AMD Instinct MI300A vs AMD Instinct MI350P Comparison

Head-to-Head Benchmarks

The recorded database contains no direct head-to-head benchmark results for the AMD Instinct MI300A versus the AMD Instinct MI350P. Both entries show an average benchmark score of zero, and the wins counters for each part remain at zero. The percentile versus all GPUs is identical for both at 50, placing each squarely in the middle of the tracked GPU population despite their radically different designs.

What the data does show is a clear split in raw compute capability. The MI300A produces 61.29 TFLOPS of FP32 performance, while the MI350P produces 36.04 TFLOPS of FP32 performance. That puts the MI300A ahead by roughly 1.7 times in single-precision floating-point throughput. The MI300A also leads in texture rate, posting 1,915.2 GTexel/s against the MI350P's 1,126.4 GTexel/s, a margin of about 1.7 times as well. The MI300A carries 14,592 shading units and 912 texture mapping units, compared with 8,192 shading units and 512 TMUs on the MI350P.

The MI350P responds with a higher boost clock of 2200 MHz versus 2100 MHz for the MI300A, a 100 MHz advantage. Both parts share the same 1000 MHz base clock. The MI350P also delivers substantially more memory bandwidth at 8.19 TB/s, compared with 5.32 TB/s for the MI300A, an advantage of roughly 1.54 times. Memory capacity favors the MI350P as well, with 144 GB against 128 GB. The MI350P uses HBM3e memory while the MI300A uses HBM3, and the effective memory speed on the MI350P is 8 Gbps versus 5.2 Gbps on the MI300A.

Neither part has any pixel rate to speak of, as both are recorded at 0 MPixel/s, and both have zero ROPs. Both are compute accelerators without display outputs, and both report no DirectX, OpenGL, or Vulkan API support. The FP16 figure for the MI350P is listed as 36.04 TFLOPS at a 1:1 ratio with FP32, while the MI300A does not list a separate FP16 value in the database.

Where Each One Wins

The MI300A wins in scenarios that stress raw FP32 compute throughput, shading unit count, and texture fill rate. Applications that scale with shading units, such as dense linear algebra in single precision or workloads that leverage texture units for non-graphics compute, will see higher throughput on the MI300A. Its 14,592 shading units and 912 TMUs give it a structural advantage in any kernel that maps well to wide SIMD execution. The 61.29 TFLOPS FP32 figure is the single highest compute number recorded for either accelerator.

The MI350P wins in memory-bound workloads. Its 8.19 TB/s bandwidth is the largest memory bandwidth figure in the comparison, and the 144 GB capacity allows larger working sets to reside on-device. The HBM3e memory type operates at a higher effective speed of 8 Gbps, which reduces the time spent moving data between memory and compute units. For inference tasks or training runs where model weights exceed 128 GB, the MI350P's larger pool is the deciding factor. The higher boost clock of 2200 MHz also gives it an edge in latency-sensitive operations that do not fully occupy all shading units.

The MI300A consumes 750 W of power, while the MI350P consumes 600 W. The MI350P achieves its memory advantages at a lower power draw, which suggests better efficiency for memory-heavy operations. The MI300A's compute advantage comes at a 150 W higher power cost. The suggested power supply rating reflects this gap: 1150 W for the MI300A and 1000 W for the MI350P.

Architecture Differences

The two accelerators come from different generations of AMD's CDNA architecture. The MI300A uses CDNA 3.0, while the MI350P uses CDNA 4.0. The MI300A is built on a 5 nm process at TSMC, while the MI350P moves to a 3 nm process, also at TSMC. The MI300A's chip is named Aqua Vanjaram, and the MI350P's chip is designated MI350 128CU.

Transistor counts diverge sharply. The MI300A packs 153,000 million transistors on a 1017 mm² die, giving a transistor density of 150.4 million per square millimeter. The MI350P contains 73,000 million transistors on a larger 1190 mm² die, yielding a much lower density of 61.3 million per square millimeter. The MI350P uses fewer transistors despite the newer process node and larger physical area. This suggests the MI350P may dedicate more die area to memory stacks or other structures rather than compute logic, consistent with its higher memory capacity and bandwidth.

Memory configurations differ in type and speed. The MI300A uses HBM3 at 1300 MHz with 5.2 Gbps effective data rate, while the MI350P uses HBM3e at 2000 MHz with 8 Gbps effective. Both have an 8192 bit bus width, so the bandwidth difference comes entirely from the faster memory type and clock. The MI350P also has a larger capacity at 144 GB versus 128 GB.

Physical form factors differ. The MI300A is an OAM module with no power connectors listed, while the MI350P is a dual-slot card measuring 267 mm in length, 111 mm in height, and 40 mm in width, using a single 16-pin power connector. Both use a PCIe 5.0 x16 bus interface, and both have no display outputs.

The MI350P lists FP16 throughput at 36.04 TFLOPS with a 1:1 ratio to FP32, a feature not recorded for the MI300A. This indicates the MI350P may process FP16 and FP32 at the same rate, which is unusual and relevant for mixed-precision workloads. The MI300A's FP16 capability is simply absent from the database.

The Verdict

The data points to two different design philosophies. The MI300A is a compute-density play. It uses a massive 153,000 million transistor count on a 5 nm node to deliver 61.29 TFLOPS of FP32 and 1,915.2 GTexel/s of texture throughput. Any workload measured primarily in FP32 operations per second will favor the MI300A by a factor of about 1.7. That includes single-precision simulation, scientific computing, and any kernel that cannot effectively use reduced precision.

The MI350P is a memory-capacity and memory-bandwidth play. Its 144 GB of HBM3e at 8.19 TB/s is unmatched in this comparison, and its 600 W power draw is lower than the MI300A's 750 W. Workloads that are memory-bound, or that require model weights and datasets larger than 128 GB, will favor the MI350P. The newer CDNA 4.0 architecture and the 3 nm process node indicate a generational shift in priorities, even though the compute throughput is lower.

Neither part has any recorded benchmark scores, so the percentile ranking of 50 for both is a placeholder rather than a measured result. The database shows no wins for either accelerator in head-to-head comparisons. The choice between them depends entirely on whether the workload demands raw FP32 compute or large, fast memory. The MI300A delivers the former, the MI350P delivers the latter. There is no overlap in their advantages.

FAQ

Q: Which accelerator has higher FP32 compute performance?

A: The AMD Instinct MI300A records 61.29 TFLOPS of FP32, while the AMD Instinct MI350P records 36.04 TFLOPS. The MI300A leads by a factor of about 1.7.

Q: Which accelerator has more memory bandwidth?

A: The AMD Instinct MI350P has 8.19 TB/s of bandwidth from HBM3e memory, compared with 5.32 TB/s from HBM3 on the MI300A.

Q: How much memory does each accelerator have?

A: The MI300A has 128 GB of HBM3, and the MI350P has 144 GB of HBM3e.

Q: What are the power consumption figures?

A: The MI300A is rated at 750 W with a suggested power supply of 1150 W. The MI350P is rated at 600 W with a suggested power supply of 1000 W.

Q: Do both accelerators support the same APIs?

A: Both record no DirectX, OpenGL, or Vulkan support, and both have no display outputs. They are compute-only accelerators.

Q: Which accelerator is built on a smaller process node?

A: The MI350P uses a 3 nm process, while the MI300A uses a 5 nm process. Both are fabricated by TSMC.

Specification Differences

| Specification | AMD Instinct MI300A | AMD Instinct MI350P |

|---|---|---|

| Architecture | CDNA 3.0 | CDNA 4.0 |

| Process Node | 5 nm | 3 nm |

| Transistors | 153,000 million | 73,000 million |

| Die Size | 1017 mm² | 1190 mm² |

| Transistor Density | 150.4M / mm² | 61.3M / mm² |

| Boost Clock | 2100 MHz | 2200 MHz |

| Memory Size | 128 GB | 144 GB |

| Memory Type | HBM3 | HBM3e |

| Memory Clock | 1300 MHz, 5.2 Gbps effective | 2000 MHz, 8 Gbps effective |

| Memory Bandwidth | 5.32 TB/s | 8.19 TB/s |

| Shading Units | 14592 | 8192 |

| TMUs | 912 | 512 |

| FP32 Performance | 61.29 TFLOPS | 36.04 TFLOPS |

| FP16 Performance | Not listed | 36.04 TFLOPS (1:1) |

| Texture Rate | 1,915.2 GTexel/s | 1,126.4 GTexel/s |

| TDP | 750 W | 600 W |

| Slot Width | OAM Module | Dual-slot |

| Power Connectors | None | 1x 16-pin |

| Suggested PSU | 1150 W | 1000 W |

| Dimensions | Not listed | 267 mm x 111 mm x 40 mm |

| Chip Name | Aqua Vanjaram | MI350 128CU |

| Release Date | 2023-12-05 | 2026-05-06 |

Shared specifications include the 8192 bit memory bus width, 1000 MHz base clock, PCIe 5.0 x16 bus interface, zero ROPs, 0 MPixel/s pixel rate, no display outputs, and no API support entries. Both list Radeon Instinct as their predecessor and both have no successor recorded. Neither has a launch MSRP in the database.