AMD Instinct MI350X vs NVIDIA RTX 3500 Embedded Ada Generation Comparison

Head-to-Head Benchmarks

The recorded data contains no direct head-to-head benchmark comparisons between the AMD Instinct MI350X and the NVIDIA RTX 3500 Embedded Ada Generation. Both entries show an average benchmark score of zero, and neither has any listed benchmark results or nearest rivals in the database. The percentile versus all GPUs is identical at 50 for both parts, which places them at the median of the database distribution, but this figure carries little analytical weight without underlying scores to differentiate them.

What the data does show is a dramatic gap in raw compute specifications. The MI350X delivers 72.09 TFLOPS FP32, which is 3.13 times the 23.04 TFLOPS FP32 of the RTX 3500 Embedded Ada. This is not a marginal advantage; it is a fundamental difference in compute capacity. The FP16 figures mirror this exactly, with both parts offering 1:1 FP16 to FP32 ratios, so the MI350X also holds a 3.13x lead in half-precision work. The texture rate gap is even larger: 2,252.8 GTexel/s versus 360.0 GTexel/s, a 6.26x difference. The pixel rate comparison is more nuanced, as the MI350X records 0 MPixel/s, meaning it has no raster output stage in the conventional sense, while the RTX 3500 Embedded Ada reaches 144.0 GPixel/s.

Memory bandwidth is another area of massive divergence. The MI350X has 8.19 TB/s of bandwidth, which is 18.96 times the 432.0 GB/s of the RTX 3500 Embedded Ada. The memory capacity difference is similarly stark: 288 GB versus 12 GB, a 24x gap. These numbers indicate that the MI350X is designed for workloads where memory capacity and bandwidth are the primary constraints, whereas the RTX 3500 Embedded Ada operates in a much more constrained power and physical envelope.

Architecture Differences

The two accelerators come from fundamentally different design philosophies. The AMD Instinct MI350X uses the CDNA 4.0 architecture, built on a 3 nm process at TSMC. It contains 185,000 million transistors on a 2380 mm² die, which works out to a transistor density of 77.7 million transistors per square millimeter. This is a massive, compute-focused die with no display outputs, no API support for DirectX, OpenGL, or Vulkan, and no raster operations pipeline. The chip is designated MI350 256CU, indicating 256 compute units. The shading unit count is 16,384, with 1,024 texture mapping units and zero ROPs.

The NVIDIA RTX 3500 Embedded Ada Generation uses the Ada Lovelace architecture, also fabricated by TSMC but on a 5 nm process. It packs 35,800 million transistors into a 294 mm² die, giving a transistor density of 121.8 million transistors per square millimeter. This is a much denser design, achieving 1.57x the transistor density of the MI350X despite the larger process node. The chip is AD104, and it includes 5,120 shading units, 160 TMUs, 64 ROPs, 40 ray tracing cores, and 160 tensor cores. Unlike the MI350X, it supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, though it has no display outputs.

The process node difference is notable: 3 nm versus 5 nm. The MI350X uses the smaller node, which allows for an enormous die of 2380 mm². The RTX 3500 Embedded Ada is much smaller at 294 mm², and its higher density reflects a design that balances compute with power efficiency. The MI350X is a 1000 W part, while the RTX 3500 Embedded Ada is rated at 100 W. This 10x power difference contextualizes the compute gap: the MI350X uses far more power to deliver its 3.13x FP32 advantage, meaning the NVIDIA part is substantially more compute-efficient per watt. The suggested PSU figures reinforce this: 1400 W for the MI350X versus 300 W for the RTX 3500 Embedded Ada.

Memory technology diverges as well. The MI350X uses HBM3e across an 8192-bit bus, while the RTX 3500 Embedded Ada uses GDDR6 across a 192-bit bus. The memory clock for the MI350X is 2000 MHz with 8 Gbps effective, while the NVIDIA part runs at 2250 MHz with 18 Gbps effective. The bus width difference dominates: 8192 bits is 42.67 times the 192-bit bus of the NVIDIA part, which explains the bandwidth gulf.

FAQ

Q: Why does the AMD Instinct MI350X have a 0 MPixel/s pixel rate?

A: The MI350X records 0 ROPs in the database. With no raster output units, it cannot perform conventional pixel rasterization. This is consistent with a compute-oriented accelerator that lists no display outputs and no DirectX, OpenGL, or Vulkan API support. The RTX 3500 Embedded Ada, by contrast, has 64 ROPs and a 144.0 GPixel/s pixel rate.

Q: Which part has higher FP32 compute throughput?

A: The MI350X delivers 72.09 TFLOPS FP32, which is 3.13 times the 23.04 TFLOPS of the RTX 3500 Embedded Ada. Both parts operate at a 1:1 FP16 to FP32 ratio, so the same 3.13x ratio applies to FP16 workloads.

Q: How do the power requirements compare?

A: The MI350X has a TDP of 1000 W and a suggested PSU of 1400 W. The RTX 3500 Embedded Ada has a TDP of 100 W and a suggested PSU of 300 W. The MI350X consumes 10 times the power of the NVIDIA part.

Q: What memory types do these accelerators use?

A: The MI350X uses HBM3e with 288 GB capacity across an 8192-bit bus, providing 8.19 TB/s bandwidth. The RTX 3500 Embedded Ada uses GDDR6 with 12 GB capacity across a 192-bit bus, providing 432.0 GB/s bandwidth.

Q: Are both parts currently in production?

A: The database lists the NVIDIA RTX 3500 Embedded Ada Generation as having an Active production status. The production status for the AMD Instinct MI350X is not listed in the record.

Q: What is the release timing for each part?

A: The MI350X has a release date of 2025-06-11, while the RTX 3500 Embedded Ada Generation was released on 2023-03-20. The NVIDIA part also has a listed successor, Blackwell-MW, which the AMD part does not have in the database.

Specification Differences

The following fields differ between the two entries:

Process node: 3 nm (AMD) versus 5 nm (NVIDIA).

Transistors: 185,000 million (AMD) versus 35,800 million (NVIDIA).

Die size: 2380 mm² (AMD) versus 294 mm² (NVIDIA).

Transistor density: 77.7 million per mm² (AMD) versus 121.8 million per mm² (NVIDIA).

Base clock: 1000 MHz (AMD) versus 1725 MHz (NVIDIA).

Boost clock: 2200 MHz (AMD) versus 2250 MHz (NVIDIA).

Memory clock: 2000 MHz, 8 Gbps effective (AMD) versus 2250 MHz, 18 Gbps effective (NVIDIA).

Memory size: 288 GB (AMD) versus 12 GB (NVIDIA).

Memory type: HBM3e (AMD) versus GDDR6 (NVIDIA).

Memory bus width: 8192 bit (AMD) versus 192 bit (NVIDIA).

Memory bandwidth: 8.19 TB/s (AMD) versus 432.0 GB/s (NVIDIA).

Shading units: 16,384 (AMD) versus 5,120 (NVIDIA).

TMUs: 1,024 (AMD) versus 160 (NVIDIA).

ROPs: 0 (AMD) versus 64 (NVIDIA).

Ray tracing cores: None listed (AMD) versus 40 (NVIDIA).

Tensor cores: None listed (AMD) versus 160 (NVIDIA).

Pixel rate: 0 MPixel/s (AMD) versus 144.0 GPixel/s (NVIDIA).

Texture rate: 2,252.8 GTexel/s (AMD) versus 360.0 GTexel/s (NVIDIA).

FP32: 72.09 TFLOPS (AMD) versus 23.04 TFLOPS (NVIDIA).

TDP: 1000 W (AMD) versus 100 W (NVIDIA).

Slot width: OAM Module (AMD) versus IGP (NVIDIA).

Suggested PSU: 1400 W (AMD) versus 300 W (NVIDIA).

Bus interface: PCIe 5.0 x16 (AMD) versus PCIe 4.0 x16 (NVIDIA).

API support: None listed (AMD) versus DirectX 12 Ultimate (12_2), OpenGL 4.6, Vulkan 1.4 (NVIDIA).

Dimensions: 102 mm length, 165 mm width (AMD) versus no dimensions listed (NVIDIA).

Release date: 2025-06-11 (AMD) versus 2023-03-20 (NVIDIA).

Predecessor: Radeon Instinct (AMD) versus Ampere-MW (NVIDIA).

Successor: None listed (AMD) versus Blackwell-MW (NVIDIA).

Production status: Not listed (AMD) versus Active (NVIDIA).

The series and generation fields also differ. The NVIDIA part is listed under the GeForce 30-series with an Ada-MW generation, while the AMD part has no series designation and a generation of Instinct (MIx). The chip identifiers are MI350 256CU for AMD and AD104 for NVIDIA.

Where Each One Wins

The AMD Instinct MI350X wins decisively in raw compute throughput. Its 72.09 TFLOPS FP32 and FP16 figures are 3.13x higher than the NVIDIA part. Texture throughput is 6.26x higher at 2,252.8 GTexel/s. Memory capacity is 24x larger at 288 GB, and bandwidth is 18.96x higher at 8.19 TB/s. The 8192-bit memory bus is 42.67x wider than the NVIDIA part's 192-bit bus. The MI350X also uses a more advanced 3 nm process and a newer PCIe 5.0 x16 interface versus the NVIDIA part's PCIe 4.0 x16. The larger transistor count of 185,000 million versus 35,800 million reflects the scale of the compute die.

The NVIDIA RTX 3500 Embedded Ada Generation wins in power efficiency, rasterization capability, and API compatibility. It consumes 100 W versus 1000 W, so it delivers its 23.04 TFLOPS at one tenth the power draw. Its 64 ROPs and 144.0 GPixel/s pixel rate give it conventional graphics capabilities that the MI350X lacks entirely. It also supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, while the MI350X lists no API support. The NVIDIA part has 40 ray tracing cores and 160 tensor cores, features absent from the AMD specification. Its transistor density is 1.57x higher at 121.8 million per mm², indicating a more efficient use of silicon area. The NVIDIA part is also listed as Active in production, while the AMD part's status is not recorded.

The base clock of the NVIDIA part is 1725 MHz versus 1000 MHz for the AMD part, and the boost clock is also slightly higher at 2250 MHz versus 2200 MHz. The NVIDIA part uses faster effective memory at 18 Gbps versus 8 Gbps, though the AMD part compensates with a vastly wider bus and more memory channels.

The Verdict

The data describes two accelerators with almost no overlap in intended use. The AMD Instinct MI350X is a 1000 W, 288 GB HBM3e compute accelerator with no display outputs and no graphics API support. It is built for workloads that can consume its 72.09 TFLOPS FP32, 8.19 TB/s bandwidth, and 288 GB memory capacity. The 2380 mm² die and 185,000 million transistors indicate a design optimized for maximum compute density in a server or data center context. The OAM Module slot width and the absence of power connectors further suggest an integrated system-level deployment rather than a user-installable card.

The NVIDIA RTX 3500 Embedded Ada Generation is a 100 W IGP-class part with 12 GB GDDR6, 23.04 TFLOPS FP32, and full graphics API support. Its 64 ROPs, 40 ray tracing cores, and 160 tensor cores make it a functional graphics processor, despite having no display outputs in the database record. The 294 mm² die and 121.8 million transistors per mm² density indicate a design that prioritizes efficiency. The 5 nm process and 100 W power envelope position it for embedded or mobile applications where power and space are limited.

The MI350X is the clear choice for compute-bound tasks that require massive memory capacity and bandwidth. The RTX 3500 Embedded Ada is the clear choice for applications that need rasterization, ray tracing, or API support within a 100 W power budget. The 10x power difference and the 24x memory capacity difference define the boundary between them. The MI350X trades power efficiency and graphics features for raw throughput; the RTX 3500 Embedded Ada trades throughput for efficiency and flexibility. Neither part can substitute for the other across the other's strengths. A workload that fits within 12 GB of memory and 100 W would be poorly served by the MI350X; a workload that needs 288 GB of memory or 8.19 TB/s of bandwidth would be impossible on the RTX 3500 Embedded Ada. The recorded data supports only this binary split.