AMD Instinct MI325X vs NVIDIA Rubin GPU Comparison

Head-to-Head Benchmarks

The benchmark database shows no recorded performance measurements for either the AMD Instinct MI325X or the NVIDIA Rubin GPU. Both entries carry a benchmark score of zero, a percentile ranking of 50th among all GPUs, and zero recorded wins in head-to-head comparisons. In the absence of measured frame rates, compute throughput tests, or workload-specific scores, the comparison must rely entirely on the architectural and specification data recorded in the database.

The most significant performance indicator available is raw FP32 throughput. The NVIDIA Rubin GPU records 130.0 TFLOPS, while the AMD Instinct MI325X records 81.72 TFLOPS. This gives the Rubin GPU a 59.1% higher FP32 figure, a substantial lead in general compute workloads that rely on single-precision floating point math. In FP16, the gap widens considerably: the Rubin GPU reaches 260.0 TFLOPS with a 2:1 ratio, while the MI325X delivers 81.72 TFLOPS at a 1:1 ratio. The Rubin GPU therefore records 218.2% higher FP16 throughput, a decisive advantage for AI training and inference workloads that dominate in half-precision.

Memory bandwidth tells a similar story. The Rubin GPU records 22.1 TB/s, compared to 6.14 TB/s for the MI325X. That is a 260.1% advantage in memory bandwidth, which directly impacts the speed at which large datasets and model weights can be fed to the compute units. The Rubin GPU also doubles the memory bus width at 16384 bit versus 8192 bit, and uses a newer HBM4 memory type versus HBM3e.

Texture throughput is one area where the AMD part shows a lead. The MI325X records 2,553.6 GTexel/s, while the Rubin GPU records 2,031.2 GTexel/s, a 25.7% advantage for AMD. The MI325X also carries more texture mapping units at 1216 versus 896. However, the Rubin GPU records a pixel rate of 54.41 GPixel/s with 24 ROPs, while the MI325X records 0 MPixel/s pixel rate and 0 ROPs, indicating the AMD part has no rasterization pipeline recorded in the database.

Where Each One Wins

The NVIDIA Rubin GPU wins in every compute-heavy category recorded in the database. Its FP32 throughput of 130.0 TFLOPS versus 81.72 TFLOPS makes it the stronger choice for scientific simulation, engineering analysis, and any workload that spends most cycles on single-precision arithmetic. The FP16 figure of 260.0 TFLOPS versus 81.72 TFLOPS positions it clearly ahead for machine learning training, where half-precision is the standard format. The memory subsystem reinforces this: 288 GB of HBM4 at 22.1 TB/s versus 256 GB of HBM3e at 6.14 TB/s means the Rubin GPU can hold larger models and move data through them more quickly. The Rubin GPU also records a higher boost clock at 2267 MHz versus 2100 MHz, and it carries 28672 shading units versus 19456, a 47.4% advantage in raw shader count.

The AMD Instinct MI325X wins the texture throughput comparison at 2,553.6 GTexel/s versus 2,031.2 GTexel/s. This indicates the MI325X is better suited for workloads with heavy texture sampling, such as certain visualization or rendering pipelines, though the absence of a pixel rate on the AMD part complicates that interpretation. The MI325X also records a higher base clock at 1000 MHz versus 700 MHz, which may help in power-constrained scenarios where sustained clocks matter more than peak boost. The AMD part carries a 5 nm process node, which is larger than the 3 nm node on the Rubin GPU, but this is not a performance advantage in itself.

For power efficiency, the recorded data shows the MI325X has a TDP of 1000 W versus 2300 W for the Rubin GPU. The MI325X delivers 81.72 TFLOPS at 1000 W, which is 0.08172 TFLOPS per watt, while the Rubin GPU delivers 130.0 TFLOPS at 2300 W, which is 0.05652 TFLOPS per watt. The AMD part is therefore more efficient on a per-watt basis for FP32 workloads, despite having a lower absolute throughput.

Architecture Differences

The two accelerators use fundamentally different architectures. The AMD Instinct MI325X is built on CDNA 3.0, the third generation of AMD's compute-focused architecture, implemented in the Aqua Vanjaram chip. The NVIDIA Rubin GPU uses the newer Rubin architecture, implemented in the GR100 chip. The process nodes differ: the MI325X uses TSMC's 5 nm process, while the Rubin GPU uses TSMC's 3 nm process. The transistor counts reflect this: the MI325X packs 153,000 million transistors on a 1017 mm² die, giving a density of 150.4 million transistors per square millimeter. The Rubin GPU packs 336,000 million transistors on a 1456 mm² die, giving a density of 230.8 million transistors per square millimeter. The Rubin GPU therefore holds 119.6% more transistors on a 43.2% larger die, with a 53.4% higher transistor density.

Memory architecture diverges sharply. The MI325X uses HBM3e with 256 GB capacity, an 8192-bit bus, and 6.14 TB/s bandwidth. The Rubin GPU uses HBM4 with 288 GB capacity, a 16384-bit bus, and 22.1 TB/s bandwidth. The memory clock also differs: the MI325X runs at 1500 MHz with 6 Gbps effective, while the Rubin GPU runs at 2695 MHz with 10.8 Gbps effective. The Rubin GPU's memory bus is double the width and its bandwidth is 3.6 times higher.

Compute unit counts differ substantially. The MI325X records 19456 shading units and 1216 TMUs, with no ROPs, no tensor cores, and no RT cores recorded. The Rubin GPU records 28672 shading units, 896 TMUs, 24 ROPs, and 896 tensor cores, with no RT cores recorded. The presence of tensor cores on the Rubin GPU is notable for AI workloads, while the MI325X has no tensor core entry in the database, relying instead on its shader units for compute. The FP16 ratios reflect this: the Rubin GPU doubles its FP32 rate to reach 260.0 TFLOPS FP16, while the MI325X maintains a 1:1 ratio at 81.72 TFLOPS.

The interface and power delivery also differ. The MI325X uses PCIe 5.0 x16 and an OAM Module slot width with no power connectors recorded, while the Rubin GPU uses PCIe 6.0 x16 and an SXM Module slot width. The suggested PSU ratings are 1400 W for the MI325X and 2700 W for the Rubin GPU. Neither part has display outputs, and both list N/A for DirectX, OpenGL, and Vulkan support, confirming their accelerator-only design.

Release timing shows the MI325X launched on 2024-10-09, while the Rubin GPU has a release date of 2025-12-31 and an active production status. The MI325X has no production status recorded, and its predecessor is listed as Radeon Instinct, while the Rubin GPU's predecessor is Server Blackwell.

FAQ

Q: Which GPU has higher FP32 compute throughput?

A: The NVIDIA Rubin GPU records 130.0 TFLOPS FP32, while the AMD Instinct MI325X records 81.72 TFLOPS. The Rubin GPU leads by 59.1%.

Q: How do the memory bandwidth figures compare?

A: The Rubin GPU records 22.1 TB/s from 288 GB of HBM4 on a 16384-bit bus. The MI325X records 6.14 TB/s from 256 GB of HBM3e on an 8192-bit bus. The Rubin GPU has 260.1% higher bandwidth.

Q: Does the AMD part have any advantage in the recorded specifications?

A: Yes. The MI325X records higher texture throughput at 2,553.6 GTexel/s versus 2,031.2 GTexel/s, has more TMUs at 1216 versus 896, a higher base clock at 1000 MHz versus 700 MHz, and a lower TDP at 1000 W versus 2300 W.

Q: What process nodes do the two chips use?

A: The MI325X uses TSMC's 5 nm process with 153,000 million transistors on a 1017 mm² die. The Rubin GPU uses TSMC's 3 nm process with 336,000 million transistors on a 1456 mm² die.

Q: Does the Rubin GPU have tensor cores?

A: Yes, the Rubin GPU records 896 tensor cores. The MI325X has no tensor core entry in the database. The Rubin GPU also reaches 260.0 TFLOPS FP16 with a 2:1 ratio, while the MI325X stays at 81.72 TFLOPS with a 1:1 ratio.

Q: Which GPU supports a newer PCIe interface?

A: The Rubin GPU uses PCIe 6.0 x16, while the MI325X uses PCIe 5.0 x16. The Rubin GPU is also listed with an active production status and a release date of 2025-12-31, while the MI325X launched on 2024-10-09.

Specification Differences

The database records the following differences between the two accelerators:

• Chip: Aqua Vanjaram (MI325X) versus GR100 (Rubin GPU)
• Architecture: CDNA 3.0 versus Rubin
• Generation: Instinct (MIx) versus Server Rubin (Rxx)
• Process Node: 5 nm versus 3 nm
• Transistors: 153,000 million versus 336,000 million
• Die Size: 1017 mm² versus 1456 mm²
• Transistor Density: 150.4M per mm² versus 230.8M per mm²
• Base Clock: 1000 MHz versus 700 MHz
• Boost Clock: 2100 MHz versus 2267 MHz
• Memory Clock: 1500 MHz 6 Gbps effective versus 2695 MHz 10.8 Gbps effective
• Memory Size: 256 GB versus 288 GB
• Memory Type: HBM3e versus HBM4
• Memory Bus Width: 8192 bit versus 16384 bit
• Memory Bandwidth: 6.14 TB/s versus 22.1 TB/s
• Shading Units: 19456 versus 28672
• TMUs: 1216 versus 896
• ROPs: 0 versus 24
• Tensor Cores: None recorded versus 896
• Pixel Rate: 0 MPixel/s versus 54.41 GPixel/s
• Texture Rate: 2,553.6 GTexel/s versus 2,031.2 GTexel/s
• FP32: 81.72 TFLOPS versus 130.0 TFLOPS
• FP16: 81.72 TFLOPS (1:1) versus 260.0 TFLOPS (2:1)
• TDP: 1000 W versus 2300 W
• Slot Width: OAM Module versus SXM Module
• Suggested PSU: 1400 W versus 2700 W
• Bus Interface: PCIe 5.0 x16 versus PCIe 6.0 x16
• Release Date: 2024-10-09 versus 2025-12-31
• Predecessor: Radeon Instinct versus Server Blackwell
• Production Status: Not recorded versus Active

The Verdict

The recorded data points to the NVIDIA Rubin GPU as the dominant compute accelerator. It leads in FP32 throughput by 59.1%, in FP16 throughput by 218.2%, and in memory bandwidth by 260.1%. It carries more shading units, a wider memory bus, newer memory technology, tensor cores, and a more advanced 3 nm process node. For AI training, high-performance computing, and any workload that scales with memory bandwidth and half-precision throughput, the Rubin GPU is the clear choice based on the database specifications.

The AMD Instinct MI325X holds advantages in texture throughput, TMU count, base clock, and power draw. Its 1000 W TDP versus 2300 W means it requires less power infrastructure, and its higher texture rate suggests it may handle texture-bound workloads more effectively. For organizations constrained by power delivery or cooling capacity, the MI325X offers a more manageable integration profile, though at a significant cost in absolute compute and memory performance. The MI325X also has a longer availability window, with a 2024 launch date versus the Rubin GPU's 2025 release.

Neither part has benchmark scores in the database, so performance conclusions rest on specification analysis. The Rubin GPU's advantages in every major compute and memory category, combined with its active production status, make it the stronger choice for peak performance workloads. The MI325X suits deployments where power limits, texture throughput, or early availability take priority over raw FP32, FP16, and bandwidth figures.