AMD Instinct MI300X vs NVIDIA CMP 40HX Comparison

Head-to-Head Benchmarks

The database contains a single head-to-head benchmark between these two accelerators, and it is a decisive one. In the Geekbench OpenCL test, the AMD Instinct MI300X scores 317,994 points, while the NVIDIA CMP 40HX scores 93,395 points. The recorded delta is 240.5%, meaning the AMD part delivers more than triple the raw compute throughput of the NVIDIA part in this workload. This is not a marginal victory; it is a categorical separation in performance class.

To frame the MI300X's result, the database shows it sits at the 100th percentile among all GPUs, which means no other accelerator in the database scores higher in this benchmark. Its nearest rivals in the rankings are the NVIDIA B200 at 345,482 points (8% ahead), the NVIDIA H200 NVL at 334,891 points (5% ahead), and the NVIDIA L40S at 295,763 points (7.5% behind). The MI300X is therefore not merely ahead of the CMP 40HX; it is at the very top of the entire database, with only two NVIDIA data-center parts exceeding it. The CMP 40HX, by contrast, sits at the 93rd percentile, which is still a strong position for a mining-focused card, but its average benchmark score of 85,637 places it in a completely different tier.

The CMP 40HX's nearest rivals provide context for its own standing. It trails the AMD Radeon PRO W7600 by 1.7% and the NVIDIA Quadro GP100 by 2.1%, while leading the AMD Radeon PRO W6600 by 4.4% and the AMD Radeon Pro Vega 64X by 5.8%. These are all workstation or prosumer parts from a similar era, and the CMP 40HX is competitive with them. However, the gap between the CMP 40HX and the MI300X is so large that no amount of overclocking or optimization could bridge it. The MI300X's OpenCL score is 3.4 times higher, and the delta of 240.5% is the only head-to-head data point recorded, but it is sufficient to establish the hierarchy.

Where Each One Wins

Given the benchmark data, the use-case split is stark. The AMD Instinct MI300X wins the only recorded head-to-head test, the Geekbench OpenCL benchmark, with a 240.5% advantage. This suggests the MI300X is designed for workloads that demand massive parallel compute throughput, such as large-scale AI training, inference, scientific simulation, and high-performance computing. Its 81.72 TFLOPS of FP32 and 81.72 TFLOPS of FP16 (1:1 ratio) indicate that it treats single-precision and half-precision workloads with equal priority, which is typical for accelerators aimed at both traditional HPC and machine learning. The absence of any display outputs and the OAM Module slot width confirm it is a server-grade component, not a consumer or workstation card.

The NVIDIA CMP 40HX, on the other hand, has no recorded wins in the head-to-head benchmark set. Its strengths lie elsewhere, specifically in its original purpose: cryptocurrency mining. The CMP 40HX has no display outputs, which is a deliberate design choice to prevent it from being used as a gaming card. Its 7.603 TFLOPS of FP32 and 15.21 TFLOPS of FP16 (2:1 ratio) show that it is more efficient at half-precision, but these numbers are dwarfed by the MI300X. The CMP 40HX also supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, whereas the MI300X reports N/A for all three APIs. This is a key differentiator: the CMP 40HX technically has graphics API support, but with no display outputs, that support is effectively useless in practice. The MI300X does not even attempt to expose these APIs, focusing solely on compute.

The data implies that the CMP 40HX is a niche product for a niche task, and its 93rd percentile ranking reflects that it performs well among its peers, but the MI300X is in a different universe of performance. If the workload is general-purpose compute, the MI300X is the clear winner. If the workload is mining, the CMP 40HX may still be functional, but the MI300X's raw compute advantage would likely translate to higher hash rates, assuming software optimization exists, although the database does not record any mining-specific benchmarks to confirm this.

Architecture Differences

The architectural divide between these two parts is profound, starting with the manufacturing process. The AMD Instinct MI300X is built on a 5 nm process at TSMC, while the NVIDIA CMP 40HX uses a 12 nm process at the same foundry. This node advantage alone explains a significant portion of the performance gap. The MI300X packs 153,000 million transistors onto a 1017 mm² die, yielding a transistor density of 150.4 million per mm². The CMP 40HX has 10,800 million transistors on a 445 mm² die, with a density of 24.3 million per mm². The MI300X has over 14 times more transistors and more than double the die area, which allows it to house vastly more compute units.

The memory subsystems are equally divergent. The MI300X features 192 GB of HBM3 memory on an 8192-bit bus, delivering 5.32 TB/s of bandwidth. The CMP 40HX has 8 GB of GDDR6 memory on a 256-bit bus, providing 448.0 GB/s. This is a 12-fold difference in capacity and an 11.9-fold difference in bandwidth, which is critical for memory-bound workloads. The MI300X's memory clock is listed as 1300 MHz with 5.2 Gbps effective speed, while the CMP 40HX runs at 1750 MHz with 14 Gbps effective. The CMP 40HX has faster individual memory chips, but the MI300X's massive bus width and HBM3 technology dominate overall bandwidth.

The compute configurations tell a similar story. The MI300X has 19,456 shading units, 1,216 texture mapping units, and zero ROPs, resulting in a texture rate of 2,553.6 GTexel/s and a pixel rate of 0 MPixel/s. The CMP 40HX has 2,304 shading units, 144 TMUs, and 64 ROPs, with a texture rate of 237.6 GTexel/s and a pixel rate of 105.6 GPixel/s. The MI300X has no ROPs because it is not designed to output pixels; it is a pure compute accelerator. The CMP 40HX, despite being mining-focused, retains ROPs and a pixel rate, likely because the TU106 chip was originally designed for consumer graphics. The CMP 40HX also has 36 RT cores and 288 tensor cores, while the MI300X reports null for both, indicating it does not carry dedicated ray tracing or tensor core hardware, instead relying on its massive shading array for all compute tasks.

Clock speeds are another point of divergence. The MI300X has a base clock of 1000 MHz and a boost clock of 2100 MHz. The CMP 40HX has a base of 1470 MHz and a boost of 1650 MHz. The CMP 40HX runs at a higher base clock, but the MI300X's boost clock is significantly higher, and with 8.4 times more shading units, the aggregate throughput is incomparable. The power envelopes reflect this: the MI300X has a TDP of 750 W with a suggested PSU of 1150 W, while the CMP 40HX has a TDP of 185 W with a suggested PSU of 450 W. The MI300X draws over four times the power, which is expected for a part with 14 times the transistor count.

The Verdict

The data is unambiguous. The AMD Instinct MI300X is the superior compute accelerator by every metric recorded in the database. Its OpenCL score of 317,994 versus 93,395 for the CMP 40HX represents a 240.5% advantage, and its position at the 100th percentile among all GPUs means it is the best or near-best in the entire database. The CMP 40HX, at the 93rd percentile, is a competent performer for its class, but its class is a lower tier entirely. The MI300X is designed for data centers, AI research, and HPC, where its 192 GB of HBM3 memory and 5.32 TB/s bandwidth are essential. The CMP 40HX is a mining card with 8 GB of GDDR6 and a PCIe 1.0 x4 interface, which is a severe bottleneck for modern workloads.

Who should pick which? The data suggests that anyone running large-scale compute tasks, such as training large language models or running scientific simulations, should choose the MI300X, because its FP32 and FP16 throughput are both over 10 times higher than the CMP 40HX's, and its memory bandwidth is nearly 12 times higher. The CMP 40HX, with its end-of-life production status and mining-specific design, is only suitable for legacy cryptocurrency mining operations where its lower power draw (185 W versus 750 W) and smaller footprint (Dual-slot versus OAM Module) might be advantageous. However, the MI300X's sheer compute power would likely outperform the CMP 40HX even in mining, provided the software can utilize its architecture. The CMP 40HX does have a launch MSRP of 699 USD, but the MI300X has no recorded MSRP, indicating it is sold through custom contracts rather than retail channels.

FAQ

Q: Which accelerator has the higher OpenCL benchmark score?

A: The AMD Instinct MI300X scores 317,994 points, while the NVIDIA CMP 40HX scores 93,395 points, giving the MI300X a 240.5% advantage.

Q: How does the MI300X compare to its nearest rivals in the database?

A: The MI300X is 5% behind the NVIDIA H200 NVL, 8% behind the NVIDIA B200, 7.5% ahead of the NVIDIA L40S, and 10.7% ahead of the NVIDIA RTX 6000 Ada Generation.

Q: What is the memory capacity difference between the two parts?

A: The MI300X has 192 GB of HBM3 memory, while the CMP 40HX has 8 GB of GDDR6 memory, a 24-fold difference in capacity.

Q: Does the CMP 40HX support modern graphics APIs?

A: Yes, the CMP 40HX supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, while the MI300X reports N/A for all three APIs.

Q: What is the thermal design power of each accelerator?

A: The MI300X has a TDP of 750 W with a suggested PSU of 1150 W, while the CMP 40HX has a TDP of 185 W with a suggested PSU of 450 W.

Q: Which part has a higher transistor density?

A: The MI300X has a density of 150.4 million transistors per mm² on a 5 nm process, compared to the CMP 40HX's 24.3 million per mm² on a 12 nm process.

Specification Differences

The following specifications differ between the two accelerators, with the MI300X listed first and the CMP 40HX second:

• Chip: Aqua Vanjaram vs TU106
• Architecture: CDNA 3.0 vs Turing
• Generation: Instinct (MIx) vs Mining GPUs
• Process Node: 5 nm vs 12 nm
• Transistors: 153,000 million vs 10,800 million
• Die Size: 1017 mm² vs 445 mm²
• Transistor Density: 150.4M / mm² vs 24.3M / mm²
• Base Clock: 1000 MHz vs 1470 MHz
• Boost Clock: 2100 MHz vs 1650 MHz
• Memory Clock: 1300 MHz 5.2 Gbps effective vs 1750 MHz 14 Gbps effective
• Memory Size: 192 GB vs 8 GB
• Memory Type: HBM3 vs GDDR6
• Memory Bus Width: 8192 bit vs 256 bit
• Memory Bandwidth: 5.32 TB/s vs 448.0 GB/s
• Shading Units: 19456 vs 2304
• TMUs: 1216 vs 144
• ROPs: 0 vs 64
• RT Cores: null vs 36
• Tensor Cores: null vs 288
• Pixel Rate: 0 MPixel/s vs 105.6 GPixel/s
• Texture Rate: 2,553.6 GTexel/s vs 237.6 GTexel/s
• FP32: 81.72 TFLOPS vs 7.603 TFLOPS
• FP16: 81.72 TFLOPS (1:1) vs 15.21 TFLOPS (2:1)
• TDP: 750 W vs 185 W
• Slot Width: OAM Module vs Dual-slot
• Power Connectors: None vs 1x 8-pin
• Suggested PSU: 1150 W vs 450 W
• Bus Interface: PCIe 5.0 x16 vs PCIe 1.0 x4
• APIs: DirectX N/A, OpenGL N/A, Vulkan N/A vs DirectX 12 Ultimate, OpenGL 4.6, Vulkan 1.4
• Dimensions: null vs 229 mm length, 111 mm height, 35 mm width
• Production Status: null vs End-of-life
• Release Date: 2023-12-05 vs 2021-02-24
• Predecessor: Radeon Instinct vs null
• Launch MSRP: null vs 699 USD
• Benchmark Scores: Geekbench OpenCL 317994 vs Geekbench OpenCL 93395 and Geekbench Vulkan 77879
• Average Benchmark Score: 317994 vs 85637
• Percentile vs All GPUs: 100 vs 93