Intel Arc A310E vs NVIDIA RTX 1000 Mobile Ada Generation Comparison

Head-to-Head Benchmarks

The database contains no recorded benchmark scores for either the Intel Arc A310E or the NVIDIA RTX 1000 Mobile Ada Generation. Both entries show an average benchmark score of zero and zero wins in head-to-head comparisons. This absence of empirical data means the performance relationship between these two parts must be derived entirely from their recorded architectural specifications and theoretical throughput figures.

What the recorded data does show is a substantial gap in raw compute capability. The RTX 1000 Mobile Ada Generation delivers 10.37 TFLOPS of FP32 performance, while the Arc A310E produces 3.072 TFLOPS. That places the NVIDIA part at roughly 3.4 times the single-precision throughput of the Intel part. The pixel throughput differential is even more pronounced: 97.20 GPixel/s against 32.00 GPixel/s, a 3.0x advantage. Texture fill rates tell a similar story, with the RTX 1000 reaching 162.0 GTexel/s compared to 64.00 GTexel/s for the Arc A310E, a 2.5x margin.

Memory bandwidth also favors the NVIDIA solution. The RTX 1000 Mobile Ada Generation accesses 192.0 GB/s across a 96-bit bus, while the Arc A310E manages 124.0 GB/s over a 64-bit interface. That is a 54.8% bandwidth advantage for the NVIDIA part, which becomes relevant for texture-heavy workloads and larger framebuffers.

The FP16 comparison is more nuanced. The Arc A310E lists 6.144 TFLOPS FP16 with a 2:1 ratio, meaning it halves its rate from FP32. The RTX 1000 Mobile Ada Generation lists 10.37 TFLOPS FP16 with a 1:1 ratio, indicating no throughput penalty for half-precision work. This gives the NVIDIA part a 1.7x lead in FP16 operations, though the Intel architecture's dedicated ratio suggests it can still accelerate FP16 workloads beyond its FP32 baseline.

Neither part has recorded wins in the head-to-head benchmark table, and both sit at the 50th percentile among all GPUs in the database. This equal percentile ranking reflects the absence of measured results rather than actual performance parity, so the specification sheet must carry the analytical weight.

Where Each One Wins

Based strictly on the recorded specifications, the NVIDIA RTX 1000 Mobile Ada Generation wins across every measurable compute category. Its FP32 throughput, FP16 throughput, texture rate, pixel rate, and memory bandwidth all exceed the Intel Arc A310E's figures. The shading unit count reinforces this: 2560 units versus 768, a 3.3x difference. Texture mapping units stand at 80 against 32, and ROPs at 48 against 16. The RT core count also favors NVIDIA at 20 versus 6, and the tensor core count of 80 gives the RTX 1000 a dedicated AI acceleration path that the Arc A310E lacks entirely, as its tensor core field is null.

The Arc A310E does hold advantages in specific non-performance areas. Its process node is listed as 6 nm versus 5 nm for the NVIDIA part, though both are fabricated by TSMC. The Intel chip packs 7,200 million transistors on a 157 mm² die, while the NVIDIA chip uses 18,900 million transistors on a 159 mm² die. The transistor density difference is stark: 118.9M per mm² for the RTX 1000 against 45.9M per mm² for the Arc A310E, indicating the NVIDIA design integrates far more logic per unit area.

Power consumption favors the Intel card in one sense: the Arc A310E carries a 75 W TDP, while the RTX 1000 Mobile Ada Generation lists a 35 W TDP. The lower power target for the NVIDIA mobile part means it delivers substantially higher throughput per watt, based on the TFLOPS-to-TDP ratio. The Arc A310E's suggested PSU of 250 W also implies a desktop-oriented installation, while the RTX 1000's IGP slot width and "Portable Device Dependent" display outputs confirm a laptop or mobile workstation target.

Display connectivity is a clear win for the Intel card, which provides 4x mini-DisplayPort 2.0 outputs. The NVIDIA mobile part lists "Portable Device Dependent" outputs, meaning its display configuration varies by the host laptop design. For fixed desktop or embedded use with multiple monitors, the Arc A310E offers a more defined output arrangement.

Architecture Differences

The two GPUs come from fundamentally different design philosophies. Intel's Arc A310E uses the DG2-128 chip built on the Xe-HPG architecture, belonging to the Alchemist (Arc 3) generation. NVIDIA's RTX 1000 Mobile Ada Generation uses the AD107 chip on the Ada Lovelace architecture, part of the Ada-MW (x000A) generation. Both support DirectX 12 Ultimate (12_2), OpenGL 4.6, and Vulkan 1.4, so API compatibility is identical on paper.

The memory subsystems differ in capacity and width. The Arc A310E ships with 4 GB of GDDR6 on a 64-bit bus, while the RTX 1000 Mobile Ada Generation ships with 6 GB of GDDR6 on a 96-bit bus. The NVIDIA part's memory clock runs at 2000 MHz with 16 Gbps effective speed, versus 1937 MHz with 15.5 Gbps effective for the Intel part. The combination of wider bus and higher effective speed produces the bandwidth gap already noted.

Clock behavior distinguishes the two designs. The Arc A310E runs at a flat 2000 MHz for both base and boost, indicating a fixed clock profile with no dynamic range. The RTX 1000 Mobile Ada Generation has a 1485 MHz base and 2025 MHz boost, providing a 540 MHz uplift window for thermal and power headroom management. This suggests the NVIDIA part can scale its clocks based on workload and cooling, while the Intel part stays pinned.

The RTX 1000 Mobile Ada Generation integrates 80 tensor cores, a feature class absent from the Arc A310E's specification sheet. This enables hardware-accelerated deep learning inference and training workloads, plus AI-enhanced rendering features. The Arc A310E's 6 RT cores handle ray tracing, but with no tensor hardware, its AI-related capabilities remain undefined in the recorded data.

NVIDIA's transistor count of 18,900 million on a 159 mm² die yields a density of 118.9M per mm², achieved on TSMC's 5 nm process. Intel's 7,200 million transistors on a 157 mm² die at 45.9M per mm² uses TSMC's 6 nm process. The smaller process node plus higher transistor density gives the NVIDIA chip a structural advantage in logic complexity per square millimeter, which aligns with its higher shading unit and RT core counts.

The bus interface is identical: PCIe 4.0 x8 for both. Neither part uses external power connectors, though the Arc A310E lists a 250 W suggested PSU. The Intel card is a single-slot, 168 mm long, 69 mm high, and 20 mm wide add-in board. The NVIDIA mobile part has no listed dimensions, consistent with an integrated or MXM-style mobile form factor.

FAQ

Q: Which GPU has higher FP32 compute throughput?

A: The NVIDIA RTX 1000 Mobile Ada Generation delivers 10.37 TFLOPS of FP32 performance, compared to 3.072 TFLOPS for the Intel Arc A310E, a 3.4x advantage.

Q: How do the memory capacities compare?

A: The RTX 1000 Mobile Ada Generation has 6 GB of GDDR6 on a 96-bit bus with 192.0 GB/s bandwidth. The Arc A310E has 4 GB of GDDR6 on a 64-bit bus with 124.0 GB/s bandwidth.

Q: Does either GPU support hardware ray tracing?

A: Both support DirectX 12 Ultimate (12_2), which includes ray tracing requirements. The Arc A310E has 6 RT cores, while the RTX 1000 Mobile Ada Generation has 20 RT cores.

Q: What is the power consumption difference?

A: The Intel Arc A310E lists a 75 W TDP, while the NVIDIA RTX 1000 Mobile Ada Generation lists a 35 W TDP. The NVIDIA part achieves higher compute throughput at lower power.

Q: Are there tensor cores on either GPU?

A: The RTX 1000 Mobile Ada Generation includes 80 tensor cores. The Arc A310E's specification sheet has no tensor core entry, indicating this feature is not present.

Q: Which GPU has a larger transistor count?

A: The NVIDIA RTX 1000 Mobile Ada Generation contains 18,900 million transistors on a 159 mm² die. The Intel Arc A310E contains 7,200 million transistors on a 157 mm² die.

The Verdict

The recorded data points to a clear performance hierarchy. The NVIDIA RTX 1000 Mobile Ada Generation outclasses the Intel Arc A310E in every compute metric: FP32 throughput (10.37 vs 3.072 TFLOPS), FP16 throughput (10.37 vs 6.144 TFLOPS), pixel rate (97.20 vs 32.00 GPixel/s), texture rate (162.0 vs 64.00 GTexel/s), memory bandwidth (192.0 vs 124.0 GB/s), shading units (2560 vs 768), TMUs (80 vs 32), ROPs (48 vs 16), and RT cores (20 vs 6). It also carries 80 tensor cores, a feature the Intel part lacks entirely.

The RTX 1000 Mobile Ada Generation achieves this with a 35 W TDP, less than half the Arc A310E's 75 W TDP. Its higher transistor density on a 5 nm process versus 6 nm, combined with a boost clock of 2025 MHz against a flat 2000 MHz, explains the efficiency gap. The NVIDIA part also offers 6 GB of memory versus 4 GB, which matters for larger datasets and higher-resolution textures.

The Intel Arc A310E retains value in specific contexts. Its 4x mini-DisplayPort 2.0 outputs provide a fixed, multi-monitor desktop configuration that the NVIDIA mobile part cannot guarantee, given its "Portable Device Dependent" display outputs. The Arc A310E is an end-of-life product with a successor listed as Battlemage, while the RTX 1000 Mobile Ada Generation remains active with a Blackwell-MW successor. The Intel card's 168 mm length and single-slot profile make it suitable for compact desktop builds, though its 250 W suggested PSU indicates system-level power planning is required.

For workloads that demand raw compute, ray tracing, AI acceleration, or memory capacity, the RTX 1000 Mobile Ada Generation is the superior choice based on all recorded specifications. For applications requiring a defined multi-display output arrangement in a desktop form factor, the Arc A310E offers a clearer hardware configuration. The database shows no benchmark results to contradict these specification-based conclusions, so the NVIDIA part stands as the higher-performing GPU in every measured category.