llama3.1-70b vs llama3.2-3b on Apple M2 Pro
Compare llama3.1-70b and llama3.2-3b running locally on Apple M2 Pro (16GB unified) — tokens/sec, VRAM fit, and quality scores for local inference.
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Which is faster on Apple M2 Pro: llama3.1-70b or llama3.2-3b?
This Apple M2 Pro comparison shows VRAM fit and quality data for llama3.1-70b vs llama3.2-3b, but one or both decode-speed benchmarks are still missing.
Do both models fit on Apple M2 Pro?
llama3.1-70b: ✗ No. llama3.2-3b: ✓. The fit labels use Q4_K_M VRAM estimates and the benchmark data available for this GPU.
How much VRAM do these models need?
llama3.1-70b needs about 42GB in Q4_K_M; llama3.2-3b needs about 2GB in Q4_K_M.
Why can speed differ by GPU?
Local LLM speed depends on GPU memory bandwidth, backend, quantization, context length, and whether the model fits entirely in VRAM or unified memory.
How can I correct this comparison?
Use the GitHub correction link on this page with your GPU, model, quantization, context length, and measured decode tokens per second.