AMD Instinct MI300 vs AMD Instinct MI350P Comparison

Where Each One Wins

The AMD Instinct MI300 and AMD Instinct MI350P occupy different positions in the accelerator lineup, with the data showing a clear split between raw compute throughput and memory capacity. The MI300 leads in shading units, texture mapping units, and FP32/FP16 compute rates, while the MI350P counters with a significantly larger memory pool and substantially higher memory bandwidth.

For workloads that stress raw shader and texture throughput, the MI300 holds the advantage. Its 14,080 shading units versus 8,192 on the MI350P gives it a 71.9% higher shader count, and its 880 TMUs against 512 TMUs represents a 71.9% advantage in texture processing hardware. The FP32 compute rate of 47.87 TFLOPS on the MI300 exceeds the 36.04 TFLOPS on the MI350P by roughly 32.8%. FP16 performance follows the same pattern, with the MI300 again delivering 47.87 TFLOPS against 36.04 TFLOPS on the MI350P, both at a 1:1 ratio. The texture fill rate tells the same story: 1,496.0 GTexel/s on the MI300 versus 1,126.4 GTexel/s on the MI350P, a 32.8% margin.

The MI350P wins on memory capacity and bandwidth. With 144 GB of HBM3e memory versus 128 GB of HBM3 on the MI300, the MI350P offers 12.5% more capacity. The bandwidth gap is far larger: 8.19 TB/s versus 5.32 TB/s, a 53.9% advantage. That bandwidth difference comes from faster memory clocks, with the MI350P running its memory at 2000 MHz (8 Gbps effective) compared to 1300 MHz (5.2 Gbps effective) on the MI300.

The MI350P also boosts higher. Its 2200 MHz boost clock versus 1700 MHz on the MI300 represents a 29.4% clock advantage, though the MI300 compensates with more execution units. Both cards share a 600 W TDP, a PCIe 5.0 x16 bus interface, and no display outputs. The MI350P uses a single 16-pin power connector while the MI300 uses two 8-pin connectors, and the MI350P is a dual-slot card with a width of 40 mm (1.6 inches) while the MI300 lists no slot width.

Architecture Differences

The two accelerators come from different CDNA generations. The MI300 uses CDNA 3.0 architecture with the Aqua Vanjaram chip, while the MI350P uses CDNA 4.0 architecture with the MI350 128CU chip. Both belong to the same Instinct (MIx) generation family and both are manufactured by AMD at TSMC, but the process nodes differ: the MI300 uses a 5 nm process, and the MI350P uses a 3 nm process.

Transistor counts and die sizes create an interesting contrast. The MI300 packs 153,000 million transistors on a 1017 mm² die, yielding a transistor density of 150.4M per mm². The MI350P has 73,000 million transistors on a larger 1190 mm² die, resulting in a much lower density of 61.3M per mm². The MI300 has more than double the transistor count, yet the MI350P die is 17.0% larger by area.

Memory technology differs between the two. The MI300 uses HBM3 memory, while the MI350P uses HBM3e. Both have an 8192-bit memory bus width, but the effective memory speed differs: 5.2 Gbps on the MI300 versus 8 Gbps on the MI350P. This accounts for the substantial bandwidth gap.

Both cards have zero ROPs and zero pixel rate, indicating they are compute-focused accelerators rather than rasterization-oriented GPUs. Neither has RT cores or tensor cores listed, and both have no display outputs. Their API support is identical: DirectX is N/A, OpenGL is N/A, and Vulkan is N/A. Both share the same physical footprint in length and height: 267 mm (10.5 inches) long and 111 mm (4.4 inches) tall, with the MI350P additionally listed at 40 mm (1.6 inches) wide.

The MI300 was released on 2023-01-03, while the MI350P has a release date of 2026-05-06. Both list Radeon Instinct as their predecessor, and neither has a successor listed in the database.

FAQ

Q: Which accelerator has higher FP32 compute performance?

A: The MI300 delivers 47.87 TFLOPS FP32, which is 32.8% higher than the 36.04 TFLOPS on the MI350P. FP16 performance follows the same pattern, with both cards running FP16 at a 1:1 ratio to FP32.

Q: How much memory bandwidth does each card provide?

A: The MI350P provides 8.19 TB/s of bandwidth from its 144 GB HBM3e memory, while the MI300 provides 5.32 TB/s from its 128 GB HBM3 memory. The MI350P leads by 53.9% in bandwidth and 12.5% in capacity.

Q: Are these cards suitable for display output?

A: No. Both the MI300 and MI350P have no display outputs listed, and their DirectX, OpenGL, and Vulkan APIs are all marked as N/A. They are compute accelerators, not graphics cards.

Q: What power connector does each card use?

A: The MI300 uses two 8-pin power connectors, while the MI350P uses a single 16-pin connector. Both have a 600 W TDP and a suggested PSU of 1000 W.

Q: How do the boost clocks compare?

A: The MI350P boosts to 2200 MHz, which is 29.4% higher than the 1700 MHz boost clock on the MI300. The base clock is identical at 1000 MHz on both cards.

Q: What is the die size difference between the two?

A: The MI350P has a die size of 1190 mm², which is 17.0% larger than the 1017 mm² die on the MI300. Despite the larger die, the MI300 has more than double the transistor count at 153,000 million versus 73,000 million.

Specification Differences

| Specification | AMD Instinct MI300 | AMD Instinct MI350P |

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

| Architecture | CDNA 3.0 | CDNA 4.0 |

| Chip | Aqua Vanjaram | MI350 128CU |

| 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 | 1700 MHz | 2200 MHz |

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

| Memory Size | 128 GB | 144 GB |

| Memory Type | HBM3 | HBM3e |

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

| Shading Units | 14080 | 8192 |

| TMUs | 880 | 512 |

| Texture Rate | 1,496.0 GTexel/s | 1,126.4 GTexel/s |

| FP32 | 47.87 TFLOPS | 36.04 TFLOPS |

| FP16 | 47.87 TFLOPS (1:1) | 36.04 TFLOPS (1:1) |

| Power Connectors | 2x 8-pin | 1x 16-pin |

| Slot Width | Not listed | Dual-slot |

| Width | Not listed | 40 mm 1.6 inches |

| Release Date | 2023-01-03 | 2026-05-06 |

Shared specifications include a 1000 MHz base clock, 8192-bit memory bus width, 0 ROPs, 0 MPixel/s pixel rate, 600 W TDP, 1000 W suggested PSU, PCIe 5.0 x16 bus interface, no display outputs, N/A APIs, 267 mm length, and 111 mm height.

Head-to-Head Benchmarks

The recorded data shows no direct head-to-head benchmark scores in the database, and both cards hold a 50th percentile position among all GPUs with an average benchmark score of zero. The comparison therefore rests on the architectural specifications and computed throughput figures.

The MI300's clearest wins come from its execution resource counts. Its 14,080 shading units exceed the MI350P's 8,192 by 5,888 units, a 71.9% margin. The texture pipeline shows the same proportional gap: 880 TMUs versus 512 TMUs, again a 71.9% advantage. These resource advantages translate directly into throughput. The MI300's 47.87 TFLOPS FP32 output is 11.83 TFLOPS higher than the MI350P's 36.04 TFLOPS, representing a 32.8% lead. Its texture rate of 1,496.0 GTexel/s beats the MI350P's 1,126.4 GTexel/s by 369.6 GTexel/s, also a 32.8% difference. FP16 output mirrors FP32 exactly on both cards, so the MI300 holds the same 32.8% lead there.

The MI350P's wins are concentrated in memory and clock speed. Its 8.19 TB/s bandwidth is 2.87 TB/s higher than the MI300's 5.32 TB/s, a 53.9% advantage. The boost clock of 2200 MHz versus 1700 MHz gives the MI350P a 500 MHz lead, or 29.4% higher boost frequency. Memory capacity is also higher: 144 GB versus 128 GB, a 16 GB difference that amounts to 12.5% more storage. The effective memory speed of 8 Gbps versus 5.2 Gbps represents a 53.8% improvement in per-pin data rate.

Transistor density is a notable MI300 advantage. At 150.4M transistors per mm², it packs 145.7% more density than the MI350P's 61.3M per mm². However, the MI350P's 3 nm process node versus 5 nm on the MI300 shows a newer manufacturing technology, and the MI350P die is larger at 1190 mm² versus 1017 mm², a 17.0% size increase.

The MI300's transistor count advantage is substantial: 153,000 million versus 73,000 million, which is 109.6% more transistors. Yet the MI350P achieves higher boost clocks and memory bandwidth with far fewer transistors, indicating a more efficient design per transistor for those metrics.

The Verdict

The data presents a clear trade-off between the two accelerators. The MI300 is the compute-throughput leader, with higher shading unit counts, higher TMU counts, higher FP32 and FP16 TFLOPS, and a higher texture fill rate. Its 47.87 TFLOPS FP32 output and 1,496.0 GTexel/s texture rate make it the stronger choice for workloads that scale with shader and texture execution resources. The 71.9% advantage in shading units and TMUs is substantial and directly translates to the 32.8% lead in FP32 throughput.

The MI350P is the memory-capacity and bandwidth leader. Its 144 GB HBM3e pool with 8.19 TB/s bandwidth represents a 53.9% bandwidth advantage and 12.5% more capacity than the MI300. For workloads that are memory-bound, such as large model inference or data-intensive compute tasks, the MI350P's bandwidth headroom is the decisive factor. The 2200 MHz boost clock also gives it a 29.4% clock advantage, though the MI300 compensates with more execution units.

The MI300's transistor count of 153,000 million versus 73,000 million on the MI350P suggests the MI300 dedicates far more hardware to compute resources, while the MI350P, despite having fewer transistors, achieves superior memory performance and higher clocks on a larger 1190 mm² die manufactured on a 3 nm process. The MI350P's dual-slot form factor and single 16-pin power connector indicate a different physical design compared to the MI300's two 8-pin connectors.

Both cards share a 600 W TDP, a 1000 W suggested PSU, PCIe 5.0 x16 connectivity, and identical length and height dimensions. Neither has display outputs or rasterization hardware, and both are compute-only accelerators with N/A graphics APIs.

The choice depends on workload characteristics. Compute-heavy tasks that utilize shader and texture throughput favor the MI300. Memory-heavy tasks that require large capacity and high bandwidth favor the MI350P. The MI350P's later release date of 2026-05-06 versus 2023-01-03 on the MI300 reflects a newer generation with a more advanced process node, but the MI300 retains a definitive edge in raw compute throughput. The data shows no single winner; it shows two accelerators optimized for different aspects of accelerated computing.