gpubudget-llmimage-gen

Arc A730M

Updated Jun 8, 2026
VRAM
12 GB
Bandwidth
336 GB/s
TDP
80 W
MSRP
-
Category
gpu

Arc A730M

The Arc A730M is an Intel GPU built on the Xe-HPG architecture, released 2022-01-01. For running AI locally, the numbers that matter are its 12 GB of GDDR6 and 336 GB/s of memory bandwidth. VRAM decides which models fit at all; bandwidth sets how fast they generate text.

What you can run on 12 GB

At Q4_K_M quantization (the usual local default), 12 GB holds models up to roughly 19B parameters, leaving headroom for context. On this card you can run, among others:

Larger models need a higher-VRAM card, a second GPU, or CPU offload (which is much slower). Check any specific model with the VRAM calculator, or see the full picture on what can I run.

Local LLM speed (LLaMA 3, llama.cpp)

Single-stream token-generation throughput - estimated from memory bandwidth:

Model (quant)Speed on Arc A730M
Llama 3 8B (Q4_K_M)39.3 tok/s
Llama 3 8B (F16)✗ won't fit
Llama 3 70B (Q4_K_M)✗ won't fit

Because decode is memory-bandwidth bound, the 336 GB/s figure is the best single predictor of chat speed on this card. Estimates are calibrated against measured RTX-40-series cards and are typically within ~15%.

Memory and power

  • VRAM: 12 GB GDDR6 (192-bit bus)
  • Bandwidth: 336 GB/s
  • TDP: 80 W
  • Process: 6 nm
  • Interface: PCIe 4.0 x16

Quantization and context

Quantization trades a little quality for a lot of VRAM. On 12 GB you can fit roughly a 19B model at Q4_K_M, about a 10B model at the higher-quality Q8, or a smaller model at full FP16. Longer context windows also consume VRAM (the KV cache grows with context length), so leave a few GB of headroom if you plan to use large prompts or many concurrent requests. For most chat and coding use, Q4_K_M on this card is the sweet spot between speed, quality, and the 12 GB budget.

How it compares

Similar cards for local AI, by VRAM and 8B-Q4 speed:

GPUVRAMBandwidthLlama 3 8B Q4
Arc A730M12 GB336 GB/s39.3 tok/s
AMD Radeon RX 7700 XT12 GB432 GB/s50.6 tok/s
Arc Pro A6012 GB384 GB/s44.9 tok/s
Intel Arc B58012 GB456 GB/s53.4 tok/s

Bottom line

The Arc A730M is best for budget-llm, image-gen. 12 GB is the practical entry point for serious local LLMs (7B-13B at Q4). If you need more, compare with AMD Radeon RX 7700 XT and Arc Pro A60.

Sources

Specs and benchmarks last checked 2026-06-08. Verify current pricing before buying.

Frequently asked

Quick answers to common questions

How much VRAM does the Arc A730M have?

The Arc A730M has 12 GB of VRAM with 336 GB/s memory bandwidth.

What local AI models can run on the Arc A730M?

The Arc A730M with 12 GB VRAM can run many models depending on quantization. Models up to ~18B params may fit at Q4_K_M. Use our VRAM calculator to check specific models.

Is the Arc A730M good for local AI inference?

Arc A730M is best for budget-llm, image-gen. Check our hardware directory for alternatives with more VRAM.

Where can I buy the Arc A730M?

Check our buy links above for the best current prices on Amazon, Newegg, and B&H. Prices vary by retailer and availability.

How does the Arc A730M compare to other GPUs?

Arc A730M has 12 GB VRAM and 336 GB/s bandwidth. It works best with smaller quantized models. Browse our hardware directory for side-by-side comparisons.

What power supply do I need for the Arc A730M?

The Arc A730M has a TDP of 80W. A standard quality PSU of 650W+ should suffice. Always check the manufacturer's recommendations for your specific build.

Nearby options

Similar hardware and models that fit

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