Intel Arc A380E vs NVIDIA H800 PCIe 80 GB Comparison

FAQ

Q: What are the core architectural families of the Intel Arc A380E and the NVIDIA H800 PCIe 80 GB?

A: The Intel Arc A380E uses the Xe-HPG architecture with the DG2-128 chip, belonging to the Alchemist (Arc 3) generation. The NVIDIA H800 PCIe 80 GB uses the Hopper architecture with the GH100 chip, part of the Server Hopper (Hxx) generation.

Q: How do the transistor counts and die sizes compare between the two GPUs?

A: The Intel Arc A380E has 7,200 million transistors on a 157 mm² die, yielding a density of 45.9M per mm². The NVIDIA H800 PCIe 80 GB has 80,000 million transistors on an 814 mm² die, resulting in a density of 98.3M per mm².

Q: What are the memory specifications for each card?

A: The Intel Arc A380E features 6 GB of GDDR6 memory on a 96-bit bus with 186.0 GB/s bandwidth. The NVIDIA H800 PCIe 80 GB has 80 GB of HBM2e memory on a 5120-bit bus with 2.04 TB/s bandwidth.

Q: Which GPU has a higher FP32 compute throughput?

A: The NVIDIA H800 PCIe 80 GB delivers 51.22 TFLOPS FP32, which is substantially higher than the Intel Arc A380E's 4.096 TFLOPS. For FP16, the H800 reaches 204.9 TFLOPS (4:1 ratio), while the A380E provides 8.192 TFLOPS (2:1 ratio).

Q: What are the power requirements for each card?

A: The Intel Arc A380E has a 75 W TDP with no power connectors and a suggested PSU of 250 W. The NVIDIA H800 PCIe 80 GB has a 350 W TDP, requires a single 16-pin connector, and suggests a 750 W PSU.

Q: What display outputs do the two cards provide?

A: The Intel Arc A380E includes 4x DisplayPort 2.0 outputs. The NVIDIA H800 PCIe 80 GB has no display outputs, indicating its server-focused design.

Where Each One Wins

The recorded data shows a clear split between these two accelerators. The Intel Arc A380E wins in every metric related to graphics output and rasterization efficiency per watt. Its pixel rate of 64.00 GPixel/s exceeds the H800's 42.12 GPixel/s, despite the H800 having far more shading units. The A380E also has a higher ROP count at 32 versus 24, which directly contributes to its pixel throughput advantage.

The NVIDIA H800 PCIe 80 GB dominates in raw compute and memory bandwidth. Its FP32 throughput of 51.22 TFLOPS is roughly 12.5 times that of the A380E. The H800's texture rate of 800.3 GTexel/s dwarfs the A380E's 128.0 GTexel/s. Memory bandwidth is another decisive area: 2.04 TB/s versus 186.0 GB/s, a factor of nearly 11. The H800 also carries tensor cores (456 of them), a feature entirely absent from the A380E's specification sheet.

The interface also differs. The H800 uses PCIe 5.0 x16, while the A380E uses PCIe 4.0 x8. This gives the H800 double the lane width and a newer bus generation for host communication. For AI workloads, scientific computing, or large-scale data processing, the H800's compute and memory resources are the clear choice. For embedded graphics, edge rendering, or any task requiring direct display output, the A380E holds the advantage.

Architecture Differences

The two GPUs come from opposite ends of the design spectrum. Intel's DG2-128 chip is built on a 6 nm TSMC process and uses the Xe-HPG architecture, which is optimized for consumer graphics with support for DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4. The A380E includes 8 dedicated ray tracing cores, aligning it with modern gaming and real-time rendering workloads.

NVIDIA's GH100 chip uses a 5 nm TSMC process and the Hopper architecture, which is explicitly designed for server and data center acceleration. The H800 does not list DirectX, OpenGL, or Vulkan support, and it has no display outputs. Instead, it carries 456 tensor cores, which are critical for matrix operations in AI training and inference. The H800 also omits dedicated RT cores, suggesting its focus is not on real-time ray tracing but on parallel compute.

Transistor density tells a story of design philosophy. The A380E packs 45.9M transistors per mm², while the H800 achieves 98.3M per mm². The H800's higher density reflects the greater complexity of its compute units, memory controllers for HBM2e, and tensor core arrays. The A380E's simpler layout prioritizes power efficiency and compact size, fitting into a 254 mm length, 127 mm height, and 20 mm width single-slot form factor. The H800 is longer at 268 mm, taller at 111 mm, and dual-slot.

The memory architectures are fundamentally different. The A380E uses GDDR6 with a 96-bit bus, which is sufficient for its 6 GB capacity and 186.0 GB/s bandwidth. The H800 uses HBM2e with a 5120-bit bus, enabling 2.04 TB/s bandwidth and 80 GB capacity. This is not just a capacity difference but a structural one: HBM2e stacks memory vertically to achieve massive bandwidth, while GDDR6 relies on wider parallel traces on the PCB.

Specification Differences

The table of differences between the Intel Arc A380E and NVIDIA H800 PCIe 80 GB is extensive. The A380E has 1,024 shading units, 64 TMUs, and 32 ROPs. The H800 has 14,592 shading units, 456 TMUs, and 24 ROPs. The H800's shading unit count is over 14 times higher, and its TMU count is over 7 times higher, but its ROP count is lower.

Clock speeds diverge significantly. The A380E runs at a constant 2000 MHz for both base and boost. The H800 has a base clock of 1095 MHz and a boost clock of 1755 MHz. Memory clocks also differ: the A380E operates at 1937 MHz with 15.5 Gbps effective data rate, while the H800 runs at 1593 MHz with 3.2 Gbps effective. The H800's lower memory clock is offset by its vastly wider bus.

Power and physical requirements show the intended use cases. The A380E is rated at 75 W TDP, single-slot, with no external power connectors and a 250 W suggested PSU. The H800 is rated at 350 W TDP, dual-slot, requires one 16-pin connector, and suggests a 750 W PSU. The A380E is 254 mm long and 127 mm high, while the H800 is 268 mm long and 111 mm high. The A380E has a width of 20 mm; the H800's width is not recorded.

Production status and release timing also differ. The A380E was released on 2024-03-31 and is now end-of-life, with the successor listed as Battlemage. The H800 was released on 2023-03-20 and remains active, with Server Blackwell listed as its successor. The A380E's predecessor is Xe Graphics, while the H800's predecessor is Server Ada.

Head-to-Head Benchmarks

The direct benchmark data shows no recorded head-to-head results, and neither GPU has individual benchmark scores or nearest rivals in the database. The percentile ranking for both is 50, indicating they sit at the median of all GPUs tracked, but this does not reflect relative performance against each other.

What the recorded specifications allow is a direct comparison of theoretical peak outputs. The H800's FP32 throughput of 51.22 TFLOPS is 12.5 times the A380E's 4.096 TFLOPS. In FP16, the gap widens: 204.9 TFLOPS versus 8.192 TFLOPS, a factor of 25. The H800's tensor cores enable this FP16 advantage, as the 4:1 ratio effectively doubles the FP32 rate when using tensor operations.

Texture throughput favors the H800 decisively. Its 800.3 GTexel/s compares to 128.0 GTexel/s for the A380E, a 6.25 times difference. However, pixel rate tells a different story. The A380E achieves 64.00 GPixel/s, surpassing the H800's 42.12 GPixel/s by about 52%. This is unusual given the H800's larger chip, but it reflects the A380E's higher ROP count (32 versus 24) and its higher boost clock relative to its architecture.

Memory bandwidth is the most lopsided metric. The H800's 2.04 TB/s is 10.97 times the A380E's 186.0 GB/s. This bandwidth advantage is critical for data-heavy workloads like large language model inference or scientific simulations. The A380E's 6 GB capacity is marginal for such tasks, while the H800's 80 GB capacity allows holding entire model weights in memory.

The bus interface also differs. The H800 uses PCIe 5.0 x16, which provides more than double the bandwidth of the A380E's PCIe 4.0 x8. For applications that stream data from host memory, this difference compounds the H800's memory advantage.

The Verdict

The data indicates two products designed for fundamentally different purposes. The Intel Arc A380E is a low-power, single-slot graphics card with display outputs and a 75 W TDP. Its strengths are pixel throughput, compact dimensions, and support for modern graphics APIs. It suits embedded systems, digital signage, or any environment requiring multiple DisplayPort outputs without high compute demands.

The NVIDIA H800 PCIe 80 GB is a high-power, dual-slot server accelerator with no display outputs and a 350 W TDP. Its strengths are massive FP32 and FP16 compute, 456 tensor cores, 80 GB of HBM2e memory, and 2.04 TB/s bandwidth. It targets AI training, inference, and high-performance computing where raw throughput and memory capacity outweigh power consumption.

For any workload involving rendering to a screen, the A380E is the only viable option between the two, as the H800 has no display outputs. For any workload involving matrix multiplication, large datasets, or neural networks, the H800 provides over 12 times the FP32 performance and over 10 times the memory bandwidth.

The production statuses also inform the decision. The A380E is end-of-life, suggesting it is a mature product at the end of its support cycle. The H800 is active, indicating ongoing availability and likely continued driver and software support.

Neither card is a substitute for the other. The A380E wins on pixel rate, ROP count, power efficiency per watt, and physical footprint. The H800 wins on shading units, TMUs, tensor cores, memory size, memory bandwidth, FP32, FP16, texture rate, bus interface, and transistor density. The choice depends entirely on whether the task requires graphics output or massive parallel compute. The recorded data offers no overlap: these are complementary tools for disjoint workloads.