AMD Instinct MI350P vs AMD Radeon Instinct MI300X Comparison

Head-to-Head Benchmarks

The recorded data shows no benchmark entries for either the AMD Instinct MI350P or the AMD Radeon Instinct MI300X. The database contains no head-to-head benchmark comparisons, no individual benchmark scores, and no average benchmark scores for either accelerator. Both parts also sit at the 50th percentile against all GPUs, which is a neutral position indicating no measured performance data has been logged for either product.

Without benchmark scores, the only quantitative comparisons available come from the specification sheets. In raw compute throughput, the MI300X delivers 81.72 TFLOPS FP32, which is more than double the 36.04 TFLOPS FP32 of the MI350P. The MI300X also produces 653.7 TFLOPS FP16 using an 8:1 ratio, while the MI350P produces 36.04 TFLOPS FP16 at a 1:1 ratio. The texture rate follows the same pattern: the MI300X reaches 2,553.6 GTexel/s against 1,126.4 GTexel/s for the MI350P. Pixel rate is recorded as 0 MPixel/s for both, since these are compute accelerators without traditional raster output stages.

Memory capacity favors the MI300X as well, with 192 GB of HBM3 versus 144 GB of HBM3e for the MI350P. Memory bandwidth sits at 10.3 TB/s for the MI300X and 8.19 TB/s for the MI350P. Both use an 8192-bit memory bus. The MI300X carries 19,456 shading units and 1,216 texture mapping units, while the MI350P has 8,192 shading units and 512 TMUs. Clock speeds differ modestly: both have a 1000 MHz base clock, but the MI350P boosts to 2200 MHz versus 2100 MHz for the MI300X. Memory clocks are 2000 MHz (8 Gbps effective) for the MI350P and 2525 MHz (10.1 Gbps effective) for the MI300X.

The MI350P does hold advantages in process node and transistor density. It uses a 3 nm process from TSMC versus 5 nm for the MI300X. Its die is larger at 1190 mm² compared to 1017 mm², yet it packs far fewer transistors at 73,000 million versus 153,000 million. The density figures reflect this: 61.3M transistors per mm² for the MI350P and 150.4M per mm² for the MI300X. The MI350P uses the newer CDNA 4.0 architecture, while the MI300X uses CDNA 3.0.

Power draw is lower for the MI350P at 600 W TDP versus 750 W for the MI300X. The MI350P also suggests a 1000 W PSU rather than 1150 W. Slot design differs: the MI350P is dual-slot with a single 16-pin power connector, while the MI300X is an OAM module with no power connectors listed. The MI350P has physical dimensions of 267 mm length, 111 mm height, and 40 mm width; the MI300X has no recorded dimensions.

The Verdict

The data supports selecting the MI300X for workloads that depend on raw compute throughput and memory bandwidth. It delivers 81.72 TFLOPS FP32, 653.7 TFLOPS FP16, 10.3 TB/s memory bandwidth, and 192 GB of HBM3. Every one of these figures is higher than the corresponding MI350P value. For FP32-heavy or FP16-heavy inference and training tasks, the MI300X specification sheet is strictly superior.

The MI350P is the choice when power efficiency and physical integration matter. It draws 600 W versus 750 W, fits a dual-slot PCIe form factor with a standard 16-pin connector, and uses a 3 nm process. Its die is larger, but its transistor count is dramatically lower at 73,000 million versus 153,000 million. The MI350P also has a higher boost clock at 2200 MHz versus 2100 MHz, which suggests a different clock-per-compute-unit design philosophy, though without benchmark data the actual performance impact cannot be quantified.

Neither part has any recorded benchmark scores, average scores, or rival comparisons in the database. The percentile rank for both is identical at 50. This means any purchase decision must rely entirely on the specification differences, not on measured performance data.

FAQ

Q: Which accelerator has higher FP32 compute?

A: The AMD Radeon Instinct MI300X, with 81.72 TFLOPS FP32 compared to 36.04 TFLOPS for the AMD Instinct MI350P.

Q: How much memory does each accelerator have?

A: The MI300X has 192 GB of HBM3, while the MI350P has 144 GB of HBM3e.

Q: What are the memory bandwidth figures?

A: The MI300X records 10.3 TB/s, and the MI350P records 8.19 TB/s. Both use an 8192-bit bus.

Q: Which uses a newer manufacturing process?

A: The MI350P uses a 3 nm process from TSMC, while the MI300X uses 5 nm from TSMC.

Q: What is the TDP of each?

A: The MI350P is rated at 600 W, and the MI300X is rated at 750 W.

Q: Do either have benchmark scores in the database?

A: No. Both have no benchmark entries, no average benchmark score, and no nearest rivals listed.

Specification Differences

The two accelerators differ across nearly every recorded specification. The MI350P uses the MI350 128CU chip, while the MI300X uses the Aqua Vanjaram chip. Architecture differs: CDNA 4.0 for the MI350P, CDNA 3.0 for the MI300X. Process nodes are 3 nm versus 5 nm. Transistor counts are 73,000 million versus 153,000 million. Die sizes are 1190 mm² versus 1017 mm². Transistor density is 61.3M per mm² versus 150.4M per mm².

Boost clocks are 2200 MHz versus 2100 MHz. Memory clocks are 2000 MHz (8 Gbps effective) versus 2525 MHz (10.1 Gbps effective). Memory size is 144 GB HBM3e versus 192 GB HBM3. Bandwidth is 8.19 TB/s versus 10.3 TB/s. Shading units are 8,192 versus 19,456. TMUs are 512 versus 1,216. FP32 is 36.04 TFLOPS versus 81.72 TFLOPS. FP16 is 36.04 TFLOPS (1:1) versus 653.7 TFLOPS (8:1). Texture rate is 1,126.4 GTexel/s versus 2,553.6 GTexel/s.

TDP is 600 W versus 750 W. Slot width is dual-slot versus OAM Module. Power connectors are 1x 16-pin versus none. Suggested PSU is 1000 W versus 1150 W. Dimensions exist only for the MI350P: 267 mm by 111 mm by 40 mm. The MI300X has no recorded dimensions.

Architecture Differences

The MI350P is built on CDNA 4.0 and a 3 nm TSMC process. It uses 73,000 million transistors on a 1190 mm² die, yielding a density of 61.3M transistors per mm². The architecture pairs 8,192 shading units with 512 TMUs and no ROPs. FP16 throughput matches FP32 at 36.04 TFLOPS with a 1:1 ratio, which indicates a design that does not double-rate FP16 work. The memory subsystem uses HBM3e with 144 GB capacity and 8.19 TB/s bandwidth on an 8192-bit bus. The 128CU chip designation and 2200 MHz boost clock define the compute layout. The MI350P carries no display outputs and no API support for DirectX, OpenGL, or Vulkan.

The MI300X is built on CDNA 3.0 and a 5 nm TSMC process. It uses 153,000 million transistors on a 1017 mm² die, yielding a density of 150.4M transistors per mm². The architecture has 19,456 shading units and 1,216 TMUs with no ROPs. FP16 throughput is 653.7 TFLOPS at an 8:1 ratio, meaning the hardware performs eight FP16 operations per FP32 operation. Memory is HBM3 with 192 GB capacity and 10.3 TB/s bandwidth on an 8192-bit bus. The Aqua Vanjaram chip boosts to 2100 MHz. It also has no display outputs and no recorded API support.

The transistor density gap is notable: the MI300X packs more than twice the transistors per square millimeter despite using an older process node. The MI350P uses a smaller transistor budget but a larger die. The FP16 ratio difference is the defining architectural choice. The MI350P treats FP16 and FP32 as equal throughput, while the MI300X heavily favors FP16. The MI300X also carries significantly more shading units and TMUs, which explains its higher texture rate and FP32 output.

Where Each One Wins

The MI300X wins every compute and memory category with recorded numbers. It leads in FP32, FP16, texture rate, shading units, TMUs, memory capacity, memory bandwidth, and memory clock speed. For workloads that are throughput-bound, the MI300X is the stronger part on paper. The 653.7 TFLOPS FP16 figure is especially dominant for dense FP16 matrix operations, and the 192 GB HBM3 pool provides more capacity for large model residency.

The MI350P wins in power, process, and form factor. It draws 600 W versus 750 W, which lowers the suggested PSU requirement from 1150 W to 1000 W. It fits a dual-slot design with a 1x 16-pin connector, making it compatible with standard PCIe server enclosures, while the MI300X requires an OAM module. The 3 nm process yields a smaller transistor budget at 73,000 million, and the boost clock is 100 MHz higher at 2200 MHz. For FP16 workloads that do not need the 8:1 throughput advantage, the MI350P's 1:1 ratio simplifies performance modeling.

The MI350P also has a clearly defined physical footprint at 267 mm by 111 mm by 40 mm, which is useful for planning server layouts. The MI300X has no recorded dimensions, so physical integration details remain unspecified. Neither accelerator offers display outputs, and neither has benchmark data to confirm real-world performance. The database currently provides only specification-level guidance.