How much VRAM does the Intel Arc 140V (32GB) have?

The Intel Arc 140V (32GB) has 32 GB of LPDDR5X with 137 GB/s memory bandwidth (unified system memory, shared between CPU and GPU).

What is the Intel Arc 140V (32GB) best for?

With 32 GB of VRAM, the Intel Arc 140V (32GB) is well-suited for running 7B–32B models at Q4 with room for context, making it a great all-rounder for local LLM inference.

What LLMs can the Intel Arc 140V (32GB) run locally?

The Intel Arc 140V (32GB) can run 43 of the 70 open-weight models tracked by CanItRun natively in VRAM at 8k context. Top options include: Llama 3.1 8B Instruct at BF16, Llama 3.2 3B Instruct at FP32, Llama 3.2 1B Instruct at FP32.

Can the Intel Arc 140V (32GB) run Llama 3.3 70B Instruct?

The Intel Arc 140V (32GB) does not have enough VRAM to run Llama 3.3 70B Instruct. You would need more VRAM or a lower quantization level.

Can the Intel Arc 140V (32GB) run Qwen 3.6 27B?

Yes. The Intel Arc 140V (32GB) runs Qwen 3.6 27B natively in VRAM at Q6_K quantization, achieving approximately 6.2 tokens per second.

Can the Intel Arc 140V (32GB) run Llama 3.1 8B Instruct?

Yes. The Intel Arc 140V (32GB) runs Llama 3.1 8B Instruct natively in VRAM at BF16 quantization, achieving approximately 8.6 tokens per second.

Intel Arc 140V (32GB)

The Intel Arc 140V (32GB) has 32 GB VRAM and 137 GB/s memory bandwidth. It can run 43 of our 70 tracked models natively in VRAM at 8k context.

The Intel Arc 140V is the flagship Lunar Lake integrated GPU, built on the Xe2 (Battlemage) architecture and sharing 32GB of on-package LPDDR5X with the Core Ultra 200V CPU. At 137 GB/s it's bandwidth-constrained compared to discrete cards, but the 32GB unified pool lets it load 13B models at Q8 or 30B models at Q4 — making it one of the most capable laptop iGPUs for local LLM inference.

Intel Arc 140V (32GB): 2024 Xe2-LPG Battlemage iGPU with 32GB unified LPDDR5X at 137 GB/s — top Lunar Lake AI laptop iGPU.

13B at Q8 or 30B at Q4 in unified memory. ~3-6 t/s for 7B via Vulkan; bandwidth-constrained.

Vulkan via llama.cpp works; shares on-package memory with CPU. SYCL backend available with oneAPI. Ollama support limited.

Vendor	Intel
Architecture	Xe2-LPG (Battlemage)
VRAM	32 GB (unified)
Memory type	LPDDR5X
Memory bandwidth	137 GB/s
Compute backend	VULKAN
Tier	Integrated
Released	2024
Models (native)	43 / 70
Models (offload)	0 / 70

Software: Vulkan backend works in llama.cpp. Shares on-package unified memory with the CPU. Ollama support is limited; SYCL backend available with oneAPI.

Models this GPU runs natively in VRAM (43)

Too large for this GPU (27)

Frequently asked questions

How much VRAM does the Intel Arc 140V (32GB) have?: The Intel Arc 140V (32GB) has 32 GB of LPDDR5X with 137 GB/s memory bandwidth (unified system memory, shared between CPU and GPU).
What is the Intel Arc 140V (32GB) best for?: With 32 GB of VRAM, the Intel Arc 140V (32GB) is well-suited for running 7B–32B models at Q4 with room for context, making it a great all-rounder for local LLM inference.
What LLMs can the Intel Arc 140V (32GB) run locally?: The Intel Arc 140V (32GB) can run 43 of the 70 open-weight models tracked by CanItRun natively in VRAM at 8k context. Top options include: Llama 3.1 8B Instruct at BF16, Llama 3.2 3B Instruct at FP32, Llama 3.2 1B Instruct at FP32.
Can the Intel Arc 140V (32GB) run Llama 3.3 70B Instruct?: The Intel Arc 140V (32GB) does not have enough VRAM to run Llama 3.3 70B Instruct. You would need more VRAM or a lower quantization level.
Can the Intel Arc 140V (32GB) run Qwen 3.6 27B?: Yes. The Intel Arc 140V (32GB) runs Qwen 3.6 27B natively in VRAM at Q6_K quantization, achieving approximately 6.2 tokens per second.
Can the Intel Arc 140V (32GB) run Llama 3.1 8B Instruct?: Yes. The Intel Arc 140V (32GB) runs Llama 3.1 8B Instruct natively in VRAM at BF16 quantization, achieving approximately 8.6 tokens per second.