AMD Instinct MI300X vs Intel Arc Pro A60M Comparison

The Verdict

The AMD Instinct MI300X and Intel Arc Pro A60M occupy entirely separate segments of the accelerator market, and the recorded data confirms they should never be considered direct substitutes. The MI300X is a data-center compute accelerator with a benchmark score of 317,994 in Geekbench OpenCL, placing it in the 100th percentile of all GPUs in the database. The Arc Pro A60M, by contrast, has no recorded benchmark scores, an average benchmark score of 0, and sits at the 50th percentile. Any workload that demands raw compute throughput belongs to the MI300X; the Arc Pro A60M is a mobile professional graphics processor designed for portability and display output, not for competing in dense compute tasks.

The MI300X leads in every measurable compute metric. Its FP32 output of 81.72 TFLOPS is roughly 15 times the Arc Pro A60M's 5.325 TFLOPS. Memory capacity differs by a factor of 24: 192 GB of HBM3 versus 8 GB of GDDR6. Memory bandwidth is 5.32 TB/s versus 256.0 GB/s, a 20-fold gap. The MI300X uses a 5 nm TSMC process with 153,000 million transistors on a 1017 mm² die, while the A60M uses a 6 nm TSMC process with 11,500 million transistors on a 269 mm² die. The power envelope tells the same story: 750 W for the MI300X versus 95 W for the A60M. The MI300X also requires a 1150 W suggested power supply and uses an OAM module slot with no power connectors, while the A60M is an IGP with no suggested PSU listed.

The verdict is straightforward. For AI training, large-model inference, or high-throughput scientific computing, the MI300X is the only choice in this comparison. For a mobile workstation GPU with DirectX 12 Ultimate support, OpenGL 4.6, Vulkan 1.4, and portable device dependent display outputs, the A60M is the only option that provides those features. The MI300X has no display outputs at all and lists its DirectX, OpenGL, and Vulkan APIs as N/A. The two accelerators do not overlap in function, and the data reflects that separation.

Architecture Differences

The MI300X uses the CDNA 3.0 architecture on the Aqua Vanjaram chip, built on a 5 nm process at TSMC. It packs 153,000 million transistors into a 1017 mm² die, yielding a transistor density of 150.4 million per square millimeter. Its memory subsystem is HBM3 with 192 GB capacity, an 8192-bit bus, and 5.32 TB/s bandwidth. The chip has 19,456 shading units, 1,216 texture mapping units, and zero ROPs. Its pixel rate is 0 MPixel/s and its texture rate is 2,553.6 GTexel/s. FP32 compute is 81.72 TFLOPS, FP16 is also 81.72 TFLOPS at a 1:1 ratio. The base clock is 1000 MHz and boost clock is 2100 MHz. Memory runs at 1300 MHz with 5.2 Gbps effective data rate. The MI300X belongs to the Instinct (MIx) generation, was released on December 5, 2023, and succeeds the Radeon Instinct line.

The Arc Pro A60M uses the Xe-HPG architecture on the DG2-256 chip, built on a 6 nm process at TSMC. It has 11,500 million transistors on a 269 mm² die, giving a transistor density of 42.8 million per square millimeter. Its memory is GDDR6 with 8 GB capacity, a 128-bit bus, and 256.0 GB/s bandwidth. The chip has 2,048 shading units, 128 TMUs, 64 ROPs, and 16 ray tracing cores. Pixel rate is 83.20 GPixel/s and texture rate is 166.4 GTexel/s. FP32 compute is 5.325 TFLOPS, FP16 is 10.65 TFLOPS at a 2:1 ratio. Base clock is 900 MHz, boost clock is 1300 MHz, and memory runs at 2000 MHz with 16 Gbps effective data rate. The A60M belongs to the Alchemist (Pro-Series Mobile) generation, was released on June 5, 2023, and its production status is Active.

The architectural philosophies diverge sharply. CDNA 3.0 prioritizes raw compute throughput, massive memory capacity, and bandwidth for data-center workloads, sacrificing display output and graphics APIs entirely. Xe-HPG prioritizes a balanced mobile professional GPU with ray tracing support, full graphics API coverage, and efficient power use. The MI300X has no ray tracing cores listed, while the A60M has 16. The MI300X has no ROPs, while the A60M has 64. The MI300X's FP16 runs at a 1:1 ratio with FP32, indicating compute-oriented throughput, while the A60M's FP16 runs at 2:1, a more graphics-oriented ratio.

FAQ

Q: Which GPU has higher raw compute performance?

A: The MI300X delivers 81.72 TFLOPS FP32 and 81.72 TFLOPS FP16, while the A60M delivers 5.325 TFLOPS FP32 and 10.65 TFLOPS FP16. The MI300X leads FP32 by roughly 15 times.

Q: How do the memory subsystems compare?

A: The MI300X has 192 GB of HBM3 on an 8192-bit bus with 5.32 TB/s bandwidth. The A60M has 8 GB of GDDR6 on a 128-bit bus with 256.0 GB/s bandwidth. The MI300X has 24 times the capacity and about 20 times the bandwidth.

Q: Which GPU supports display outputs?

A: The A60M lists its display outputs as portable device dependent and supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4. The MI300X has no display outputs and lists all graphics APIs as N/A.

Q: What is the power requirement difference?

A: The MI300X has a TDP of 750 W and a suggested PSU of 1150 W, using an OAM module slot. The A60M has a TDP of 95 W and is an IGP with no suggested PSU listed.

Q: How do the benchmark scores compare?

A: The MI300X scores 317,994 in Geekbench OpenCL and sits in the 100th percentile of all GPUs. The A60M has no recorded benchmark scores, an average score of 0, and sits in the 50th percentile.

Q: What are the process node and transistor differences?

A: The MI300X uses a 5 nm TSMC process with 153,000 million transistors on a 1017 mm² die. The A60M uses a 6 nm TSMC process with 11,500 million transistors on a 269 mm² die.

Specification Differences

The two accelerators differ in nearly every recorded specification field. The MI300X uses a 5 nm process node; the A60M uses 6 nm. Transistor count is 153,000 million versus 11,500 million. Die size is 1017 mm² versus 269 mm². Transistor density is 150.4 million per mm² versus 42.8 million per mm². Base clock is 1000 MHz versus 900 MHz. Boost clock is 2100 MHz versus 1300 MHz. Memory clock is 1300 MHz with 5.2 Gbps effective versus 2000 MHz with 16 Gbps effective.

Memory size is 192 GB versus 8 GB. Memory type is HBM3 versus GDDR6. Bus width is 8192 bit versus 128 bit. Memory bandwidth is 5.32 TB/s versus 256.0 GB/s. Shading units are 19,456 versus 2,048. TMUs are 1,216 versus 128. ROPs are 0 versus 64. Ray tracing cores are not listed for the MI300X versus 16 for the A60M. Pixel rate is 0 MPixel/s versus 83.20 GPixel/s. Texture rate is 2,553.6 GTexel/s versus 166.4 GTexel/s. FP32 is 81.72 TFLOPS versus 5.325 TFLOPS. FP16 is 81.72 TFLOPS versus 10.65 TFLOPS.

TDP is 750 W versus 95 W. Slot width is OAM Module versus IGP. Power connectors are None for the MI300X, not listed for the A60M. Suggested PSU is 1150 W versus not listed. Bus interface is PCIe 5.0 x16 versus PCIe 4.0 x16. Display outputs are none versus portable device dependent. DirectX support is N/A versus 12 Ultimate (12_2). OpenGL is N/A versus 4.6. Vulkan is N/A versus 1.4. Production status is not listed for the MI300X versus Active for the A60M. Release dates differ: December 5, 2023 for the MI300X versus June 5, 2023 for the A60M.

Head-to-Head Benchmarks

The head-to-head benchmark list is empty, and the win counts are 0 for both accelerators. The only recorded benchmark in the database is the MI300X's Geekbench OpenCL score of 317,994, which places it in the 100th percentile of all GPUs. The A60M has no recorded benchmark scores, so direct numerical comparison relies on the MI300X's nearest rivals instead.

The MI300X's nearest rival, the NVIDIA H200 NVL, averages 334,891 with a delta of -5 percent relative to the MI300X. The NVIDIA B200 averages 345,482 with a delta of -8 percent. The NVIDIA L40S averages 295,763 with a delta of 7.5 percent, meaning the MI300X leads it by 7.5 percent. The NVIDIA RTX 6000 Ada Generation averages 287,237 with a delta of 10.7 percent, meaning the MI300X leads it by 10.7 percent. These deltas place the MI300X slightly below the H200 NVL and B200 but clearly above the L40S and RTX 6000 Ada Generation.

The A60M has no nearest rivals listed and no benchmark scores, so its competitive position can only be inferred from its percentile rank of 50. That placement indicates a mid-pack standing across all GPUs in the database, far below the MI300X's 100th percentile. The compute gap between the two accelerators is consistent with their architectural roles: the MI300X is built for maximum throughput, while the A60M is built for professional mobile graphics with moderate compute.

Where Each One Wins

The MI300X wins in every compute-oriented category. Its FP32 throughput of 81.72 TFLOPS, FP16 throughput of 81.72 TFLOPS, memory capacity of 192 GB, and bandwidth of 5.32 TB/s position it for large-scale AI inference, model training, and high-bandwidth data processing. Its 100th percentile benchmark standing and Geekbench OpenCL score of 317,994 confirm its top-tier placement among all GPUs. The MI300X also leads in transistor count, die size, transistor density, shading units, TMUs, texture rate, and bus interface width. Its PCIe 5.0 x16 interface provides double the per-lane bandwidth of the A60M's PCIe 4.0 x16.

The A60M wins in categories related to graphics output and mobile integration. It supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, while the MI300X lists all three as N/A. The A60M has 64 ROPs and a pixel rate of 83.20 GPixel/s, whereas the MI300X has 0 ROPs and a pixel rate of 0 MPixel/s. The A60M has 16 ray tracing cores, which the MI300X does not list. Its display outputs are portable device dependent, making it suitable for mobile workstations, while the MI300X has no display outputs at all. The A60M's 95 W TDP and IGP form factor allow integration into portable systems, contrasted with the MI300X's 750 W TDP and OAM module slot. Its FP16 ratio of 2:1 also indicates more balanced graphics and compute throughput for a mobile part.

The production status of the A60M is Active, while the MI300X's production status is not listed. The A60M's higher FP16 to FP32 ratio, ray tracing support, and graphics API coverage make it the appropriate choice for professional mobile graphics workloads. The MI300X's massive compute and memory resources make it the appropriate choice for data-center acceleration. The two accelerators do not compete for the same tasks, and each wins in its respective domain.