AMD Instinct MI350X vs AMD Radeon RX 7900M Comparison

FAQ

Q: What are the core architectural differences between the AMD Instinct MI350X and the AMD Radeon RX 7900M?

A: The MI350X uses AMD's CDNA 4.0 architecture on a 3 nm TSMC process with 185,000 million transistors across a 2380 mm² die. The RX 7900M uses RDNA 3.0 on a 5 nm TSMC process with 57,700 million transistors on a 529 mm² die. The MI350X is built for compute workloads, while the RX 7900M is a mobile graphics processor.

Q: How do memory configurations compare between the two?

A: The MI350X features 288 GB of HBM3e memory on an 8192-bit bus with 8.19 TB/s bandwidth. The RX 7900M has 16 GB of GDDR6 memory on a 256-bit bus with 576.0 GB/s bandwidth. The MI350X provides roughly 14 times the memory capacity and over 14 times the bandwidth.

Q: What benchmark data exists for each GPU?

A: The MI350X has no recorded benchmark scores in the database, placing it at the 50th percentile of all GPUs with an average score of 0. The RX 7900M has three recorded benchmark scores: 4,201 in 3DMark Steel Nomad DX12, 129,499 in Geekbench OpenCL, and 158,760 in Geekbench Vulkan, achieving the 94th percentile.

Q: How does the RX 7900M compare to its nearest rivals?

A: The RX 7900M's average benchmark score of 97,487 places it 0.4% above the AMD Radeon Pro VII (97,131), 4.3% below the NVIDIA Quadro RTX 6000 (101,872), 5.4% above the AMD Radeon Instinct MI60 (92,466), and 6.3% above the NVIDIA RTX A4500 (91,671).

Q: What are the power requirements for each card?

A: The MI350X has a 1000 W TDP with a suggested power supply of 1400 W. The RX 7900M has a 180 W TDP with no suggested power supply listed. The MI350X uses an OAM module slot width, while the RX 7900M is an integrated graphics processor (IGP) for portable devices.

Q: What display and API support does each GPU offer?

A: The MI350X has no display outputs and no API support for DirectX, OpenGL, or Vulkan. The RX 7900M provides portable device dependent display outputs and supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4.

Architecture Differences

The AMD Instinct MI350X and AMD Radeon RX 7900M represent fundamentally different design philosophies within AMD's product stack. The MI350X is a data center compute accelerator built on the CDNA 4.0 architecture, while the RX 7900M is a mobile gaming and professional graphics processor based on RDNA 3.0.

The manufacturing processes diverge significantly. The MI350X uses a 3 nm TSMC process with 185,000 million transistors on a 2380 mm² die, yielding a transistor density of 77.7 million transistors per square millimeter. The RX 7900M uses a 5 nm TSMC process with 57,700 million transistors on a 529 mm² die, achieving a higher transistor density of 109.1 million per square millimeter. The MI350X's die is over four times larger in physical area.

The chip designs reflect their intended workloads. The MI350X carries the MI350 256CU chip with 16,384 shading units and 1,024 texture mapping units, but it has zero ROPs and zero pixel rate, confirming its compute-only orientation. The RX 7900M uses the Navi 31 chip with 4,608 shading units, 288 TMUs, 192 ROPs, and 72 ray tracing cores, delivering a pixel rate of 401.3 GPixel/s.

Clock behavior differs substantially. The MI350X operates at a 1000 MHz base clock with a 2200 MHz boost clock. The RX 7900M runs at a higher 1825 MHz base clock but a lower 2090 MHz boost clock. The memory clocks also differ: the MI350X uses 2000 MHz HBM3e memory at 8 Gbps effective, while the RX 7900M uses 2250 MHz GDDR6 at 18 Gbps effective.

The MI350X's memory architecture is designed for massive bandwidth. Its 8192-bit bus width with HBM3e memory produces 8.19 TB/s of bandwidth. The RX 7900M's 256-bit GDDR6 bus delivers 576.0 GB/s. This memory bandwidth disparity directly reflects the MI350X's role in memory-intensive compute workloads.

The interface and form factor also separate these products. The MI350X uses PCIe 5.0 x16 with an OAM module slot width and no power connectors. The RX 7900M uses PCIe 4.0 x16 as an IGP with portable device dependent display outputs. The MI350X measures 102 mm by 165 mm, while the RX 7900M has no recorded dimensions.

API support marks another critical division. The MI350X lists no DirectX, OpenGL, or Vulkan support, while the RX 7900M supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. This difference confirms the MI350X targets compute APIs rather than graphics APIs.

Head-to-Head Benchmarks

The database contains no direct head-to-head benchmark comparisons between the AMD Instinct MI350X and the AMD Radeon RX 7900M. The head-to-head benchmark array is empty, and neither GPU records any wins against the other in this category.

The MI350X has no benchmark entries at all. Its average benchmark score is recorded as 0, and it sits at the 50th percentile of all GPUs in the database. This absence of data reflects its positioning as a compute accelerator without standard graphics benchmark results.

The RX 7900M, by contrast, has three recorded benchmark scores. In 3DMark Steel Nomad DX12, it scores 4,201. In Geekbench OpenCL, it scores 129,499. In Geekbench Vulkan, it scores 158,760. These results produce an average benchmark score of 97,487 and place it at the 94th percentile of all GPUs.

The RX 7900M's nearest rival comparisons provide context for its performance. It sits 0.4% above the AMD Radeon Pro VII's average score of 97,131. The NVIDIA Quadro RTX 6000 leads the RX 7900M by 4.3% with a score of 101,872. The AMD Radeon Instinct MI60 trails by 5.4% at 92,466, and the NVIDIA RTX A4500 trails by 6.3% at 91,671.

These rival deltas indicate the RX 7900M competes in the professional graphics space with workstation cards. Its Vulkan score of 158,760 stands well above its OpenCL score of 129,499, suggesting stronger performance in graphics-oriented workloads than in general compute tasks. The 3DMark Steel Nomad result of 4,201 provides a gaming-oriented data point.

For the MI350X, the lack of benchmark data means no direct performance comparisons can be drawn from the database. Its 50th percentile ranking with zero average score indicates the database treats it as an outlier without standardized test results. The compute specifications suggest substantial capability, but the recorded data does not quantify it.

Specification Differences

The two GPUs differ across nearly every specification category in the database.

Process and die: The MI350X uses a 3 nm process, while the RX 7900M uses 5 nm. The MI350X has 185,000 million transistors on a 2380 mm² die with 77.7 million transistors per square millimeter. The RX 7900M has 57,700 million transistors on a 529 mm² die with 109.1 million per square millimeter.

Clocks: The MI350X runs at 1000 MHz base and 2200 MHz boost. The RX 7900M runs at 1825 MHz base and 2090 MHz boost. Memory clocks are 2000 MHz (8 Gbps effective) for the MI350X and 2250 MHz (18 Gbps effective) for the RX 7900M.

Memory: The MI350X uses 288 GB of HBM3e on an 8192-bit bus with 8.19 TB/s bandwidth. The RX 7900M uses 16 GB of GDDR6 on a 256-bit bus with 576.0 GB/s bandwidth.

Compute units: The MI350X has 16,384 shading units, 1,024 TMUs, and 0 ROPs. The RX 7900M has 4,608 shading units, 288 TMUs, 192 ROPs, and 72 ray tracing cores.

Performance rates: The MI350X delivers 0 MPixel/s pixel rate and 2,252.8 GTexel/s texture rate. The RX 7900M delivers 401.3 GPixel/s pixel rate and 601.9 GTexel/s texture rate. FP32 performance is 72.09 TFLOPS for the MI350X and 38.52 TFLOPS for the RX 7900M. FP16 performance is 72.09 TFLOPS (1:1) for the MI350X and 77.05 TFLOPS (2:1) for the RX 7900M.

Power and form factor: The MI350X has a 1000 W TDP with a 1400 W suggested PSU and OAM module slot width. The RX 7900M has a 180 W TDP with no suggested PSU and IGP slot width. Neither uses power connectors.

Bus and outputs: The MI350X uses PCIe 5.0 x16 with no display outputs. The RX 7900M uses PCIe 4.0 x16 with portable device dependent display outputs.

API support: The MI350X has N/A for DirectX, OpenGL, and Vulkan. The RX 7900M supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4.

Release dates: The MI350X released on June 11, 2025. The RX 7900M released on October 18, 2023.

Where Each One Wins

The AMD Instinct MI350X wins in compute throughput and memory capacity. Its FP32 performance of 72.09 TFLOPS nearly doubles the RX 7900M's 38.52 TFLOPS. Its 288 GB of HBM3e memory with 8.19 TB/s bandwidth provides an enormous advantage for large dataset workloads, with over 14 times the capacity and bandwidth of the RX 7900M. The 8192-bit memory bus and 2,252.8 GTexel/s texture rate position it for data center compute tasks.

The MI350X also wins on power delivery design. Its 1000 W TDP with a 1400 W suggested PSU indicates a system designed for sustained heavy compute, while its OAM module form factor suits rack-mounted server configurations. The PCIe 5.0 x16 interface provides double the bus bandwidth of the RX 7900M's PCIe 4.0 x16 connection. The 3 nm process with 185,000 million transistors enables the largest compute configuration in the database comparison.

The AMD Radeon RX 7900M wins in graphics-oriented workloads. Its 401.3 GPixel/s pixel rate and 192 ROPs enable rasterization tasks that the MI350X cannot perform at all, given its zero ROPs and pixel rate. The 72 ray tracing cores add hardware acceleration for ray-traced rendering, which the MI350X lacks entirely. Vulkan and DirectX 12 Ultimate API support make the RX 7900M suitable for gaming and graphics applications.

The RX 7900M also wins on efficiency and mobility. Its 180 W TDP represents an 82% reduction in power draw compared to the MI350X. The IGP form factor with portable device dependent outputs fits mobile workstations and laptops. The 5 nm process with 109.1 million transistors per square millimeter achieves higher density than the MI350X, indicating compact design efficiency.

The benchmark data shows the RX 7900M has quantifiable performance in the 94th percentile of all GPUs, with an average score of 97,487. Its closest competitor, the NVIDIA Quadro RTX 6000, leads by only 4.3%. The MI350X has no recorded benchmarks, making its 50th percentile ranking a placeholder rather than a measured result.

The FP16 comparison reveals different design priorities. The MI350X delivers 72.09 TFLOPS at 1:1 ratio, meaning equal FP16 and FP32 throughput. The RX 7900M delivers 77.05 TFLOPS at 2:1 ratio, meaning it doubles its FP32 rate when using FP16. The RX 7900M actually exceeds the MI350X in raw FP16 throughput despite its lower FP32 performance.

The use cases diverge clearly. The MI350X suits large-scale compute, AI training, and scientific simulation where memory capacity and FP32 throughput dominate. The RX 7900M suits graphics rendering, gaming, and mobile professional workloads where rasterization, ray tracing, and API compatibility matter. The database records no direct competition between them because they address different market segments entirely.