DeepSeek-R1 (distill) on Apple M2 Ultra · 192GB

✅ Runs comfortably — DeepSeek-R1 (distill) 70B (Llama) @ Q8_0
DeepSeek-R1 (distill) 70B (Llama) at Q8_0 needs ~75.8 GB (weights 69.8 GB + KV 2.5 GB + overhead 3.5 GB @ 8K ctx) of your 141 GB usable (of 192 GB unified memory) — plenty of headroom. Expect ~3–5 tok/s (slow).
context @ Q8_0: comfortable to 64K · runs to its full 128K
quantneedsspeed
✓ Q8_075.8 GB~3–5 tok/s (slow)
✓ Q5_K_M51.3 GB~5–8 tok/s (slow)
✓ Q4_K_M44.1 GB~6–9 tok/s (slow)
✓ Q2_K28.3 GB~9–14 tok/s (usable)
$runlocal install deepseek-r1:70b
runlocal verdict card
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DeepSeek-R1 (distill): Runs comfortably
for your own README — links back here

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

Also runs on a Apple M2 Ultra: Qwen3 · Qwen2.5 · Llama 3.1 · Llama 3.3 · Mistral Small 3

Best models for a Apple M2 Ultra · 192GB →

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 M2 Ultra · 192GB too:

modelsharesverdict here
Qwen2.5-Coder 2kv/128hd4kv/128hd8kv/128hd ✅ Runs comfortably
Llama 3.2 8kv/128hd ✅ Runs comfortably
Mistral 7B 8kv/128hd ✅ Runs comfortably
Mistral Nemo 8kv/128hd ✅ Runs comfortably
Codestral 8kv/128hd ✅ Runs comfortably
Llama 3.2 Vision 8kv/128hd ✅ Runs comfortably
Mixtral 8x7B 8kv/128hd ✅ Runs comfortably
Phi-4-mini 8kv/128hd ✅ Runs comfortably

…and 10 more — see the DeepSeek-R1 (distill) page.

Check any combo yourself: open the checker →