Intel Iris Xe Graphics 80EU Mobile vs NVIDIA H20 NVL16 Comparison

Where Each One Wins

The data presents two fundamentally different graphics products with no direct head-to-head benchmark results recorded. The Intel Iris Xe Graphics 80EU Mobile and the NVIDIA H20 NVL16 occupy distinct market positions, and their respective strengths emerge from entirely separate performance domains.

The Intel part is an integrated GPU designed for portable devices. Its entire feature set revolves around mobility and system integration. The recorded data shows a 15 W power envelope, an IGP slot width, and display outputs described as portable device dependent. This product wins in scenarios where power efficiency and system integration are the primary considerations. Its benchmark percentile sits at 50, placing it in the middle of the database's GPU distribution.

The NVIDIA H20 NVL16 is a server-class accelerator. The data records a 400 W power envelope, an SXM Module slot width, and no display outputs whatsoever. This is a compute-oriented product with no video output capability. Its wins are in raw computational throughput, memory capacity, and server deployment scenarios. Its percentile also sits at 50, but the absolute performance levels between the two products differ by orders of magnitude.

The use-case split is stark. The Intel Iris Xe serves the mobile integrated graphics segment, where the system shares memory and the GPU must operate within tight thermal constraints. The NVIDIA H20 NVL16 serves data center acceleration workloads, where power consumption and physical size are secondary to raw compute capability.

Neither product wins across the board against the other, because they were never designed to compete. The Intel part wins on integration and portability; the NVIDIA part wins on sheer throughput and memory resources.

Architecture Differences

The architectural divide between these two products is substantial. Intel builds the Iris Xe on a 10 nm process at Intel's own foundry, using the Generation 12.2 architecture. The chip is designated Raptor Lake, and the generation field lists it as HD Graphics-M. The NVIDIA part uses a 5 nm process at TSMC, based on the Hopper architecture, with the GH100 chip. The foundry difference alone indicates separate manufacturing ecosystems.

The transistor counts reveal the scale gap. The NVIDIA GH100 packs 80,000 million transistors on an 814 mm² die, with a transistor density of 98.3M per mm². The Intel part has no transistor count or die size recorded, but its integrated nature and 10 nm process imply a far smaller footprint. The NVIDIA chip is a monolithic giant designed for maximum compute density.

Clock behavior differs fundamentally. The Intel GPU runs a 300 MHz base clock with a 1450 MHz boost. The NVIDIA part operates at 1830 MHz base and 1980 MHz boost, with memory clocked at 1313 MHz or 5.3 Gbps effective. The NVIDIA chip runs at higher clocks despite having vastly more transistors, a consequence of its server-oriented power budget.

Memory architecture presents the clearest functional divergence. The Intel Iris Xe uses system shared memory with a system dependent bandwidth and a ring bus interface. The NVIDIA H20 NVL16 carries 96 GB of HBM3 on a 6144 bit bus, delivering 4.03 TB/s of bandwidth. One product borrows from the host system; the other brings its own dedicated high-speed memory pool.

Compute resources scale accordingly. The Intel part has 640 shading units, 40 TMUs, and 20 ROPs. The NVIDIA part has 9984 shading units, 312 TMUs, and 24 ROPs. The NVIDIA chip also includes 312 tensor cores, while the Intel part has none recorded. The tensor core presence signals AI and deep learning capability that the Intel integrated GPU simply cannot match.

The API support also diverges. Intel offers DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. The NVIDIA part reports N/A for DirectX, OpenGL, and Vulkan, reinforcing its compute-only orientation.

Head-to-Head Benchmarks

The recorded database contains no direct head-to-head benchmark results between these two products. The winsA and winsB fields both show zero. The headToHeadBenchmarks array is empty. This absence of comparative data is itself informative: the database does not treat these as competing products.

However, the specification data allows for quantitative comparison of theoretical peak performance. The Intel Iris Xe delivers 1.856 TFLOPS of FP32 compute and 3.712 TFLOPS of FP16 (2:1 ratio). The NVIDIA H20 NVL16 delivers 39.54 TFLOPS of FP32 and 79.07 TFLOPS of FP16. The NVIDIA part offers roughly 21 times the FP32 throughput and roughly 21 times the FP16 throughput. These ratios come directly from the recorded figures: 39.54 divided by 1.856 equals approximately 21.3, and 79.07 divided by 3.712 equals approximately 21.3.

Pixel and texture rates show a similar disparity. The Intel part achieves 29.00 GPixel/s and 58.00 GTexel/s. The NVIDIA part achieves 47.52 GPixel/s and 617.8 GTexel/s. The texture rate gap is particularly pronounced, with the NVIDIA part offering more than ten times the texel throughput.

Memory bandwidth presents the largest relative difference. The Intel part's bandwidth is system dependent, meaning it varies with the host platform. The NVIDIA part delivers a fixed 4.03 TB/s. For a system with modest shared memory bandwidth, the NVIDIA accelerator could hold a several hundredfold advantage in memory throughput.

The absence of benchmark scores and nearest rivals in the database means percentile comparisons remain flat. Both products sit at the 50th percentile, but this reflects the database's lack of comparative data for these specific items rather than any meaningful performance equivalence.

FAQ

Q: Does the NVIDIA H20 NVL16 support display output?

A: No. The recorded data lists display outputs as "No outputs" for the NVIDIA part. The Intel Iris Xe, by contrast, lists display outputs as portable device dependent.

Q: Which product has tensor cores?

A: Only the NVIDIA H20 NVL16 has tensor cores, with 312 recorded. The Intel Iris Xe lists no tensor cores at all.

Q: How much memory does each product use?

A: The Intel Iris Xe uses system shared memory with system dependent bandwidth. The NVIDIA H20 NVL16 carries 96 GB of HBM3 memory on a 6144 bit bus with 4.03 TB/s bandwidth.

Q: What is the power consumption difference?

A: The Intel Iris Xe is rated at 15 W. The NVIDIA H20 NVL16 is rated at 400 W, with a suggested PSU of 800 W.

Q: Do these products share the same API support?

A: No. Intel supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. NVIDIA reports N/A for DirectX, OpenGL, and Vulkan.

Q: Which product was released more recently?

A: The Intel Iris Xe carries a release date of 2023-01-03. The NVIDIA H20 NVL16 carries a release date of 2025-09-01.

Specification Differences

The two products differ across nearly every recorded specification field.

Manufacturer and architecture: Intel versus NVIDIA. The Intel part uses Generation 12.2 architecture on a Raptor Lake chip. The NVIDIA part uses Hopper architecture on a GH100 chip.

Process node and foundry: Intel fabricates at 10 nm in its own foundry. NVIDIA fabricates at 5 nm at TSMC. The NVIDIA chip contains 80,000 million transistors on an 814 mm² die with 98.3M transistors per mm²; no transistor data is recorded for Intel.

Clocks: Intel runs 300 MHz base and 1450 MHz boost. NVIDIA runs 1830 MHz base and 1980 MHz boost, with memory at 1313 MHz or 5.3 Gbps effective.

Memory: Intel uses system shared memory, type, bus width, and bandwidth all system dependent. NVIDIA uses 96 GB of HBM3 on a 6144 bit bus with 4.03 TB/s bandwidth.

Compute units: Intel has 640 shading units, 40 TMUs, and 20 ROPs. NVIDIA has 9984 shading units, 312 TMUs, and 24 ROPs, plus 312 tensor cores.

Rates: Intel delivers 29.00 GPixel/s, 58.00 GTexel/s, 1.856 TFLOPS FP32, and 3.712 TFLOPS FP16. NVIDIA delivers 47.52 GPixel/s, 617.8 GTexel/s, 39.54 TFLOPS FP32, and 79.07 TFLOPS FP16.

Power and form factor: Intel runs at 15 W with an IGP slot width. NVIDIA runs at 400 W with an SXM Module slot width and an 800 W suggested PSU.

Bus interface: Intel uses Ring Bus. NVIDIA uses PCIe 5.0 x16.

Display outputs: Intel lists portable device dependent. NVIDIA lists no outputs.

APIs: Intel supports DirectX 12 (12_1), OpenGL 4.6, and Vulkan 1.4. NVIDIA lists N/A for all three.

Release dates: Intel released 2023-01-03. NVIDIA released 2025-09-01. The Intel successor is Arc Graphics-M; the NVIDIA predecessor is Server Ada and successor is Server Blackwell.

Production status: Both are listed as Active.

The Verdict

The data supports a straightforward selection criterion based on deployment environment. For portable devices requiring integrated graphics with modest power draw, the Intel Iris Xe Graphics 80EU Mobile is the appropriate choice. Its 15 W envelope, system shared memory, and portable device dependent display outputs align with laptop and compact form factor requirements. The 640 shading units and 1.856 TFLOPS FP32 throughput provide basic graphics capability within a constrained power budget.

For server deployments requiring maximum compute throughput and memory capacity, the NVIDIA H20 NVL16 is the appropriate choice. Its 9984 shading units, 312 tensor cores, 96 GB of HBM3, and 4.03 TB/s bandwidth position it for data center acceleration workloads. The 400 W power envelope and SXM Module form factor assume a server environment with appropriate power delivery and cooling. The absence of display outputs confirms its compute-only role.

The FP32 throughput comparison alone settles the raw performance question. The NVIDIA part delivers 39.54 TFLOPS versus the Intel part's 1.856 TFLOPS, a roughly 21-fold advantage. Memory bandwidth shows an even larger gap when the Intel part operates on a modest system shared memory configuration.

The selection hinges on workload and platform. A mobile device with integrated graphics needs the Intel part. A server node with dedicated accelerator slots needs the NVIDIA part. The two products do not compete for the same sockets, power budgets, or use cases. The database records no direct benchmark comparisons because none exist in practice. Each product wins in its own domain, and the specifications confirm that neither could substitute for the other in its respective deployment scenario.