AMD Instinct MI300 vs AMD Instinct MI350X Comparison

Head-to-Head Benchmarks

The database contains no recorded head-to-head benchmark results for the AMD Instinct MI300 versus the AMD Instinct MI350X. WinsA and winsB are both zero, and the headToHeadBenchmarks array is empty. The average benchmark score for both accelerators is zero, placing each at the 50th percentile among all GPUs in the database. Without measured performance deltas, direct score-based comparison is impossible, but the recorded specifications provide a basis for evaluating relative capability.

The raw compute figures show the MI350X at 72.09 TFLOPS FP32 and 72.09 TFLOPS FP16 (1:1), while the MI300 delivers 47.87 TFLOPS in both FP32 and FP16 (1:1). That places the MI350X approximately 51% ahead in peak FP32 throughput, a substantial increase for workloads that scale with raw floating-point operations. Texture rate follows a similar pattern: the MI350X reaches 2,252.8 GTexel/s versus 1,496.0 GTexel/s on the MI300, a gain of roughly 51% as well. Both accelerators report a pixel rate of 0 MPixel/s, consistent with their lack of display outputs and their role as compute-focused parts rather than graphics renderers.

Memory bandwidth is another major differentiator. The MI350X carries 288 GB of HBM3e across an 8192-bit bus, delivering 8.19 TB/s. The MI300 carries 128 GB of HBM3 across the same 8192-bit bus width, delivering 5.32 TB/s. That is a 54% bandwidth advantage for the newer part, a meaningful margin for memory-bound training and inference kernels. The effective memory clock also rises from 5.2 Gbps on the MI300 to 8 Gbps on the MI350X, while the memory clock itself moves from 1300 MHz to 2000 MHz.

Boost clocks separate the two as well. The MI300 boosts to 1700 MHz, while the MI350X boosts to 2200 MHz, a 500 MHz increase. Base clocks are identical at 1000 MHz. The higher boost clock on the MI350X directly contributes to its compute and texture throughput advantages.

Architecture Differences

The MI300 uses the CDNA 3.0 architecture, built on TSMC's 5 nm process. The MI350X uses CDNA 4.0, built on TSMC's 3 nm process. The process change allows the MI350X to pack substantially more hardware despite a much larger die. Transistor counts are 153,000 million for the MI300 and 185,000 million for the MI350X, a 32,000 million increase. Die size grows from 1017 mm² to 2380 mm², more than doubling the physical silicon area. Transistor density actually declines on the newer part: the MI300 achieves 150.4M transistors per mm², while the MI350X achieves 77.7M per mm². The density drop reflects the larger die and the different design goals of the CDNA 4.0 generation, which prioritizes total compute and memory capacity over density.

Compute unit counts scale accordingly. The MI300 features 14,080 shading units, 880 texture mapping units, and no ROPs. The MI350X features 16,384 shading units and 1,024 texture mapping units, also with no ROPs. Neither accelerator includes ray tracing cores or tensor cores as separate hardware blocks in the recorded data. Both parts have identical bus interfaces: PCIe 5.0 x16. Neither has display outputs, and both report N/A for DirectX, OpenGL, and Vulkan API support, confirming their role as headless compute accelerators.

Memory technology differs significantly. The MI300 uses HBM3, while the MI350X uses HBM3e. Capacity jumps from 128 GB to 288 GB, and bandwidth from 5.32 TB/s to 8.19 TB/s. The bus width remains 8192 bit on both, so the bandwidth gain comes entirely from the faster HBM3e memory and its higher effective data rate.

Physical design also changes. The MI300 is a PCIe card measuring 267 mm in length and 111 mm in height, with dual 8-pin power connectors and a suggested PSU of 1000 W. The MI350X is an OAM module with a length of 102 mm and a width of 165 mm, no power connectors listed, and a suggested PSU of 1400 W. Power draw rises from 600 W on the MI300 to 1000 W on the MI350X, a 400 W increase that tracks the added compute and memory resources.

Release timing places the MI300 on 2023-01-03 and the MI350X on 2025-06-11, with the latter arriving roughly two and a half years later. Both list "Radeon Instinct" as their predecessor, and neither has a recorded successor. Neither part has a launch MSRP in the database.

Where Each One Wins

The MI350X wins outright in every recorded performance-oriented specification. Its FP32 throughput of 72.09 TFLOPS tops the MI300's 47.87 TFLOPS. Its FP16 throughput of 72.09 TFLOPS likewise tops 47.87 TFLOPS. Texture rate favors the MI350X at 2,252.8 GTexel/s versus 1,496.0 GTexel/s. Memory bandwidth favors the MI350X at 8.19 TB/s versus 5.32 TB/s, and memory capacity favors it at 288 GB versus 128 GB. The MI350X also boosts higher at 2200 MHz versus 1700 MHz.

The MI300 retains advantages only in select physical and efficiency-related fields. It has a smaller die at 1017 mm² versus 2380 mm², a higher transistor density at 150.4M per mm² versus 77.7M per mm², and a lower TDP at 600 W versus 1000 W. Its suggested PSU is also lower at 1000 W versus 1400 W. The MI300 uses a standard PCIe card form factor with 2x 8-pin power connectors, which may fit into existing server chassis more readily than the OAM module form factor of the MI350X. Its 267 mm length and 111 mm height are conventional card dimensions, while the MI350X's 102 mm by 165 mm footprint reflects a module layout.

For workloads where power draw and chassis compatibility are the limiting constraints, the MI300's lower 600 W TDP and smaller 1017 mm² die are notable. For workloads where peak compute, memory capacity, or memory bandwidth dominate, the MI350X is the clear choice. The MI300 is the only one of the two with a recorded slot width, power connector requirement, and height dimension, making it easier to slot into standard PCIe server platforms. The MI350X, as an OAM module, targets dense accelerator trays where the system provides power delivery rather than the card itself.

Neither part has display outputs, so neither suits workstation graphics duties. Both report N/A for graphics APIs, reinforcing that these are pure compute accelerators.

FAQ

Q: Which accelerator has higher FP32 compute throughput?

A: The MI350X delivers 72.09 TFLOPS FP32, compared to 47.87 TFLOPS on the MI300. That is roughly a 51% advantage for the MI350X.

Q: How much memory does each accelerator provide, and what type?

A: The MI300 provides 128 GB of HBM3, while the MI350X provides 288 GB of HBM3e. Memory bandwidth is 5.32 TB/s on the MI300 and 8.19 TB/s on the MI350X.

Q: What are the power requirements for each?

A: The MI300 has a TDP of 600 W and a suggested PSU of 1000 W, using 2x 8-pin power connectors. The MI350X has a TDP of 1000 W and a suggested PSU of 1400 W, with no power connectors listed, consistent with its OAM module form factor.

Q: Are these accelerators suitable for graphics or display output?

A: No. Both report no display outputs, and both list N/A for DirectX, OpenGL, and Vulkan API support. Pixel rate is 0 MPixel/s on both.

Q: What process nodes do the two accelerators use?

A: The MI300 uses TSMC's 5 nm process, and the MI350X uses TSMC's 3 nm process. The MI300 packs 153,000 million transistors into a 1017 mm² die, while the MI350X packs 185,000 million transistors into a 2380 mm² die.

Q: When was each accelerator released?

A: The MI300 was released on 2023-01-03, and the MI350X was released on 2025-06-11. Both belong to the Instinct (MIx) generation and list Radeon Instinct as their predecessor.

The Verdict

The data favors the MI350X for any workload that scales with compute throughput, memory capacity, or memory bandwidth. It offers 72.09 TFLOPS FP32, 288 GB of HBM3e, and 8.19 TB/s of bandwidth, all clear improvements over the MI300's 47.87 TFLOPS, 128 GB of HBM3, and 5.32 TB/s. The newer 3 nm process, higher 2200 MHz boost clock, and larger 2380 mm² die with 185,000 million transistors position it as the more capable accelerator in absolute terms.

The MI300 remains relevant in deployments where power envelope and form factor matter more than peak throughput. Its 600 W TDP, 1000 W suggested PSU, and standard PCIe card with 2x 8-pin connectors make it easier to integrate into conventional servers. Its 1017 mm² die and 150.4M transistors per mm² density also indicate a more compact design, which may matter in space-constrained systems.

There are no recorded benchmark scores for either part, so the verdict rests entirely on specification-level analysis. The percentileVsAllGpus field places both at 50, and the average benchmark score is zero for both. Buyers selecting between the two should weigh the MI350X's substantial compute and memory advantages against the MI300's lower power draw and simpler physical integration. For raw capability, the MI350X is the stronger part. For low-power or retrofit scenarios, the MI300 holds a practical edge.