DeepSeek-R1 (distill) on Apple M3 Pro · 18GB

✅ Runs (tight) — DeepSeek-R1 (distill) 14B @ Q3_K_M
DeepSeek-R1 (distill) 14B at Q3_K_M needs ~8.8 GB (weights 6.8 GB + KV 1.5 GB + overhead 512 MB @ 8K ctx) of your 9.1 GB usable (of 18.0 GB unified memory) — fits, but little headroom — close other apps or trim context. Expect ~9–16 tok/s (usable).
context @ Q3_K_M: runs to 32K · won't fit past that on this rig
quantneedsspeed
✗ Q8_016.9 GB—
~ Q5_K_M11.8 GB~0.9–1 tok/s (slow)
~ Q4_K_M10.4 GB~1–2 tok/s (slow)
✓ Q3_K_M8.8 GB~9–16 tok/s (usable)
$runlocal install deepseek-r1:14b
runlocal verdict card
download card share on x share on reddit drop it in your model-drop post
DeepSeek-R1 (distill): Runs (tight)
for your own README — links back here

Same model, other machines: Apple M1 · Apple M1 Pro · Apple M2 · Apple M2 Pro · Apple M4 Pro · Apple M3 Max

Also runs on a Apple M3 Pro: Qwen2.5 · Mistral 7B · Qwen3 · Llama 3.1 · Gemma 3

Best models for a Apple M3 Pro · 18GB →

Architecturally similar

These share DeepSeek-R1 (distill)'s KV-cache geometry — they size memory the same way, so here's how they fit on a Apple M3 Pro · 18GB too:

modelsharesverdict here
Qwen2.5-Coder 2kv/128hd4kv/128hd8kv/128hd ✅ Runs (tight)
Llama 3.2 8kv/128hd ✅ Runs comfortably
Llama 3.3 8kv/128hd ❌ Won't fit
Mistral Small 3 8kv/128hd 🐢 CPU-only (slow)
Mistral Nemo 8kv/128hd ✅ Runs (tight)
Codestral 8kv/128hd 🐢 CPU-only (slow)
Llama 3.2 Vision 8kv/128hd ✅ Runs (tight)
Mixtral 8x7B 8kv/128hd ❌ Won't fit

…and 11 more — see the DeepSeek-R1 (distill) page.

Check any combo yourself: open the checker →