Intel Data Center GPU Max 1350 vs NVIDIA N1 16SM Comparison

The Verdict

The data presents two fundamentally different compute devices. The Intel Data Center GPU Max 1350 is a discrete accelerator built for massive parallel throughput, while the NVIDIA N1 16SM is an integrated graphics processor within a Blackwell IGP package. The Intel part, with its 44.44 TFLOPS FP32 throughput, is designed for heavy data center compute workloads. The NVIDIA N1 16SM, delivering 9.609 TFLOPS FP32, targets a different segment where integration and power efficiency take priority.

The recorded data shows no benchmark scores for either device, so direct performance comparisons rely entirely on architectural specifications. The Intel part holds decisive advantages in raw compute resources, memory bandwidth, and texture throughput. The NVIDIA part counters with a significantly smaller die, a more advanced process node, and a unified memory architecture typical of integrated processors. The choice between them depends on whether a workload requires the massive parallel capacity of a discrete accelerator or the compact integration of an IGP.

Architecture Differences

The Intel Data Center GPU Max 1350 uses the Ponte Vecchio chip built on Intel's Generation 12.5 architecture. It is manufactured on a 10 nm process at Intel's own foundry. The die measures 1280 mm² and contains 100,000 million transistors, yielding a transistor density of 78.1M per mm². This is a large, multi-die accelerator package designed for maximum compute density.

The NVIDIA N1 16SM uses the GB20B chip based on Blackwell 2.0 architecture. It is fabricated on a 5 nm process at TSMC, a more advanced node than Intel's 10 nm. The die size is 382 mm², substantially smaller than the Intel part. Transistor counts and density are not recorded for the NVIDIA chip, but the smaller die with a more advanced process indicates a different design philosophy focused on integration efficiency.

The Intel part packs 14,336 shading units, 896 texture mapping units, and 112 ray tracing cores. It has no raster operation units, with a pixel rate of 0 MPixel/s. The NVIDIA part contains 2,048 shading units, 128 TMUs, 24 ROPs, and 16 ray tracing cores. It also includes 64 tensor cores, a feature not listed for the Intel accelerator. The NVIDIA part delivers a pixel rate of 56.30 GPixel/s, a capability the Intel part lacks entirely.

Clock behavior differs markedly. The Intel part runs at a 750 MHz base clock with a 1550 MHz boost. The NVIDIA part operates at a 741 MHz base clock but boosts to 2346 MHz. The higher boost clock on the NVIDIA part partially compensates for its lower core count, though the sheer scale of the Intel core array still dominates raw throughput.

Memory configurations reflect their different roles. The Intel part uses 96 GB of HBM2e on an 8192-bit bus, delivering 2.46 TB/s of bandwidth. The NVIDIA part uses 128 GB of LPDDR5X on a 256-bit bus, providing 273.2 GB/s. The Intel bandwidth is nearly nine times higher, which is critical for memory-bound data center workloads. The NVIDIA part offers more capacity but far lower bandwidth, typical of shared system memory in an IGP.

The Intel part is a 450 W OAM module with no display outputs and no power connectors listed, requiring a suggested 850 W power supply. The NVIDIA part is an IGP with no recorded TDP, no power connectors, and one HDMI output. The Intel part supports DirectX 12 (12_1) and OpenGL 4.6, while the NVIDIA part reports no API support for DirectX, OpenGL, or Vulkan, indicating a compute-focused role.

The Intel part was released on 2023-01-09 and lists the H3C Graphics as its successor. The NVIDIA part is dated 2026-05-31 with no successor recorded. Both are marked as Active in production status.

Where Each One Wins

The Intel Data Center GPU Max 1350 wins decisively in raw compute throughput. Its FP32 performance of 44.44 TFLOPS is more than 4.6 times the NVIDIA part's 9.609 TFLOPS. Texture rate follows the same pattern, with the Intel part delivering 1,388.8 GTexel/s against 300.3 GTexel/s for the NVIDIA part. Memory bandwidth of 2.46 TB/s versus 273.2 GB/s gives the Intel part a massive advantage in data movement.

The NVIDIA N1 16SM wins in integration and efficiency metrics. Its 5 nm process node is more advanced than Intel's 10 nm node, and its 382 mm² die is less than a third the size of the Intel 1280 mm² package. The NVIDIA part provides 128 GB of memory, 32 GB more than the Intel part, which could matter for workloads requiring large in-memory datasets that do not need extreme bandwidth.

The NVIDIA part also offers features the Intel part lacks. It has 64 tensor cores, which are not listed for the Intel accelerator. It includes 24 ROPs and delivers 56.30 GPixel/s pixel throughput, while the Intel part has zero ROPs and 0 MPixel/s pixel rate. The NVIDIA part includes a display output, making it capable of driving a display, while the Intel part has no outputs.

The NVIDIA part's higher boost clock of 2346 MHz versus 1550 MHz indicates better single-thread or lightly-threaded performance scaling, though its core count is far lower. The Intel part's base clock of 750 MHz versus 741 MHz is nearly identical, so the difference lies entirely in boost behavior.

FAQ

Q: Which device has higher raw FP32 compute performance?

A: The Intel Data Center GPU Max 1350 delivers 44.44 TFLOPS FP32, while the NVIDIA N1 16SM delivers 9.609 TFLOPS. The Intel part is approximately 4.6 times faster in FP32 throughput.

Q: How do the memory configurations compare?

A: The Intel part uses 96 GB of HBM2e on an 8192-bit bus with 2.46 TB/s bandwidth. The NVIDIA part uses 128 GB of LPDDR5X on a 256-bit bus with 273.2 GB/s bandwidth. The Intel part has far higher bandwidth, while the NVIDIA part has more capacity.

Q: What process nodes and foundries are used?

A: The Intel part is fabricated on a 10 nm process at Intel's foundry. The NVIDIA part is fabricated on a 5 nm process at TSMC, which is a more advanced manufacturing node.

Q: Does the NVIDIA N1 16SM have tensor cores?

A: Yes, the NVIDIA part includes 64 tensor cores. The Intel Data Center GPU Max 1350 does not list tensor cores in its specifications.

Q: Can either device output to a display?

A: The NVIDIA N1 16SM includes 1x HDMI output. The Intel Data Center GPU Max 1350 has no display outputs and is a compute-only OAM module.

Q: What are the release dates?

A: The Intel part was released on 2023-01-09. The NVIDIA part is dated 2026-05-31, over three years later.

Head-to-Head Benchmarks

The database contains no recorded benchmark scores for either device, so the comparison rests entirely on specification-derived capabilities. The largest differential appears in memory bandwidth, where the Intel part delivers 2.46 TB/s against 273.2 GB/s for the NVIDIA part. This is a 9-fold advantage for the Intel accelerator, a decisive factor in any memory-bound workload such as large matrix operations or data streaming.

FP32 compute shows the next largest gap. The Intel part produces 44.44 TFLOPS versus 9.609 TFLOPS for the NVIDIA part, a ratio of 4.6 to 1. The Intel part's 14,336 shading units dwarf the NVIDIA part's 2,048, and its 896 TMUs compare to 128. Texture rate follows proportionally: 1,388.8 GTexel/s versus 300.3 GTexel/s, a 4.6 to 1 ratio consistent with the core counts.

The NVIDIA part wins the pixel throughput comparison. Its 56.30 GPixel/s stands against 0 MPixel/s for the Intel part, which has no ROPs. This makes the NVIDIA part the only viable option for rasterization tasks, though the Intel part's DirectX 12 (12_1) support suggests it could theoretically handle compute-oriented graphics workloads without pixel output.

Clock speed favors the NVIDIA part in boost conditions. The NVIDIA part reaches 2346 MHz, which is 51% higher than the Intel part's 1550 MHz boost. The base clocks are nearly identical at 741 MHz versus 750 MHz. The NVIDIA part's higher boost clock, combined with its smaller core array, suggests it can scale single-threaded or lightly-parallel workloads more effectively, though the Intel part's massive parallel array overwhelms this advantage in full utilization.

Die size and process node favor the NVIDIA part in manufacturing efficiency. The NVIDIA die at 382 mm² is 30% of the Intel die's 1280 mm². The NVIDIA part uses a 5 nm TSMC process versus Intel's 10 nm node. Transistor density for the Intel part is 78.1M per mm², while the NVIDIA density is not recorded, but the smaller die with a more advanced process implies tighter packing.

Memory capacity favors the NVIDIA part by 32 GB, offering 128 GB against 96 GB. However, the memory type differences are stark: HBM2e on the Intel part versus LPDDR5X on the NVIDIA part. The bus width difference of 8192 bits versus 256 bits explains the bandwidth gap. The NVIDIA part's memory clock of 1067 MHz with 8.5 Gbps effective compares to 1200 MHz with 2.4 Gbps effective for the Intel part, but the bus width difference completely dominates the bandwidth calculation.

Power characteristics are only partially recorded. The Intel part lists a 450 W TDP with a suggested 850 W power supply. The NVIDIA part has no recorded TDP and no power supply recommendation, consistent with its IGP classification. The Intel part is an OAM module, while the NVIDIA part is integrated directly into a processor package.

Both devices occupy the 50th percentile against all GPUs in the database, with average benchmark scores of zero. The nearest rival lists are empty for both, meaning no direct comparison points exist in the recorded data. The production status for both is Active.

The release date gap matters for platform context. The Intel part launched in January 2023, while the NVIDIA part is dated May 2026. The Intel part has a successor listed, the H3C Graphics, while the NVIDIA part has none. This suggests the Intel accelerator is further along in its lifecycle, while the NVIDIA IGP is a newer, active design.

The architectural split is clear: the Intel Data Center GPU Max 1350 is a discrete, high-bandwidth, high-throughput accelerator for data center compute. The NVIDIA N1 16SM is a compact, integrated processor with display output, tensor cores, and large memory capacity, built on a more advanced process. The data confirms each device targets a distinct workload profile, and neither substitutes for the other.