L
localai.computer
ModelsGPUsSystemsAI SetupsBuildsOpenClawMethodology

Resources

  • Methodology
  • Submit Benchmark
  • About

Browse

  • AI Models
  • GPUs
  • PC Builds

Guides

  • OpenClaw Guide
  • How-To Guides

Legal

  • Privacy
  • Terms
  • Contact

© 2025 localai.computer. Hardware recommendations for running AI models locally.

ℹ️We earn from qualifying purchases through affiliate links at no extra cost to you. This supports our free content and research.

Can Apple M2 Max run meta-llama/Llama-3.2-3B-Instruct?

Runs Q496GB VRAM availableRequires 2GB+

Apple M2 Max meets the minimum VRAM requirement for Q4 inference of meta-llama/Llama-3.2-3B-Instruct. Review the quantization breakdown below to see how higher precision settings impact VRAM and throughput.

What this means for you

Apple M2 Max can run meta-llama/Llama-3.2-3B-Instruct with Q4 quantization. At approximately 64 tokens/second, you can expect Good speed - acceptable for interactive use.

You have 94GB headroom, which is sufficient for system overhead and smooth operation.

Quantization breakdown

QuantizationVRAM neededVRAM availableEstimated speedVerdict
Q42GB96GB63.51 tok/s✅ Fits comfortably
Q83GB96GB40.95 tok/s✅ Fits comfortably
FP166GB96GB24.24 tok/s✅ Fits comfortably

Suitable alternatives

NVIDIA H200 SXM 141GB
141GB
891.20 tok/s
Price: —
AMD Instinct MI300X
192GB
885.01 tok/s
Price: —
NVIDIA H200 SXM 141GB
141GB
635.06 tok/s
Price: —
NVIDIA H100 SXM5 80GB
80GB
633.16 tok/s
Price: —
AMD Instinct MI250X
128GB
611.92 tok/s
Price: —

More questions

Apple M2 Max specs & pricingFull guide for meta-llama/Llama-3.2-3B-Instructmeta-llama/Llama-3.2-3B-Instruct speed on Apple M2 Maxmeta-llama/Llama-3.2-3B-Instruct Q4 requirements