Intel Arc Pro B65 vs NVIDIA N1 16SM Comparison

Head-to-Head Benchmarks

The recorded database contains no head-to-head benchmark results for the Intel Arc Pro B65 and the NVIDIA N1 16SM. The head-to-head benchmark array is empty, and neither product has a wins tally assigned. This absence of comparative data means a direct performance ranking cannot be established from the measurements on file.

Both GPUs sit at the 50th percentile against all GPUs in the database, indicating that their aggregate recorded standing is identical when placed against the broader field. However, the average benchmark score for each is recorded as zero, which further confirms that no individual benchmark runs have been logged for either product. The data does not permit a statement about which part is faster, slower, or more efficient in real workloads.

The nearest rivals arrays for both products are also empty. There are no reference points within the database to anchor either GPU against a third component. Consequently, relative performance deltas, percentile comparisons, and win/loss breakdowns cannot be derived. The database simply has not yet captured the required measurements for these two parts.

What can be stated from the existing records is limited to architectural and specification differences, which are detailed in the sections below. Until benchmark data is populated, any quantitative performance comparison between the Intel Arc Pro B65 and the NVIDIA N1 16SM remains unavailable.

FAQ

Q: Which GPU has the higher FP32 compute throughput?

A: The Intel Arc Pro B65 records 12.29 TFLOPS FP32, while the NVIDIA N1 16SM records 9.609 TFLOPS FP32. The Intel part holds a numerical advantage in raw single-precision compute.

Q: How do the memory subsystems differ?

A: The Intel Arc Pro B65 uses 32 GB of GDDR6 on a 256-bit bus with 608.0 GB/s bandwidth. The NVIDIA N1 16SM uses 128 GB of LPDDR5X on a 256-bit bus with 273.2 GB/s bandwidth. The Intel card has over twice the memory bandwidth, while the NVIDIA part has four times the memory capacity.

Q: What are the respective clock speeds?

A: The Intel Arc Pro B65 runs at 2400 MHz base and 2400 MHz boost, with memory at 2375 MHz (19 Gbps effective). The NVIDIA N1 16SM runs at 741 MHz base and 2346 MHz boost, with memory at 1067 MHz (8.5 Gbps effective).

Q: Which GPU supports more display outputs?

A: The Intel Arc Pro B65 provides 4x DisplayPort 2.1 outputs. The NVIDIA N1 16SM provides a single HDMI output.

Q: What are the API support differences?

A: The Intel Arc Pro B65 supports DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The NVIDIA N1 16SM lists N/A for DirectX, OpenGL, and Vulkan, indicating no recorded API support.

Q: What is the physical form factor of each?

A: The Intel Arc Pro B65 is a dual-slot card requiring a single 8-pin power connector and a 550 W suggested PSU. The NVIDIA N1 16SM is an integrated graphics processor (IGP) with no power connectors and no suggested PSU listed.

Architecture Differences

The architectural gap between these two parts is substantial. The Intel Arc Pro B65 uses the BMG-G21 chip built on the Xe2-HPG architecture, belonging to the Battlemage (Pro Series) generation. The NVIDIA N1 16SM uses the GB20B chip built on Blackwell 2.0, part of the Blackwell IGP (N1x) generation. Both chips are fabricated on a 5 nm process at TSMC, which places them on the same manufacturing node.

The transistor counts differ markedly. The Intel chip contains 19,600 million transistors on a 272 mm² die, yielding a transistor density of 72.1M per mm². The NVIDIA chip has an unknown transistor count but a larger die size of 382 mm². The density figure for the NVIDIA part is not recorded.

The compute architectures diverge in several ways. The Intel Arc Pro B65 has 2560 shading units, 160 texture mapping units, 80 ROPs, and 20 ray tracing cores. The NVIDIA N1 16SM has 2048 shading units, 128 TMUs, 24 ROPs, and 16 ray tracing cores. NVIDIA additionally lists 64 tensor cores, while Intel does not report a tensor core count.

The FP16 throughput patterns reveal a key difference. The Intel part delivers 24.58 TFLOPS FP16, described as a 2:1 ratio relative to FP32. The NVIDIA part delivers 9.609 TFLOPS FP16, described as a 1:1 ratio. This indicates the Intel architecture uses a doubled-rate FP16 path, while the NVIDIA part processes FP16 at the same rate as FP32.

The NVIDIA N1 16SM is explicitly positioned as an integrated graphics processor. Its slot width is listed as IGP, and it uses no power connectors. The Intel part is a dual-slot discrete card with a single 8-pin connector. This form factor difference aligns with the architectural intent: the NVIDIA part appears designed for system-on-chip integration, while the Intel part is a standalone expansion card.

Specification Differences

The specification sheets show differences across nearly every measured category.

Process and Die: Both use TSMC 5 nm. The Intel die is 272 mm² with 19,600 million transistors and a density of 72.1M per mm². The NVIDIA die is 382 mm² with an unknown transistor count and no density figure.

Clocks: The Intel base clock is 2400 MHz and the boost clock is 2400 MHz, meaning it runs at a fixed frequency. The NVIDIA base clock is 741 MHz and the boost clock is 2346 MHz, a much wider range. Memory clocks differ: Intel at 2375 MHz (19 Gbps effective) versus NVIDIA at 1067 MHz (8.5 Gbps effective).

Memory: Intel uses 32 GB GDDR6 with 608.0 GB/s bandwidth. NVIDIA uses 128 GB LPDDR5X with 273.2 GB/s bandwidth. Both have a 256-bit bus width.

Compute Units: Intel has 2560 shading units, 160 TMUs, 80 ROPs, and 20 RT cores. NVIDIA has 2048 shading units, 128 TMUs, 24 ROPs, and 16 RT cores. NVIDIA has 64 tensor cores; Intel reports none.

Rates: Intel pixel rate is 192.0 GPixel/s and texture rate is 384.0 GTexel/s. NVIDIA pixel rate is 56.30 GPixel/s and texture rate is 300.3 GTexel/s.

Power and Physical: Intel TDP is 200 W with a dual-slot form factor, one 8-pin connector, and a 550 W suggested PSU. NVIDIA TDP is unknown, form factor is IGP, and no power connectors or suggested PSU are listed.

Bus and Display: Both use PCIe 5.0 x16. Intel offers 4x DisplayPort 2.1; NVIDIA offers 1x HDMI.

API Support: Intel lists DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. NVIDIA lists N/A for all three.

Release Dates: The Intel Arc Pro B65 has a release date of 2026-03-31. The NVIDIA N1 16SM has a release date of 2026-05-31. The Intel part is recorded two months earlier.

The Verdict

The recorded data does not support a performance verdict. With no benchmark scores, no wins tally, and no nearest rivals on file, any claim of superiority for either GPU would be unsupported. The database currently holds only architectural and specification records for these two parts.

What the specifications indicate is a clear design split. The Intel Arc Pro B65 is built as a high-bandwidth, high-throughput discrete graphics card. Its 608.0 GB/s memory bandwidth, 12.29 TFLOPS FP32, 2400 MHz fixed clock, and 200 W TDP position it for workloads that stress raw rendering throughput and memory speed. The 80 ROPs and 192.0 GPixel/s pixel rate suggest strong fill-rate performance, and the 2:1 FP16 ratio indicates support for accelerated half-precision workloads.

The NVIDIA N1 16SM is recorded as an integrated processor with a different set of priorities. Its 128 GB memory capacity is substantially larger, and the 1:1 FP16 ratio suggests a compute path that treats precision levels equally. The 64 tensor cores indicate a focus on tensor operations, which the Intel part does not list. The 741 MHz base clock with a 2346 MHz boost shows a variable frequency design, likely constrained by thermal and power limits typical of integrated parts.

The absence of benchmark data means the verdict must be conditional. If the database later populates head-to-head results, the analysis can be completed. Until then, the only defensible conclusion is that these are two different classes of products: one discrete add-in card, one integrated processor, each with distinct specification profiles.

Where Each One Wins

Based strictly on the recorded specifications, without benchmark confirmation, each part shows strengths in different areas.

Intel Arc Pro B65 wins on memory bandwidth and rendering throughput. The 608.0 GB/s bandwidth versus 273.2 GB/s gives it a 2.2x advantage in raw memory speed. The 192.0 GPixel/s pixel rate is 3.4x the NVIDIA part's 56.30 GPixel/s. The 384.0 GTexel/s texture rate exceeds the NVIDIA part's 300.3 GTexel/s by 28%. The 12.29 TFLOPS FP32 is 28% higher than 9.609 TFLOPS. The FP16 rate of 24.58 TFLOPS is 2.6x the NVIDIA part's 9.609 TFLOPS. The Intel part also supports DirectX 12 Ultimate, OpenGL 4.6, and Vulkan 1.4, while the NVIDIA part lists no API support.

NVIDIA N1 16SM wins on memory capacity and tensor compute. The 128 GB memory is 4x the Intel part's 32 GB. This is a decisive advantage for workloads that need large in-memory datasets. The 64 tensor cores are not present on the Intel part at all, indicating a dedicated path for tensor operations. The NVIDIA part also has a larger die at 382 mm² versus 272 mm², though the transistor count is unknown. The 2346 MHz boost clock is close to the Intel part's 2400 MHz, despite the much lower 741 MHz base clock.

Physical integration favors NVIDIA. The NVIDIA part is an IGP with no power connectors and no suggested PSU, meaning it can be integrated into a system without additional power delivery. The Intel part requires a 200 W TDP budget, a dual-slot cooler, a single 8-pin connector, and a 550 W suggested PSU. For compact or power-constrained systems, the NVIDIA part has a structural advantage.

Display connectivity favors Intel. The Intel part offers 4x DisplayPort 2.1 outputs, while the NVIDIA part offers a single HDMI output. Multi-display setups are better served by the Intel card based on the recorded outputs.

The data does not assign wins in actual benchmarks, but the specification record supports these usage-based distinctions. The Intel Arc Pro B65 appears suited for rendering, high-bandwidth tasks, and multi-display configurations. The NVIDIA N1 16SM appears suited for large-memory workloads, tensor operations, and integrated deployments.