AMD Radeon Instinct MI60 vs NVIDIA A10M Comparison

The NVIDIA A10M and AMD Radeon Instinct MI60 are both end-of-life server accelerators, but they target very different workloads. The benchmark data places the A10M in the 96th percentile of all GPUs with an average score of 135,230, while the MI60 sits in the 93rd percentile with an average of 92,466. The single head-to-head result shows a decisive 46.2% lead for the A10M in OpenCL performance, yet the MI60 counters with double the memory capacity and a vastly wider memory bus.

The Verdict

The NVIDIA A10M is the clear performance winner. Its Geekbench OpenCL score of 135,230 beats the MI60’s 92,488 by 46.2%. For compute tasks that rely on raw FP32 throughput, the A10M delivers 23.44 TFLOPS versus the MI60’s 14.75 TFLOPS, a 58.9% advantage. The A10M also has 7,168 shading units compared to 4,096, and its 56 RT cores and 224 tensor cores provide hardware acceleration the MI60 lacks entirely.

However, the MI60 is the memory-capacity champion. It offers 32 GB of HBM2 on a 4096-bit bus, yielding 1.02 TB/s of bandwidth. The A10M has 20 GB of GDDR6 on a 320-bit bus, producing 500.2 GB/s. For datasets that exceed 20 GB, the MI60’s larger frame buffer is the deciding factor, even at lower compute throughput.

Pick the A10M if your workloads fit within 20 GB and demand maximum FP32, ray tracing, or tensor performance. Pick the MI60 if you need 32 GB of VRAM and the highest memory bandwidth available, and can tolerate a 46.2% compute deficit in OpenCL.

Architecture Differences

The A10M uses the GA102 chip built on Samsung’s 8 nm process, packing 28,300 million transistors into a 628 mm² die. This yields a transistor density of 45.1M per mm². The MI60 uses the Vega 20 chip on TSMC’s 7 nm process, with 13,230 million transistors on a 331 mm² die, for a density of 40.0M per mm². The A10M’s die is nearly twice as large and holds more than twice the transistors.

The A10M is based on the Ampere architecture, which includes 56 RT cores and 224 tensor cores. The MI60 is based on GCN 5.1 and has no equivalent hardware for ray tracing or tensor operations. This is a fundamental feature gap: the A10M supports DirectX 12 Ultimate (12_2) and Vulkan 1.4, while the MI60 tops out at DirectX 12 (12_1) and Vulkan 1.3.

Clock speeds favor the MI60. The MI60 has a base clock of 1200 MHz and a boost of 1800 MHz, versus the A10M’s 975 MHz base and 1635 MHz boost. However, the A10M compensates with far more execution units. The MI60 also has more texture mapping units (256 vs. 224), resulting in a higher texture rate of 460.8 GTexel/s versus 366.2 GTexel/s. The A10M wins pixel rate, 130.8 GPixel/s against 115.2 GPixel/s, thanks to its 80 ROPs versus 64.

Memory architecture diverges sharply. The A10M uses 20 GB of GDDR6 with a 320-bit bus, achieving 500.2 GB/s. The MI60 uses 32 GB of HBM2 with a 4096-bit bus, delivering 1.02 TB/s — more than double the bandwidth. The MI60’s memory clock is 1000 MHz (2 Gbps effective), while the A10M’s is 1563 MHz (12.5 Gbps effective). The MI60’s HBM2 advantage is bandwidth and capacity; the A10M’s GDDR6 advantage is simpler integration.

Power and physical design differ as well. The A10M is a single-slot card with a 150 W TDP and an 8-pin EPS connector, requiring a 450 W PSU. The MI60 is a dual-slot card with a 300 W TDP, using 1x 6-pin + 1x 8-pin connectors, and needs a 700 W PSU. Both are 267 mm long, but the A10M is 112 mm tall versus the MI60’s 111 mm. The A10M has no display outputs; the MI60 includes one mini-DisplayPort 1.4a.

Head-to-Head Benchmarks

The only direct benchmark comparison is Geekbench OpenCL, where the A10M scores 135,230 against the MI60’s 92,488. This is a 46.2% delta in favor of the A10M. That margin is substantial and consistent with the FP32 throughput gap: 23.44 TFLOPS versus 14.75 TFLOPS, a 58.9% advantage. The A10M’s higher shading unit count (7,168 vs. 4,096) and tensor cores clearly drive this result.

The MI60 has a separate Geekbench Vulkan score of 92,444, which is nearly identical to its OpenCL score of 92,488. The A10M has no Vulkan benchmark listed, so cross-API comparison is incomplete. However, the MI60’s Vulkan and OpenCL scores are within 0.05% of each other, indicating consistent performance across APIs.

The A10M’s nearest rivals in the database are the NVIDIA RTX 4000 Ada Generation (135,218, 0% delta), AMD Radeon PRO W6800 (135,396, -0.1%), AMD Radeon Pro W6800X Duo (135,774, -0.4%), and AMD Radeon PRO V620 (136,472, -0.9%). All four are within 1% of the A10M’s score, placing the A10M in a tight performance cluster.

The MI60’s nearest rivals are the NVIDIA RTX A4500 (91,671, +0.9%), NVIDIA RTX A4500 Mobile (91,134, +1.5%), AMD Radeon Pro VII (97,131, -4.8%), and AMD Radeon RX 7900M (97,487, -5.2%). The MI60 beats the A4500 cards by less than 2%, but trails the Pro VII and RX 7900M by nearly 5%.

FAQ

Q: Which GPU has higher FP32 compute?

A: The NVIDIA A10M, with 23.44 TFLOPS versus the MI60’s 14.75 TFLOPS, a 58.9% advantage.

Q: Does the MI60 support ray tracing or tensor cores?

A: No. The MI60 has no RT cores or tensor cores listed, while the A10M has 56 RT cores and 224 tensor cores.

Q: Which card offers more memory bandwidth?

A: The MI60, with 1.02 TB/s from 32 GB of HBM2 on a 4096-bit bus. The A10M has 500.2 GB/s from 20 GB of GDDR6 on a 320-bit bus.

Q: What is the power consumption difference?

A: The A10M has a 150 W TDP and requires a 450 W PSU. The MI60 has a 300 W TDP and requires a 700 W PSU.

Q: Which card is the better value based on OpenCL scores?

A: The A10M wins the only head-to-head test with a 46.2% higher score, making it the higher-performing option in OpenCL compute.

Q: Are both cards still in production?

A: No. Both are listed as end-of-life products.

Where Each One Wins

The NVIDIA A10M wins in raw compute performance. Its Geekbench OpenCL score of 135,230 dwarfs the MI60’s 92,488. The 23.44 TFLOPS FP32 throughput is ideal for single-precision workloads like AI inference, graphics rendering, and simulation. The 56 RT cores handle ray-traced rendering, and the 224 tensor cores accelerate matrix operations. The A10M also excels in API support, with DirectX 12 Ultimate and Vulkan 1.4, and its 150 W TDP makes it far easier to cool and power in dense servers. The single-slot design and 8-pin EPS connector simplify deployment. For any workload where FP32 or tensor performance matters, the A10M is the choice.

The AMD Radeon Instinct MI60 wins in memory capacity and bandwidth. Its 32 GB of HBM2 is 60% more than the A10M’s 20 GB. The 1.02 TB/s bandwidth is more than double the A10M’s 500.2 GB/s. This makes the MI60 superior for large-scale data processing, such as training models with datasets exceeding 20 GB, or for HPC tasks that stream massive amounts of data through the GPU. The MI60 also has a higher texture rate (460.8 GTexel/s vs. 366.2 GTexel/s), which helps in texture-heavy workloads. Its base and boost clocks are higher (1200/1800 MHz vs. 975/1635 MHz), and the included mini-DisplayPort output allows direct display connection, which the A10M lacks.

The FP16 picture is nuanced. The A10M lists FP16 at 23.44 TFLOPS (1:1 ratio with FP32), meaning it does not gain a throughput advantage in half precision. The MI60 lists FP16 at 29.49 TFLOPS (2:1 ratio), which is 25.8% higher than its FP32 rate. So, while the A10M wins FP32, the MI60 actually has higher raw FP16 compute. For workloads that can use FP16 arithmetic — such as certain machine learning kernels — the MI60’s 29.49 TFLOPS exceeds the A10M’s 23.44 TFLOPS.

Power efficiency favors the A10M. The A10M achieves its 135,230 OpenCL score at 150 W, while the MI60 reaches 92,488 at 300 W. Per watt, the A10M delivers roughly 901 points per watt versus the MI60’s 308 points per watt — a nearly 3x efficiency gap. The A10M’s lower TDP also reduces cooling requirements and allows more cards per server chassis.

Physical compatibility differs. Both cards are 267 mm long, but the A10M is single-slot and the MI60 is dual-slot. The A10M uses an 8-pin EPS connector, while the MI60 needs 1x 6-pin plus 1x 8-pin. The A10M is 112 mm tall; the MI60 is 111 mm. Neither has a width specified. For dense GPU servers, the A10M’s single-slot profile is a major advantage.

In summary: The A10M is the compute king with better performance, efficiency, and modern features. The MI60 is the memory giant, offering double the VRAM and bandwidth for large datasets, plus higher FP16 throughput. Choose based on whether your bottleneck is compute (A10M) or memory capacity/bandwidth (MI60).