AMD Radeon RX 6800M vs NVIDIA A2 Comparison

The NVIDIA A2 and AMD Radeon RX 6800M represent two distinct philosophies in GPU design: one is a low-power, server-oriented compute accelerator, while the other is a high-performance mobile graphics processor. The recorded data shows a clear performance disparity, but the reasons behind it and the implications for different workloads are worth examining.

Head-to-Head Benchmarks

The database contains two direct comparison points between these GPUs: Geekbench OpenCL and Geekbench Vulkan. In both tests, the AMD Radeon RX 6800M delivers a decisive victory, but the scale of the win reveals a fundamental gap in raw compute capability.

In the Geekbench OpenCL test, the NVIDIA A2 scores 35,357 points, while the AMD Radeon RX 6800M scores 87,621 points. The delta percentage is -59.6%, meaning the AMD part is approximately 148% faster than the NVIDIA A2 in this workload. This is not a marginal difference; it is a generational and architectural chasm. The RX 6800M delivers roughly 2.5 times the performance of the A2 in OpenCL compute tasks.

The Geekbench Vulkan test tells a similar story. The NVIDIA A2 produces a score of 34,023, while the AMD Radeon RX 6800M reaches 94,766. The delta percentage here is -64.1%, indicating the AMD GPU is about 179% faster. This slightly larger gap suggests that the RX 6800M's advantage grows in graphics-oriented API workloads, which is consistent with its design as a mobile gaming part.

It is notably the NVIDIA A2's average benchmark score across all recorded tests is 34,690, placing it in the 79th percentile of all GPUs. The AMD Radeon RX 6800M, despite its massive wins in these two tests, has an average score of 28,874 and sits in the 74th percentile. This apparent contradiction stems from the fact that the RX 6800M's average is dragged down by a broader set of benchmark results, including some low scores in specific legacy tests. The A2, with only two recorded benchmarks, benefits from a narrower and more consistent dataset.

Where Each One Wins

The AMD Radeon RX 6800M wins every head-to-head benchmark recorded in the database, making its supremacy in raw performance absolute. Its advantage is most pronounced in Vulkan, where the 64.1% delta suggests strong driver optimization and architectural efficiency for modern graphics APIs. The OpenCL win, while slightly smaller, still demonstrates a commanding lead in general-purpose compute.

The NVIDIA A2 wins in a different category: efficiency. With a TDP of 60 W compared to the RX 6800M's 145 W, the A2 delivers its 4.531 TFLOPS of FP32 performance at less than half the power draw. This makes it a compelling option for dense server environments where power density and thermal constraints are critical. The A2 is a single-slot card with no power connectors, requiring only a 250 W power supply, whereas the RX 6800M is an IGP (integrated graphics processor) designed for laptops, with power delivery handled by the host system.

For workloads that rely on the NVIDIA ecosystem, the A2 has a clear edge. It features 40 tensor cores, which the RX 6800M lacks entirely. This makes the A2 the only viable choice for AI inference or machine learning tasks that leverage TensorRT or CUDA, despite its lower raw compute throughput. The A2 also has a higher transistor density at 43.5M per mm² compared to the RX 6800M's 51.3M per mm², though this metric favors the AMD chip due to its larger and denser design.

Architecture Differences

The architectural divide between these two GPUs is stark. The NVIDIA A2 is built on the Ampere architecture, specifically the GA107 chip, manufactured on an 8 nm process by Samsung. It packs 8,700 million transistors into a 200 mm² die. The AMD Radeon RX 6800M uses the RDNA 2.0 architecture with the Navi 22 chip, fabricated on a 7 nm process by TSMC. This chip houses 17,200 million transistors on a 335 mm² die, nearly doubling the transistor count and increasing the die area by 67.5%.

These process and design choices have direct performance implications. The RX 6800M's 7 nm process allows for higher clock speeds: its base clock is 2116 MHz, boosting to 2390 MHz, with a game clock of 2300 MHz. The A2 operates at a more modest 1440 MHz base and 1770 MHz boost. This clock advantage, combined with double the shading units (2560 versus 1280), explains the massive performance gap.

Memory architecture also diverges significantly. The A2 has 16 GB of GDDR6 on a 128-bit bus, yielding 200.1 GB/s of bandwidth. The RX 6800M has 12 GB of GDDR6 on a 192-bit bus, delivering 384.0 GB/s. The RX 6800M's memory runs at 2000 MHz (16 Gbps effective) compared to the A2's 1563 MHz (12.5 Gbps effective). Despite having less capacity, the RX 6800M offers nearly double the bandwidth, which is crucial for high-resolution gaming and compute workloads.

The compute resources tell a similar story. The A2 has 40 texture mapping units (TMUs) and 32 render output units (ROPs), while the RX 6800M has 160 TMUs and 64 ROPs. Pixel rate and texture rate follow suit: the A2 achieves 56.64 GPixel/s and 70.80 GTexel/s, while the RX 6800M hits 153.0 GPixel/s and 382.4 GTexel/s. The RX 6800M's FP32 throughput is 12.24 TFLOPS versus the A2's 4.531 TFLOPS, a 2.7x advantage. In FP16, the RX 6800M reaches 24.47 TFLOPS with a 2:1 ratio, while the A2 is limited to 4.531 TFLOPS at a 1:1 ratio.

Ray tracing hardware also differs. The RX 6800M has 40 ray tracing cores, while the A2 has only 10. This gives the AMD part a substantial edge in ray-traced workloads, though neither is a dedicated high-end RT solution. The A2's 40 tensor cores are its unique asset, enabling AI acceleration that the RX 6800M cannot offer.

Specification Differences

The two GPUs differ across nearly every measurable specification. The most consequential differences are:

• Process node: A2 at 8 nm (Samsung) versus RX 6800M at 7 nm (TSMC)
• Transistors: A2 at 8,700 million versus RX 6800M at 17,200 million
• Die size: A2 at 200 mm² versus RX 6800M at 335 mm²
• Base clock: A2 at 1440 MHz versus RX 6800M at 2116 MHz
• Boost clock: A2 at 1770 MHz versus RX 6800M at 2390 MHz
• Memory size: A2 at 16 GB versus RX 6800M at 12 GB
• Memory bus width: A2 at 128-bit versus RX 6800M at 192-bit
• Memory bandwidth: A2 at 200.1 GB/s versus RX 6800M at 384.0 GB/s
• Shading units: A2 at 1280 versus RX 6800M at 2560
• TMUs: A2 at 40 versus RX 6800M at 160
• ROPs: A2 at 32 versus RX 6800M at 64
• RT cores: A2 at 10 versus RX 6800M at 40
• Tensor cores: A2 at 40 versus RX 6800M at none
• FP32: A2 at 4.531 TFLOPS versus RX 6800M at 12.24 TFLOPS
• FP16: A2 at 4.531 TFLOPS versus RX 6800M at 24.47 TFLOPS
• Pixel rate: A2 at 56.64 GPixel/s versus RX 6800M at 153.0 GPixel/s
• Texture rate: A2 at 70.80 GTexel/s versus RX 6800M at 382.4 GTexel/s
• TDP: A2 at 60 W versus RX 6800M at 145 W
• Bus interface: A2 at PCIe 4.0 x8 versus RX 6800M at PCIe 4.0 x16
• Display outputs: A2 has none versus RX 6800M being portable device dependent

The A2 and RX 6800M share the same API support: both support DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. Both are end-of-life products, with the A2 released on November 9, 2021, and the RX 6800M on May 30, 2021. The A2's predecessor is the Quadro Turing, with the Workstation Ada as its successor. The RX 6800M's predecessor is Polaris Mobile, and it has no recorded successor.

FAQ

Q: Which GPU is faster in raw compute performance?

A: The AMD Radeon RX 6800M is significantly faster. In Geekbench OpenCL, it scores 87,621 versus the NVIDIA A2's 35,357, a delta of -59.6%. In Vulkan, it scores 94,766 versus 34,023, a delta of -64.1%.

Q: Does the NVIDIA A2 have any unique advantages?

A: Yes. The A2 has 40 tensor cores, which the RX 6800M does not have at all. It also has a much lower TDP at 60 W versus 145 W, making it suitable for power-constrained environments.

Q: Why is the RX 6800M's average benchmark score lower despite winning head-to-head tests?

A: The RX 6800M has 11 recorded benchmarks, including low scores in legacy tests (e.g., PassMark DirectX 9 at 147), which drag down its average to 28,874. The A2 has only 2 benchmarks, both relatively high, giving it an average of 34,690.

Q: Which GPU has more memory bandwidth?

A: The AMD Radeon RX 6800M has 384.0 GB/s, nearly double the NVIDIA A2's 200.1 GB/s, due to its wider 192-bit bus and faster memory clock.

Q: Can either GPU be used for machine learning workloads?

A: The NVIDIA A2 is better suited due to its 40 tensor cores and CUDA ecosystem support. The RX 6800M lacks tensor cores, though its high FP32 and FP16 throughput could still handle some compute tasks.

Q: What is the performance percentile ranking for each GPU?

A: The NVIDIA A2 ranks in the 79th percentile of all GPUs, while the AMD Radeon RX 6800M ranks in the 74th percentile.

The Verdict

The data presents a clear picture: the AMD Radeon RX 6800M is the superior performer in every direct benchmark comparison. Its 2.5x to 2.8x advantage in OpenCL and Vulkan scores, combined with double the shading units, higher clocks, and nearly double the memory bandwidth, makes it the obvious choice for graphics-intensive and general compute workloads. The RX 6800M's 12.24 TFLOPS FP32 performance and 24.47 TFLOPS FP16 performance dwarf the A2's 4.531 TFLOPS in both metrics.

However, the NVIDIA A2 serves a different purpose. Its 60 W TDP, single-slot form factor, and lack of display outputs position it as a server-side accelerator for inference tasks. The presence of 40 tensor cores gives it a capability the RX 6800M cannot match: hardware-accelerated AI processing. For users running CUDA-based machine learning pipelines or needing a low-power compute card in a dense server, the A2 is the only viable option despite its lower raw performance.

For gamers, content creators, or anyone needing maximum graphics throughput in a mobile form factor, the RX 6800M is the definitive choice. Its 2.7x FP32 advantage and superior memory subsystem ensure it handles demanding workloads with ease. The A2, by contrast, is a niche product for specialized AI acceleration where power efficiency trumps raw speed. The benchmark data leaves no ambiguity: the RX 6800M wins on performance, while the A2 wins on efficiency and AI-specific features.