AMD Instinct MI325X vs AMD Instinct MI350X Comparison

The Verdict

The AMD Instinct MI350X represents the newer generation, built on CDNA 4.0 architecture and fabricated on a 3 nm process, while the MI325X uses CDNA 3.0 and a 5 nm node. The MI350X delivers higher memory bandwidth at 8.19 TB/s versus 6.14 TB/s and offers more memory capacity at 288 GB versus 256 GB. However, the MI325X counteracts with a higher shading unit count of 19,456 versus 16,384 and a higher FP32 compute rating of 81.72 TFLOPS versus 72.09 TFLOPS.

The data indicates that the MI350X is positioned for workloads that demand larger memory pools and faster memory throughput, such as large model inference or training scenarios with massive datasets. The MI325X, with its higher raw compute throughput and texture rate, suits compute-heavy tasks where memory capacity is less of a constraint. Both parts are OAM modules with a 1000 W TDP, require a 1400 W suggested power supply, and use PCIe 5.0 x16 connectivity.

Neither part carries a launch MSRP in the database, so no pricing analysis is possible. The recorded percentile for both against all GPUs is 50, and neither has benchmark scores or nearest rivals listed, meaning all comparisons derive strictly from architectural specifications and memory characteristics.

Architecture Differences

The fundamental architectural split is CDNA 3.0 versus CDNA 4.0. The MI325X uses the Aqua Vanjaram chip, produced on a 5 nm TSMC process with 153,000 million transistors on a 1017 mm² die, resulting in a transistor density of 150.4M per mm². The MI350X uses the MI350 256CU chip, built on a 3 nm TSMC process with 185,000 million transistors on a 2380 mm² die, giving a transistor density of 77.7M per mm². The MI350X packs more transistors but on a much larger die, leading to lower density.

Compute resources differ notably. The MI325X has 19,456 shading units, 1,216 texture mapping units, and a texture rate of 2,553.6 GTexel/s. The MI350X has 16,384 shading units, 1,024 TMUs, and a texture rate of 2,252.8 GTexel/s. Both have zero ROPs and zero pixel rate, consistent with their compute-focused, non-render-capable nature. Neither has RT cores or tensor cores listed.

Clock speeds show the MI350X with a higher boost clock of 2200 MHz versus 2100 MHz on the MI325X, while both share a 1000 MHz base clock. The memory clock differs significantly: the MI350X runs at 2000 MHz (8 Gbps effective) versus 1500 MHz (6 Gbps effective) on the MI325X.

Memory architecture is a major differentiator. The MI325X has 256 GB of HBM3e on an 8192-bit bus with 6.14 TB/s bandwidth. The MI350X has 288 GB of HBM3e on the same 8192-bit bus but achieves 8.19 TB/s bandwidth, a 33.4% increase in throughput. The bus width is identical, so the bandwidth gain comes from the higher memory clock.

Both modules are OAM form factor with no display outputs, no power connectors (relying on the module interface), and no supported graphics APIs (DirectX, OpenGL, Vulkan all N/A). The MI350X has recorded physical dimensions of 102 mm by 165 mm, while the MI325X has no dimension data. Both are PCIe 5.0 x16 and share the same generation label, Instinct (MIx), with the same predecessor, Radeon Instinct.

Release dates show the MI325X launched on 2024-10-09, while the MI350X launched on 2025-06-11, a gap of roughly eight months. Neither has a listed successor, and both have identical power requirements at 1000 W TDP with a 1400 W suggested PSU.

Head-to-Head Benchmarks

The database contains no head-to-head benchmark results for these two accelerators, and neither has individual benchmark scores or nearest rival comparisons. All analysis must rely on the recorded specification data, which provides several clear differentiators.

Memory bandwidth is the most pronounced advantage for the MI350X. At 8.19 TB/s, it exceeds the MI325X's 6.14 TB/s by 2.05 TB/s, a 33.4% margin. For memory-bound workloads, such as large-scale matrix operations or data movement between compute units and HBM stacks, this delta is substantial. The MI350X also holds a memory capacity advantage at 288 GB versus 256 GB, a 12.5% difference that could determine whether a model fits in on-chip memory.

Raw compute throughput favors the MI325X. Its FP32 rating of 81.72 TFLOPS beats the MI350X's 72.09 TFLOPS by 9.63 TFLOPS, a 13.4% advantage. FP16 performance is identical to FP32 on both parts at a 1:1 ratio, so the same margin applies to reduced-precision workloads. The MI325X also leads in texture rate at 2,553.6 GTexel/s versus 2,252.8 GTexel/s, a 13.4% edge consistent with its higher shading unit and TMU counts.

The MI350X compensates with a higher boost clock of 2200 MHz versus 2100 MHz, a 4.8% increase, but the MI325X's larger compute resource pool (19,456 versus 16,384 shading units, 1,216 versus 1,024 TMUs) overrides the clock advantage in theoretical throughput. The MI325X has 18.7% more shading units and 18.75% more TMUs.

Transistor counts favor the MI350X at 185,000 million versus 153,000 million, a 20.9% difference, but the MI350X spreads those transistors across a 2380 mm² die versus 1017 mm², indicating a different design philosophy focused on memory and density rather than raw compute per unit area. The MI325X's transistor density of 150.4M per mm² versus 77.7M per mm² reflects the smaller node and tighter packing.

Both parts share identical power envelopes at 1000 W TDP, meaning the MI325X delivers higher FP32 throughput per watt based on the recorded figures, while the MI350X delivers higher memory bandwidth per watt. The MI325X achieves 81.72 TFLOPS per 1000 W, while the MI350X achieves 72.09 TFLOPS per 1000 W.

FAQ

Q: Which accelerator has higher memory bandwidth?

A: The MI350X leads with 8.19 TB/s versus 6.14 TB/s on the MI325X, a 33.4% advantage, both using HBM3e on an 8192-bit bus.

Q: Which accelerator has higher FP32 compute throughput?

A: The MI325X delivers 81.72 TFLOPS compared to the MI350X's 72.09 TFLOPS, a 13.4% margin, with both parts offering FP16 at a 1:1 ratio to FP32.

Q: What are the memory capacity differences?

A: The MI350X has 288 GB of HBM3e, while the MI325X has 256 GB, a 32 GB difference that gives the MI350X more headroom for large models.

Q: How do the transistor counts and die sizes compare?

A: The MI350X has 185,000 million transistors on a 2380 mm² die, while the MI325X has 153,000 million on a 1017 mm² die. The MI325X has a higher density at 150.4M per mm² versus 77.7M per mm².

Q: Do both accelerators require the same power?

A: Yes, both are rated at 1000 W TDP with a 1400 W suggested power supply, and both use OAM modules with no external power connectors.

Q: Which architecture and process node does each use?

A: The MI325X uses CDNA 3.0 on a 5 nm TSMC process, while the MI350X uses CDNA 4.0 on a 3 nm TSMC process. The MI350X also has a higher boost clock at 2200 MHz versus 2100 MHz.

Where Each One Wins

The MI350X wins decisively in memory-related metrics. Its 8.19 TB/s bandwidth is 33.4% above the MI325X, and its 288 GB capacity provides a 12.5% increase. These advantages make it the stronger candidate for workloads where data movement dominates compute, such as training or inference on very large transformer models where the entire model and its activations must reside in HBM. The higher memory clock of 2000 MHz (8 Gbps effective) versus 1500 MHz (6 Gbps effective) directly drives this bandwidth advantage. The MI350X also benefits from a more recent release date of 2025-06-11 and a newer architecture, CDNA 4.0, which may include instruction-level or scheduling improvements not captured in the raw specification data.

The MI325X wins in raw compute throughput. Its FP32 output of 81.72 TFLOPS exceeds the MI350X by 9.63 TFLOPS, and its texture rate of 2,553.6 GTexel/s beats the MI350X by 300.8 GTexel/s. With 19,456 shading units and 1,216 TMUs, the MI325X has 18.7% more shading units and 18.75% more TMUs than the MI350X. These figures point to workloads with high arithmetic intensity, where memory bandwidth is less of a bottleneck and the compute units can stay busy. The MI325X also achieves higher transistor density at 150.4M per mm², indicating a more compact design that may offer better locality for certain compute patterns.

The shared characteristics matter for deployment decisions. Both are OAM modules with 1000 W TDP and 1400 W suggested PSU, so system power delivery and cooling infrastructure can be identical. Both use PCIe 5.0 x16 and have no display outputs or graphics API support, meaning they are strictly compute accelerators for server environments. Neither has a listed successor, and both share the same generation label and predecessor.

The MI350X's larger die, 2380 mm² versus 1017 mm², combined with the 3 nm process, suggests a design that prioritizes memory integration and bandwidth scaling. The MI325X's smaller, denser die on 5 nm prioritizes compute density. For users with memory-bound workloads, the MI350X is the clear choice based on the recorded data. For users with compute-bound workloads that fit within 256 GB, the MI325X offers more theoretical FLOPs. The absence of benchmark scores means these conclusions are provisional on the specification deltas, but the memory bandwidth gap of 2.05 TB/s is the largest single difference between the two parts and likely the most impactful for real-world AI workloads.