Intel Arc A750, AI & Machine Learning Benchmarks & Specs

8GB · AI Score 1.5/100 · anchored estimate vs 51 measured cards

1.5 AI Score Includes estimates

We have not run Intel Arc A750 on our bench. These figures are anchored estimates, interpolated per workload against the 51 GPUs we did measure (confidence: low). On Llama 3.1 8B (Q4_K_M) Intel Arc A750 should deliver about 37 tokens/sec. Llama 3.3 70B does not fit. It needs roughly 42GB and this card has 8GB. 3 of the 12 workloads won't fit on 8GB at the tested precision, Qwen2.5-Coder 14B, Qwen3 32B, Llama 3.3 70B. We publish those as hard gates rather than quietly dropping to a smaller quant. Image, video and 3D models aren't listed for this card. They're built for NVIDIA's CUDA, and on Intel Arc they only run through PyTorch XPU workarounds whose speed depends more on the driver and OS than on the card, so we don't estimate them, and they count as not supported in the AI score. For text generation (llama.cpp runs natively on SYCL and Vulkan), the numbers above hold up.

AI & Machine Learning benchmark results

Text Generation tok/s 9

WorkloadResultTelemetryData
Qwen3 4B59.5 tok/sestimatedEst.
Llama 3.1 8B37 tok/sestimatedEst.
Qwen2.5-Coder 14B✕ Won't fit VRAM-gated at this precisionEst.
Qwen3 14B✕ Won't fit needs ~11 GBVRAM-gated at this precisionEst.
Gemma 4 26B A4B✕ Won't fit needs ~20 GBVRAM-gated at this precisionEst.
Qwen3 30B A3B✕ Won't fit needs ~20 GBVRAM-gated at this precisionEst.
Gemma 4 31B✕ Won't fit needs ~22 GBVRAM-gated at this precisionEst.
Qwen3 32B✕ Won't fit VRAM-gated at this precisionEst.
Llama 3.3 70B✕ Won't fit VRAM-gated at this precisionEst.
How this estimate is derived. This card hasn’t been through our bench yet, so its numbers are anchored estimates, interpolated from the 51 first-party measured cards (Bandwidth Theil-Sen ladder off NVIDIA anchors × vendor factor (LLM ×0.5, diffusion ×0.35); measured VRAM floors; recalibrated 2026-09-19 against published llama.cpp (CUDA/ROCm/Vulkan/SYCL) and Stable Diffusion results.). The VRAM “won’t fit” gates are exact, since they’re pure capacity limits. Confidence: low. Estimates are replaced with measured data as more silicon goes through the bench. Full methodology →

Intel Arc A750 specifications

ArchitectureAlchemist (Xe-HPG)
Xe cores32
VRAM8GB GDDR6
Memory bus256-bit
Memory bandwidth512 GB/s
Boost clock2,400 MHz
TDP225 W
Process6nm
InterfacePCIe 4.0 x16
Release date2022-10-19
Launch MSRP$289

Verdict, capable, but 8GB sets the ceiling

Intel Arc A750 scores 1.5/100, #100 of 102. It ran 2 of 12; 3 exceeded its 8GB. Figures are anchored estimates, not measurements, we flag that on every row.

Relative performance: where the Intel Arc A750 lands

100% = this card, AI & Machine Learning headline metric (AI Score). #60 of 61 desktop cards in this vertical.

GPURelative%AI Score
AMD Radeon RX 7600
107%1.6
NVIDIA GeForce GTX 1660 Super
107%1.6
NVIDIA GeForce GTX 1660 Ti
107%1.6
NVIDIA GeForce GTX 1660
100%1.5
Intel Arc A750
100%1.5
NVIDIA GeForce RTX 2060
87%1.3

Same card, other workloads: Intel Arc A750 Gaming benchmarks

← All AI & Machine Learning GPU rankings

The silicon

Transistors21,700 million
Die size406 mm²
Process node6 nm
Fabricated byTSMC
Transistor density53.4 million per mm²

Denser than 86% of the 746 cards we have silicon data for. Density is the clearest measure of what a process node bought: a card that gained it without growing the die got its speed from the fab rather than the architecture.

Silicon figures from Wikipedia (CC BY-SA 4.0). Benchmarks on this page are our own. Compare every chip.

What this card can build

Whole-job timings, composed from our measured per-model results on this card.

Can't run: Short social clips (needs Qwen3 32B), 60-second AI short film (needs Qwen3 32B), 24-frame storyboard (needs Qwen3 32B), 6-panel comic page (needs Qwen3 32B), Long-form article batch (needs Llama 3.3 70B), Full codebase review (needs Qwen2.5-Coder 14B).