DeepSeek-R1 (distill) on Apple M1 · 8GB

✅ Runs (tight) — DeepSeek-R1 (distill) 1.5B @ Q8_0
DeepSeek-R1 (distill) 1.5B at Q8_0 needs ~2.5 GB (weights 1.8 GB + KV 224 MB + overhead 512 MB @ 8K ctx) of your 2.9 GB usable (of 8.0 GB unified memory) — fits, but little headroom — close other apps or trim context. Expect ~19–30 tok/s (fast).
context @ Q8_0: runs to its full 128K
quantneedsspeed
~ FP164.0 GB~1–2 tok/s (slow)
✓ Q8_02.5 GB~19–30 tok/s (fast)
✓ Q4_K_M1.8 GB~30–50 tok/s (fast)
$runlocal install deepseek-r1:1.5b
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 Pro · Apple M2 · Apple M3 Pro · Apple M2 Pro · Apple M4 Pro · Apple M3 Max

Also runs on a Apple M1: Qwen2.5 · Qwen3 · Llama 3.2 · Gemma 2 · Gemma 3

Best models for a Apple M1 · 8GB →

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 M1 · 8GB too:

modelsharesverdict here
Llama 3.1 8kv/128hd 🐢 CPU-only (slow)
Qwen2.5-Coder 2kv/128hd4kv/128hd8kv/128hd ✅ Runs comfortably
Llama 3.3 8kv/128hd ❌ Won't fit
Mistral 7B 8kv/128hd 🐢 CPU-only (slow)
Mistral Small 3 8kv/128hd ❌ Won't fit
Mistral Nemo 8kv/128hd ❌ Won't fit
Codestral 8kv/128hd ❌ Won't fit
Llama 3.2 Vision 8kv/128hd ❌ Won't fit

…and 12 more — see the DeepSeek-R1 (distill) page.

Check any combo yourself: open the checker →