What if DeepSeek-R1 Distill 8B runs out of memory on Mac M4 Pro 24GB?

Unload idle models, cap GPU layers with --num-gpu, and cut context to 2048. KV cache grows with context and is the usual OOM cause.

Should I use Q4 or Q8 for DeepSeek-R1 Distill 8B?

Start Q4_K_M. Bigger model at Q4 beats smaller at Q8. Use Q8 only with 2GB+ headroom.

can i run · seo

Yes — DeepSeek-R1 Distill 8B runs on Mac M4 Pro 24GB

DeepSeek-R1 Distill 8B (8B) needs 16GB VRAM at FP16 vs your 24GB unified. Estimated ~1–1 tok/s.

Distilled reasoner. Long traces, strong math, fits any 8 GB card at Q4.

best fit on this rig · weights + KV + headroom

FP16 · 16GB weights+0.4GB KV @ 8kfits GPU~1–1 tok/s

quant	weights	+ KV 8k	fits 24GB?
Q4	5.2GB	~5.6GB	✓ yes
Q5	6.5GB	~6.9GB	✓ yes
Q8	9GB	~9.4GB	✓ yes
FP16	16GB	~16.4GB	✓ yes

File size ≠ runtime. KV grows with context — halve to 4k/2k if long chats OOM. Leave 1–2GB free.

ollama run deepseek-r1:8b

Run it: 1) install Ollama · 2) copy command · 3) verify with ollama ps (want 100% GPU).

huggingface GGUF

faq · straight answers

Can DeepSeek-R1 Distill 8B run on Mac M4 Pro 24GB?

DeepSeek-R1 Distill 8B (8B) needs 16GB VRAM at FP16 vs your 24GB unified. Estimated ~1–1 tok/s. Model context 32k. Compare with all models or re-check with your exact specs on the bench.

What if it OOMs?

Unload with ollama stop, cap layers --num-gpu 28, cut context to 2k. See the OOM fixer on the homepage.

Q4 or Q8 on this rig?

Start FP16. Bigger model at Q4 beats smaller at Q8. Only go Q8 if 2GB+ headroom remains.

How fast will it be?

About ~1–1 tok/s when 100% on GPU. Any CPU offload drops speed 5–20× — check ollama ps.

Is MIT commercial-safe?

Yes — MIT allows commercial use.

also fits Mac M4 Pro 24GB

Qwen3.5 9B · Q8 MiniCPM5 2B · FP16 Mistral Small 3.2 · Q4 InternVL3 8B · FP16

DeepSeek-R1 Distill 8B on other rigs

8 GB laptop RTX 3060 12GB RTX 4070 12GB RTX 4090 24GB 2x RTX 3090 (48GB)RTX 5090 32GB

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