AMD Radeon Instinct MI308X vs NVIDIA H20 Comparison

FAQ

Q: What are the core architectural differences between the AMD Radeon Instinct MI308X and the NVIDIA H20?

A: The MI308X uses AMD's CDNA 3.0 architecture with the Aqua Vanjaram chip, while the H20 uses NVIDIA's Hopper architecture with the GH100 chip. Both are fabricated by TSMC on a 5 nm process, but the MI308X has a significantly larger die at 1017 mm² compared to the H20's 814 mm², and the MI308X packs 153,000 million transistors versus the H20's 80,000 million.

Q: How do the memory subsystems compare between these two accelerators?

A: The MI308X offers 192 GB of HBM3 memory with an 8192-bit bus and 10.3 TB/s bandwidth, while the H20 provides 96 GB of HBM3 with a 6144-bit bus and 4.03 TB/s bandwidth. The MI308X also has a higher effective memory clock at 10.1 Gbps compared to the H20's 5.3 Gbps.

Q: What are the FP32 and FP16 performance figures for each card?

A: The MI308X delivers 81.72 TFLOPS of FP32 performance and 653.7 TFLOPS of FP16 (8:1 ratio). The H20 delivers 39.54 TFLOPS of FP32 and 79.07 TFLOPS of FP16 (2:1 ratio). The MI308X more than doubles the H20 in FP32 and offers over 8 times the FP16 throughput.

Q: How do the power requirements differ between the two modules?

A: The MI308X has a TDP of 750 W with a suggested PSU of 1150 W, while the H20 has a TDP of 500 W with a suggested PSU of 900 W. The MI308X uses an OAM Module slot width, whereas the H20 uses an SXM Module form factor.

Q: What is the transistor density of each chip?

A: The MI308X achieves a transistor density of 150.4M per mm², while the H20 achieves 98.3M per mm². This reflects the MI308X's denser packing of transistors within its larger die.

Q: Which card has more shading units and texture mapping units?

A: The MI308X has 19,456 shading units and 1,216 TMUs, while the H20 has 9,984 shading units and 312 TMUs. The H20 does have 24 ROPs and 312 tensor cores, whereas the MI308X reports 0 ROPs and no tensor core count.

The Verdict

The recorded data shows a clear performance hierarchy: the AMD Radeon Instinct MI308X dominates in raw compute throughput, memory capacity, and bandwidth, making it the choice for memory-intensive and FP16-heavy workloads. The NVIDIA H20, with its lower power draw, tensor cores, and ROP support, is the pick for deployments where power efficiency and tensor-based operations matter more than raw memory bandwidth.

For organizations prioritizing massive memory capacity and peak FP16 throughput, the MI308X is the data-driven choice. Its 192 GB of HBM3 and 10.3 TB/s bandwidth dwarf the H20's 96 GB and 4.03 TB/s, directly enabling larger model residency and faster data movement. The MI308X also delivers 653.7 TFLOPS FP16, which is 8.3 times the H20's 79.07 TFLOPS, a decisive margin for training or inference tasks that leverage FP16 arithmetic.

The H20, however, is not without merit. Its 500 W TDP versus the MI308X's 750 W means the H20 consumes one-third less power, a meaningful advantage in dense server deployments. The H20 also includes 312 tensor cores and 24 ROPs, features absent or unspecified in the MI308X's specification sheet, making it the better-documented option for tensor-core-accelerated workloads and pixel-rate-dependent tasks.

Head-to-Head Benchmarks

The head-to-head benchmark data is empty, so the comparison relies entirely on the specification-level metrics recorded in the database. The largest wins for the MI308X are in memory and compute throughput.

The MI308X delivers 653.7 TFLOPS FP16 versus the H20's 79.07 TFLOPS, a 8.27x advantage. In FP32, the MI308X posts 81.72 TFLOPS against the H20's 39.54 TFLOPS, a 2.07x lead. Texture rate favors the MI308X at 2,553.6 GTexel/s versus 617.8 GTexel/s, a 4.13x difference. Memory bandwidth is 10.3 TB/s for the MI308X versus 4.03 TB/s for the H20, a 2.56x gap, and memory capacity is 192 GB versus 96 GB, exactly double.

The H20 wins in pixel rate, posting 47.52 GPixel/s while the MI308X records 0 MPixel/s, confirming the MI308X's lack of ROP output. The H20 also has a higher base clock at 1830 MHz versus 1000 MHz and a boost clock at 1980 MHz versus 2100 MHz, though the MI308X's boost clock is higher. The H20's transistor count is lower at 80,000 million versus 153,000 million, yet its die is smaller at 814 mm² versus 1017 mm², resulting in a lower density.

Specification Differences

The two accelerators differ across nearly every major specification category. The MI308X uses the Aqua Vanjaram chip on CDNA 3.0 architecture, while the H20 uses the GH100 chip on Hopper architecture. The MI308X has 153,000 million transistors on a 1017 mm² die, versus the H20's 80,000 million on 814 mm². Transistor density is 150.4M per mm² for the MI308X and 98.3M per mm² for the H20.

Memory configuration diverges sharply: the MI308X has 192 GB of HBM3 with an 8192-bit bus and 10.3 TB/s bandwidth, while the H20 has 96 GB of HBM3 with a 6144-bit bus and 4.03 TB/s. The MI308X's memory clock is 2525 MHz with 10.1 Gbps effective, versus the H20's 1313 MHz with 5.3 Gbps effective.

Compute resources differ: the MI308X has 19,456 shading units, 1,216 TMUs, and 0 ROPs, while the H20 has 9,984 shading units, 312 TMUs, and 24 ROPs. The H20 lists 312 tensor cores; the MI308X does not specify a tensor core count. Pixel rate is 0 MPixel/s for the MI308X and 47.52 GPixel/s for the H20. Texture rate is 2,553.6 GTexel/s for the MI308X and 617.8 GTexel/s for the H20.

Power and form factor differ: the MI308X has a 750 W TDP with a 1150 W suggested PSU and an OAM Module slot, while the H20 has a 500 W TDP with a 900 W suggested PSU and an SXM Module slot. Both use PCIe 5.0 x16 interfaces and have no display outputs. The MI308X's release date is 2023-12-05, while the H20's is 2024-01-31. The H20 is marked as Active production status, with a predecessor of Server Ada and a successor of Server Blackwell; the MI308X lists a predecessor of FirePro Data Center and no successor.

Architecture Differences

The MI308X is built on CDNA 3.0, AMD's compute-focused architecture, using the Aqua Vanjaram chip. The H20 is built on NVIDIA's Hopper architecture, using the GH100 chip. Both are 5 nm designs from TSMC, but the MI308X's die is 1017 mm², substantially larger than the H20's 814 mm². The MI308X packs 153,000 million transistors, nearly double the H20's 80,000 million, yielding a transistor density of 150.4M per mm² versus 98.3M per mm².

The MI308X's memory architecture is built around a massive 8192-bit bus and 192 GB of HBM3, enabling 10.3 TB/s of bandwidth. The H20 uses a 6144-bit bus with 96 GB of HBM3, achieving 4.03 TB/s. The MI308X's effective memory speed is 10.1 Gbps, versus 5.3 Gbps for the H20.

The MI308X has 19,456 shading units and 1,216 TMUs but no ROPs, indicating a pure compute design with no rasterization pipeline. The H20 has 9,984 shading units, 312 TMUs, 24 ROPs, and 312 tensor cores, showing a fuller feature set that includes tensor acceleration and pixel output. The MI308X's FP16 ratio is 8:1 relative to FP32, while the H20's is 2:1, reflecting different design priorities: the MI308X emphasizes FP16 throughput, the H20 balances FP16 and FP32 more evenly.

Where Each One Wins

The MI308X wins decisively in memory capacity and bandwidth. Its 192 GB of HBM3 is double the H20's 96 GB, and its 10.3 TB/s bandwidth is 2.56 times the H20's 4.03 TB/s. This makes the MI308X the choice for workloads that require large model footprints or high-bandwidth data access, such as large-scale training datasets or inference with very large models that must reside in GPU memory.

The MI308X also wins in raw compute throughput. Its 653.7 TFLOPS FP16 is 8.27 times the H20's 79.07 TFLOPS, and its 81.72 TFLOPS FP32 is 2.07 times the H20's 39.54 TFLOPS. Texture rate is 4.13 times higher at 2,553.6 GTexel/s versus 617.8 GTexel/s. These figures indicate the MI308X is the stronger choice for FP16-heavy compute tasks and texture-intensive operations.

The H20 wins in power efficiency. Its 500 W TDP is 250 W lower than the MI308X's 750 W, and its suggested PSU is 900 W versus 1150 W. In a multi-GPU server, this translates to lower aggregate power draw and simpler power delivery requirements. The H20 also wins in pixel rate, with 47.52 GPixel/s versus 0 MPixel/s for the MI308X, making it the only one of the two with any rasterization output capability.

The H20's 312 tensor cores provide a documented tensor acceleration path that the MI308X does not specify. For workloads that rely on tensor core operations, such as certain deep learning frameworks, the H20's architecture explicitly supports these operations. The H20's higher base clock of 1830 MHz versus 1000 MHz also suggests better performance at lower utilization states, though the MI308X's boost clock of 2100 MHz exceeds the H20's 1980 MHz.

In summary, the MI308X is the data-driven choice for maximum memory, bandwidth, and FP16 throughput, while the H20 is the choice for lower power consumption, tensor core support, and pixel output capability. Each card wins in distinct dimensions, and the selection depends on which of these dimensions the workload prioritizes.