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Models › Llama 3.1 8B Instruct › Apple M4 (16 GB)

Can I run Llama 3.1 8B Instruct on Apple M4 (16 GB)?

Yes

Yes. Llama 3.1 8B Instruct fits fully on the Apple M4 (16 GB) at Q8_0 (about 10.6 GB of 11 GB usable, 8k context). ESTIMATE

Verdict by quantization (8k context, f16 KV, 32 GB RAM for offload)

QuantNeedsApple M4 (16 GB) (16 GB, ~11 GB GPU-usable)
Q3_K_M5.9 GB✅ Fits
IQ4_XS6.2 GB✅ Fits
Q4_K_M6.8 GB✅ Fits
MXFP46.6 GB✅ Fits
Q5_K_M7.7 GB✅ Fits
Q6_K8.6 GB✅ Fits
Q8_010.6 GB⚠️ Fits, tight
F1618.5 GB❌ Doesn't fit

Measured speed MEASURED

QuantGeneration (tok/s)Prompt (tok/s)Source
Q4_K_M17.7—www.localscore.ai (2026-10-22)
Q4_K_M17.12—www.localscore.ai (2026-10-22)
Q4_K_M16.4—www.localscore.ai (2026-10-22)
Q4_K_M17.8—www.localscore.ai (2026-10-22)
Q4_K_M12.98—www.localscore.ai (2026-10-22)
Q4_K_M17.4—www.localscore.ai (2026-10-22)
Q4_K_M18.1—www.localscore.ai (2026-10-22)
Q4_K_M15.27—www.localscore.ai (2026-10-22)

Memory figures are estimates from the model's parameter count and config.json (Hugging Face). How we calculate. Last verified with data from 2026-10-22.

FAQ

Can I run Llama 3.1 8B Instruct on the Apple M4 (16 GB)?

Yes. Llama 3.1 8B Instruct fits fully on the Apple M4 (16 GB) at Q8_0 (about 10.6 GB of 11 GB usable, 8k context).

How much VRAM does Llama 3.1 8B Instruct need?

About 6.8 GB at Q4_K_M and 10.6 GB at Q8_0 with 8k context (estimate).

Llama 3.1 8B Instruct on other hardware: RTX 3060 12GB · RTX 4060 Ti 16GB · RTX 5060 Ti 16GB · RTX 4070 Ti Super · RTX 3090 · RTX 4090 · RTX 5090 · Radeon RX 7900 XTX · Apple M4 Pro (48 GB) · Apple M4 Max (128 GB)

Other models on Apple M4 (16 GB): Qwen3.5 9B · Gemma 4 12B · Qwen3 VL 8B

See all models for a 16GB Mac · all Mac sizes.

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