gbps effective), while the RX 7900M's memory runs at 2250 MHz (18 Gbps effective).

Compute unit counts differ: the A10G has 9216 shading units, 288 TMUs, and 96 ROPs, while the RX 7900M has 4608 shading units, 288 TMUs, and 192 ROPs. Both have 72 ray tracing cores, but the A10G also includes 288 tensor cores, a feature the RX 7900M does not list. Pixel and texture rates favor the RX 7900M at 401.3 GPixel/s and 601.9 GTexel/s, versus the A10G's 164.2 GPixel/s and 492.5 GTexel/s. Power draw is lower on the A10G at 150 W versus 180 W, and the A10G is a single-slot card with an 8-pin EPS connector, while the RX 7900M is an integrated graphics part (IGP) with no power connectors.

The A10G has no display outputs, while the RX 7900M's outputs are portable device dependent. The A10G measures 267 mm (10.5 inches) in length and 112 mm (4.4 inches) in height, while the RX 7900M has no recorded dimensions. The A10G is end-of-life with a release date of 2021-04-11, while the RX 7900M is active with a release date of 2023-10-18. Both support PCIe 4.0 x16, DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4.

Architecture Differences

The NVIDIA A10G is built on the Ampere architecture, a design that emphasizes compute density and server deployment. Its GA102 chip uses a 8 nm process from Samsung, which is older and less dense than the RX 7900M's process. The A10G integrates 28,300 million transistors across a 628 mm² die, with a transistor density of 45.1M per mm². Notably, the A10G includes 288 tensor cores, which are absent from the RX 7900M's specification sheet, making the A10G better suited for AI and deep learning tasks that leverage tensor operations. The A10G's FP16 performance is 31.52 TFLOPS with a 1:1 ratio, meaning it processes FP16 at the same rate as FP32, a design choice that prioritizes consistent throughput across data types.

The AMD Radeon RX 7900M is built on the RDNA 3.0 architecture, a chiplet-based design that focuses on gaming and graphics efficiency. Its Navi 31 chip uses a 5 nm process from TSMC, which is more advanced and allows for 57,700 million transistors on a smaller 529 mm² die, yielding a density of 109.1M per mm², more than double the A10G's density. The RX 7900M has 4608 shading units, half the A10G's count, but compensates with higher clocks (2090 MHz boost vs 1710 MHz) and more ROPs (192 vs 96). Its FP32 throughput is 38.52 TFLOPS, and FP16 is 77.05 TFLOPS with a 2:1 ratio, indicating that FP16 operations run at twice the rate of FP32, a design optimized for graphics workloads that can use packed math.

The absence of tensor cores on the RX 7900M is a critical architectural difference. The A10G's tensor cores provide dedicated hardware for matrix operations, which are essential for neural network inference and training. The RX 7900M instead relies on its general-purpose shaders for such tasks, which may be less efficient. Additionally, the RX 7900M has 72 ray tracing cores, matching the A10G, but its RDNA 3.0 ray tracing implementation is newer and may differ in efficiency. The process node advantage (5 nm vs 8 nm) gives the RX 7900M a thermal and power efficiency edge at the transistor level, but the A10G's lower TDP (150 W vs 180 W) suggests the NVIDIA card is more power-conservative overall.

Where Each One Wins

The NVIDIA A10G wins in OpenCL compute tasks. Its 22.1% lead in Geekbench OpenCL makes it the preferred choice for applications that rely on this API, such as scientific computing, financial modeling, or any CUDA-like workload that can be expressed in OpenCL. The A10G also wins on memory capacity (24 GB vs 16 GB) and bandwidth (600.2 GB/s vs 576.0 GB/s), which is beneficial for large datasets that exceed the RX 7900M's memory pool. The presence of tensor cores gives the A10G a clear edge in AI and machine learning workloads, where matrix multiplications dominate. Its higher average score (151963 vs 97487) and 97th percentile ranking also make it the stronger all-around performer in the database's aggregate metrics.

The AMD Radeon RX 7900M wins in Vulkan graphics and compute workloads. Its 8.1% lead in Geekbench Vulkan, combined with higher pixel and texture rates (401.3 GPixel/s and 601.9 GTexel/s vs 164.2 and 492.5, respectively), makes it better suited for real-time rendering, game engines, and graphics-intensive applications. The RX 7900M's higher FP32 throughput (38.52 TFLOPS vs 31.52 TFLOPS) and FP16 performance (77.05 TFLOPS vs 31.52 TFLOPS) also favor workloads that can utilize packed math, such as certain shader effects or compute shaders. Its newer architecture (RDNA 3.0) and 5 nm process suggest better long-term driver optimization potential, which could yield further performance gains in Vulkan-based software.

The RX 7900M also wins on raw compute density, with more than double the transistor density of the A10G, and it has more ROPs (192 vs 96), which helps with fill-rate-bound scenarios. For users on portable devices, the RX 7900M's integrated design (IGP) and portable device dependent outputs make it a self-contained solution, whereas the A10G requires a server chassis with no display outputs. The RX 7900M is also currently active in production, while the A10G is end-of-life, meaning the AMD card may receive more driver updates and support going forward.