AMD Instinct MI350X vs NVIDIA RTX 4000 Ada Generation Comparison

FAQ

Q: What are the core architectural identities of the AMD Instinct MI350X and NVIDIA RTX 4000 Ada Generation?

A: The AMD Instinct MI350X uses the CDNA 4.0 architecture on a 3 nm TSMC process, built around the MI350 256CU chip. The NVIDIA RTX 4000 Ada Generation uses the Ada Lovelace architecture on a 5 nm TSMC process, built around the AD104 chip.

Q: How do the two cards differ in memory capacity and type?

A: The AMD Instinct MI350X ships with 288 GB of HBM3e memory on an 8192-bit bus, providing 8.19 TB/s of bandwidth. The NVIDIA RTX 4000 Ada Generation ships with 20 GB of GDDR6 memory on a 160-bit bus, providing 360.0 GB/s of bandwidth.

Q: Which card has higher FP32 compute throughput?

A: The AMD Instinct MI350X delivers 72.09 TFLOPS of FP32 compute. The NVIDIA RTX 4000 Ada Generation delivers 26.73 TFLOPS of FP32 compute, which is roughly one-third of the MI350X's figure.

Q: What is the power draw difference between the two?

A: The AMD Instinct MI350X has a TDP of 1000 W and requires a 1400 W suggested PSU. The NVIDIA RTX 4000 Ada Generation has a TDP of 130 W and requires a 300 W suggested PSU.

Q: Does the NVIDIA card support graphical APIs?

A: Yes, the RTX 4000 Ada Generation supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The AMD Instinct MI350X lists N/A for DirectX, OpenGL, and Vulkan, and has no display outputs.

Q: What is the percentile ranking of the NVIDIA card in the database?

A: The RTX 4000 Ada Generation holds a percentile rank of 95 among all GPUs, with an average benchmark score of 135218. The MI350X holds a percentile rank of 50 with an average benchmark score of 0, as it has no recorded benchmarks in the database.

Where Each One Wins

The recorded data shows a clear split in strengths between the two accelerators. The AMD Instinct MI350X wins decisively in raw compute throughput and memory bandwidth. Its FP32 figure of 72.09 TFLOPS is 2.7 times the 26.73 TFLOPS of the NVIDIA RTX 4000 Ada Generation. Its texture rate of 2,252.8 GTexel/s dwarfs the NVIDIA card's 417.6 GTexel/s, a 5.4x margin. The MI350X also carries 8.19 TB/s of memory bandwidth versus 360.0 GB/s for the RTX 4000 Ada, a 22.7x advantage. This makes the MI350X suited for workloads dominated by large data movement and dense floating-point math.

The NVIDIA RTX 4000 Ada Generation wins in areas tied to graphics output and practical workstation deployment. It has a pixel rate of 139.2 GPixel/s while the MI350X records 0 MPixel/s, reflecting the MI350X's lack of display outputs. The RTX 4000 Ada Generation also supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, whereas the MI350X reports N/A for all three. The NVIDIA card includes 48 RT cores and 192 tensor cores, while the MI350X lists no RT cores or tensor cores. For a workstation needing rendering, display connectivity, or ray-tracing features, the RTX 4000 Ada Generation is the functional option. The MI350X is a compute-only module.

Physical deployment also separates them. The RTX 4000 Ada Generation is a single-slot card, 245 mm long and 112 mm high, with a 130 W TDP and a single 16-pin power connector. The MI350X is an OAM module, 102 mm long and 165 mm wide, with a 1000 W TDP and no power connectors, relying on the host system's power delivery. The MI350X's 1000 W TDP is 7.7 times higher than the RTX 4000 Ada's 130 W TDP.

Architecture Differences

The AMD Instinct MI350X is built on CDNA 4.0, AMD's compute-optimized architecture, using the MI350 256CU chip. It is fabricated on a 3 nm process at TSMC, packing 185,000 million transistors into a 2380 mm² die, for a transistor density of 77.7M per mm². The architecture targets data-center scale compute with HBM3e memory and an 8192-bit bus. The MI350X has 16,384 shading units, 1,024 TMUs, and 0 ROPs. It reports no RT cores and no tensor cores, and its FP16 throughput is identical to its FP32 throughput at 72.09 TFLOPS (1:1), indicating a design that does not split compute paths by precision.

The NVIDIA RTX 4000 Ada Generation uses the Ada Lovelace architecture with the AD104 chip, fabricated on a 5 nm process at TSMC. It packs 35,800 million transistors into a 294 mm² die, for a transistor density of 121.8M per mm², which is higher than the MI350X's density despite the larger process node. The RTX 4000 Ada Generation includes 6,144 shading units, 192 TMUs, 64 ROPs, 48 RT cores, and 192 tensor cores. Its FP16 throughput matches its FP32 throughput at 26.73 TFLOPS (1:1), similar to the MI350X's 1:1 ratio but at a lower absolute level.

The two chips differ fundamentally in their transistor budgets. The MI350X uses 185,000 million transistors, which is 5.2 times the 35,800 million in the AD104. The MI350X's die is 2380 mm², which is 8.1 times the 294 mm² of the RTX 4000 Ada. The MI350X's lower transistor density reflects its massive memory interface and HBM3e integration, while the RTX 4000 Ada's higher density reflects a more conventional GPU layout with graphics features.

Specification Differences

The two cards differ across nearly every major specification. The process node differs: 3 nm for the MI350X, 5 nm for the RTX 4000 Ada Generation. Transistor count differs by a factor of 5.2: 185,000 million for the MI350X versus 35,800 million for the RTX 4000 Ada. Die size is 2380 mm² for the MI350X versus 294 mm² for the RTX 4000 Ada. Transistor density is 77.7M per mm² for the MI350X versus 121.8M per mm² for the RTX 4000 Ada.

Clock speeds differ. The MI350X has a base clock of 1000 MHz and a boost clock of 2200 MHz. The RTX 4000 Ada has a base clock of 1500 MHz and a boost clock of 2175 MHz. Memory clocks also differ: the MI350X runs at 2000 MHz with 8 Gbps effective, while the RTX 4000 Ada runs at 2250 MHz with 18 Gbps effective. Memory capacity is 288 GB for the MI350X versus 20 GB for the RTX 4000 Ada. Memory type is HBM3e for the MI350X versus GDDR6 for the RTX 4000 Ada. Bus width is 8192 bits for the MI350X versus 160 bits for the RTX 4000 Ada. Bandwidth is 8.19 TB/s for the MI350X versus 360.0 GB/s for the RTX 4000 Ada.

Compute resources differ sharply. The MI350X has 16,384 shading units versus 6,144 for the RTX 4000 Ada. TMUs: 1,024 versus 192. ROPs: 0 versus 64. The MI350X has no RT cores or tensor cores; the RTX 4000 Ada has 48 RT cores and 192 tensor cores. Pixel rate is 0 MPixel/s for the MI350X versus 139.2 GPixel/s for the RTX 4000 Ada. Texture rate is 2,252.8 GTexel/s for the MI350X versus 417.6 GTexel/s for the RTX 4000 Ada. FP32 and FP16 are 72.09 TFLOPS for the MI350X versus 26.73 TFLOPS for the RTX 4000 Ada.

Power and physical specs differ as well. TDP is 1000 W for the MI350X versus 130 W for the RTX 4000 Ada. Suggested PSU is 1400 W for the MI350X versus 300 W for the RTX 4000 Ada. The MI350X is an OAM module with no power connectors; the RTX 4000 Ada is a single-slot card with one 16-pin connector. The MI350X is 102 mm long and 165 mm wide; the RTX 4000 Ada is 245 mm long and 112 mm high. The bus interface is PCIe 5.0 x16 for the MI350X versus PCIe 4.0 x16 for the RTX 4000 Ada. Display outputs: the MI350X has none; the RTX 4000 Ada has four DisplayPort 1.4a outputs. API support: the MI350X reports N/A for DirectX, OpenGL, and Vulkan; the RTX 4000 Ada supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. Release dates differ: the MI350X launched on 2025-06-11, the RTX 4000 Ada on 2023-08-08.

Head-to-Head Benchmarks

The database contains no direct head-to-head benchmark entries between the AMD Instinct MI350X and the NVIDIA RTX 4000 Ada Generation. The MI350X has no recorded benchmark scores and an average benchmark score of 0, placing it at the 50th percentile among all GPUs. The RTX 4000 Ada Generation has two recorded benchmarks: a Geekbench OpenCL score of 146,593 and a Geekbench Vulkan score of 123,842. Its average benchmark score is 135,218, placing it at the 95th percentile among all GPUs.

The RTX 4000 Ada Generation's nearest rivals in the database provide context for its standing. The NVIDIA A10M sits at an average score of 135,230 with a delta of 0%, effectively matching the RTX 4000 Ada. The AMD Radeon PRO W6800 scores 135,396, which is 0.1% higher. The AMD Radeon Pro W6800X Duo scores 135,774, 0.4% higher. The AMD Radeon PRO V620 scores 136,472, 0.9% higher. These deltas indicate that the RTX 4000 Ada Generation sits at the lower end of a tightly clustered group of workstation GPUs, all within 1% of each other.

Comparing the two cards directly requires relying on their published specifications rather than shared benchmarks. The MI350X's FP32 compute of 72.09 TFLOPS is 2.7 times the RTX 4000 Ada's 26.73 TFLOPS. The MI350X's texture rate of 2,252.8 GTexel/s is 5.4 times the RTX 4000 Ada's 417.6 GTexel/s. The MI350X's memory bandwidth of 8.19 TB/s is 22.7 times the RTX 4000 Ada's 360.0 GB/s. The RTX 4000 Ada counters with a pixel rate of 139.2 GPixel/s versus 0 MPixel/s for the MI350X, and it is the only one of the two with graphics API support and display outputs.

The percentile gap is notable. The RTX 4000 Ada Generation sits at the 95th percentile with an average score of 135,218, while the MI350X sits at the 50th percentile with an average score of 0. That discrepancy reflects missing benchmark data for the MI350X rather than measured performance. The MI350X's specifications suggest it is designed for a different workload class: 288 GB of HBM3e, an 8192-bit bus, and 72.09 TFLOPS of FP32 point to large-scale compute tasks, while the RTX 4000 Ada Generation's 20 GB of GDDR6, 48 RT cores, and 192 tensor cores point to professional graphics and rendering workloads. The data shows two accelerators aimed at opposite ends of the compute spectrum, with the MI350X prioritizing raw throughput and memory capacity and the RTX 4000 Ada Generation prioritizing graphics features and power efficiency.