AMD Instinct MI300X vs AMD Radeon Instinct MI300A Comparison

Head-to-Head Benchmarks

The database contains only one recorded benchmark result for the AMD Instinct MI300X: a Geekbench OpenCL score of 317,994. This result places the MI300X at the 100th percentile among all GPUs tracked in the database, meaning it outperforms every other recorded GPU in that particular test. The MI300A has no recorded benchmark scores in the database, so direct head-to-head comparisons between the two AMD accelerators cannot be drawn from measurements. Instead, the MI300X can be positioned against its nearest rivals, which provides context for interpreting its single score.

Against the NVIDIA H200 NVL, the MI300X trails by 5 percent. The H200 NVL records an average score of 334,891, which is 16,897 points higher than the MI300X. This is a modest gap, suggesting the MI300X remains competitive in OpenCL workloads even when facing a leading NVIDIA data center part. Against the NVIDIA B200, the deficit grows to 8 percent. The B200 averages 345,482, a lead of 27,488 points over the MI300X. While the MI300X does not top these two NVIDIA accelerators, the differences are not overwhelming in percentage terms.

The MI300X shows stronger results when compared to other NVIDIA offerings. It leads the NVIDIA L40S by 7.5 percent. The L40S averages 295,763, which is 22,231 points lower than the MI300X score. Against the NVIDIA RTX 6000 Ada Generation, the MI300X leads by 10.7 percent. The RTX 6000 Ada averages 287,237, a deficit of 30,757 points. These wins indicate that the MI300X delivers a substantial OpenCL performance advantage over mid-range and workstation-class NVIDIA accelerators, even though it falls slightly behind the top-tier H200 NVL and B200.

The MI300A, with no recorded benchmark scores and an average benchmark score of zero, cannot be compared numerically to the MI300X or to any rival. Its percentile ranking of 50 reflects the absence of data rather than measured performance. Any analysis of the MI300A must therefore rely on architectural specifications rather than benchmark outcomes.

Architecture Differences

Both the AMD Instinct MI300X and the AMD Radeon Instinct MI300A share the same fundamental silicon. They use the Aqua Vanjaram chip, built on the CDNA 3.0 architecture, and are fabricated on a 5 nm process at TSMC. Both contain 153,000 million transistors on a die size of 1017 mm², yielding a transistor density of 150.4M per mm². The core configuration is identical: 19,456 shading units, 1,216 texture mapping units, and zero raster operations units. The pixel rate is 0 MPixel/s and the texture rate is 2,553.6 GTexel/s for both parts. FP32 compute is also identical at 81.72 TFLOPS.

The critical architectural difference lies in memory clock speed and FP16 throughput. The MI300X runs its HBM3 memory at 1300 MHz, which translates to 5.2 Gbps effective. The MI300A runs its memory at 2525 MHz, or 10.1 Gbps effective. This nearly doubles the memory clock, and the MI300A consequently delivers 10.3 TB/s of memory bandwidth compared to 5.32 TB/s for the MI300X. Both use 192 GB of HBM3 memory across an 8192 bit bus, so the bandwidth advantage for the MI300A comes entirely from the higher memory clock.

FP16 performance also diverges sharply. The MI300X delivers 81.72 TFLOPS of FP16 at a 1:1 ratio with its FP32 output. The MI300A delivers 653.7 TFLOPS of FP16 at an 8:1 ratio. This means the MI300A is capable of 8 times the FP16 throughput of the MI300X, a substantial difference for workloads that rely heavily on reduced-precision arithmetic. The 8:1 ratio indicates that the MI300A's FP16 units are likely structured differently, or that the accelerator employs different precision scaling, despite sharing the same shading unit count.

Both accelerators have a TDP of 750 W, use an OAM Module slot width, have no power connectors, and suggest a 1150 W PSU. Both use a PCIe 5.0 x16 bus interface and have no display outputs. The MI300X lists its DirectX, OpenGL, and Vulkan APIs as N/A. The MI300A lists these APIs as null, which is functionally equivalent: neither part exposes graphics APIs. The release date for both is 2023-12-05. The MI300X lists its predecessor as Radeon Instinct, while the MI300A lists FirePro Data Center as its predecessor.

FAQ

Q: Which accelerator has higher memory bandwidth?

A: The AMD Radeon Instinct MI300A has 10.3 TB/s of memory bandwidth, while the AMD Instinct MI300X has 5.32 TB/s. Both use 192 GB of HBM3 memory on an 8192 bit bus, but the MI300A's memory clock of 2525 MHz (10.1 Gbps effective) is much higher than the MI300X's 1300 MHz (5.2 Gbps effective).

Q: Do the two accelerators have the same compute cores?

A: Yes, both have 19,456 shading units and 1,216 texture mapping units. Both have zero ROPs and a pixel rate of 0 MPixel/s. The texture rate is identical at 2,553.6 GTexel/s, and FP32 performance is the same at 81.72 TFLOPS.

Q: How does FP16 performance compare?

A: The MI300A delivers 653.7 TFLOPS of FP16 at an 8:1 ratio, which is 8 times the FP16 output of the MI300X. The MI300X delivers 81.72 TFLOPS of FP16 at a 1:1 ratio with its FP32 performance.

Q: What is the power requirement for these accelerators?

A: Both have a TDP of 750 W and suggest a 1150 W PSU. Both use an OAM Module slot width and have no power connectors, meaning they draw power through the OAM socket rather than external cables.

Q: Are there any benchmark scores available for the MI300A?

A: No. The database has no benchmark entries for the MI300A, and its average benchmark score is 0. The MI300X has one recorded Geekbench OpenCL score of 317,994, which places it at the 100th percentile.

Q: Do these accelerators support graphics APIs?

A: No. The MI300X lists DirectX, OpenGL, and Vulkan as N/A. The MI300A lists these APIs as null. Neither part has display outputs, confirming they are compute-only accelerators for data center use.

Specification Differences

The following specifications differ between the AMD Instinct MI300X and the AMD Radeon Instinct MI300A:

• Memory clock: The MI300X runs at 1300 MHz (5.2 Gbps effective). The MI300A runs at 2525 MHz (10.1 Gbps effective).
• Memory bandwidth: The MI300X delivers 5.32 TB/s. The MI300A delivers 10.3 TB/s.
• FP16 performance: The MI300X delivers 81.72 TFLOPS at a 1:1 ratio. The MI300A delivers 653.7 TFLOPS at an 8:1 ratio.
• API field values: The MI300X lists DirectX, OpenGL, and Vulkan as N/A. The MI300A lists them as null.
• Predecessor: The MI300X lists Radeon Instinct. The MI300A lists FirePro Data Center.
• Generation label: The MI300X is labeled "Instinct (MIx)". The MI300A is labeled "Radeon Instinct (MIx)".

All other recorded specifications are identical. Both use the Aqua Vanjaram chip on CDNA 3.0, a 5 nm TSMC process, 153,000 million transistors, a 1017 mm² die, 19,456 shading units, 1,216 TMUs, 0 ROPs, 192 GB HBM3, an 8192 bit bus, 2,553.6 GTexel/s texture rate, 81.72 TFLOPS FP32, 750 W TDP, OAM Module slot, no power connectors, a 1150 W suggested PSU, PCIe 5.0 x16, no display outputs, and a release date of 2023-12-05.

Where Each One Wins

The MI300X wins in any scenario where a recorded benchmark score is required. Its Geekbench OpenCL score of 317,994 is the only measured performance data available between the two parts. It also holds a 100th percentile ranking among all GPUs, which means it outperforms every other accelerator with recorded data in that test. For users who rely on database-verified performance, the MI300X is the only one of the two with evidence of compute capability.

The MI300A wins in memory-bound and reduced-precision workloads based on specification differences. Its 10.3 TB/s memory bandwidth is nearly double the MI300X's 5.32 TB/s. For workloads that stream large datasets through memory, such as large language model inference with high batch sizes or scientific simulations with massive matrices, the MI300A's bandwidth advantage could translate into faster execution. Its FP16 throughput of 653.7 TFLOPS is 8 times the MI300X's 81.72 TFLOPS, which gives it a clear edge in mixed-precision training or inference where FP16 arithmetic dominates.

The MI300X does not have any specification advantage over the MI300A. Its memory clock, bandwidth, and FP16 output are all lower. Its only advantage is the existence of a recorded benchmark score and the associated percentile ranking. The MI300A also has no recorded score, so its wins are purely theoretical based on its specifications.

The Verdict

The data shows two accelerators that share identical hardware foundations but diverge in memory and precision capabilities. The MI300X is the only one with a measured benchmark result: 317,994 in Geekbench OpenCL, placing it at the 100th percentile and ahead of the NVIDIA L40S by 7.5 percent and the NVIDIA RTX 6000 Ada Generation by 10.7 percent. It trails the NVIDIA H200 NVL by 5 percent and the NVIDIA B200 by 8 percent. This makes the MI300X a verifiable performer in OpenCL workloads, with a strong showing against most NVIDIA rivals.

The MI300A has no benchmark data, so its performance cannot be confirmed. However, its specifications indicate it is built for a different role. The 10.3 TB/s memory bandwidth and 653.7 TFLOPS of FP16 output are substantial advantages over the MI300X. For applications that are memory-bandwidth limited or that use FP16 arithmetic heavily, the MI300A is the better choice on paper. The MI300X, with its 5.32 TB/s bandwidth and 81.72 TFLOPS FP16, is better suited to workloads that run in FP32 or that do not saturate memory.

Users who need a proven OpenCL performer should select the MI300X. Its recorded score and 100th percentile ranking give it a level of confidence that the MI300A cannot match. Users who know their workloads are memory-heavy or FP16-heavy should consider the MI300A, provided they can validate its performance independently, since the database has no measurements to confirm its behavior. Both parts share the same power envelope, cooling requirements, and form factor, so system integration is identical. The choice comes down to whether a verified benchmark result matters more than the theoretical memory and FP16 advantages of the MI300A.