Mistral Nemo on Apple M2 Pro · 32GB

✅ Runs comfortably — Mistral Nemo 12B @ Q8_0
Mistral Nemo 12B at Q8_0 needs ~14.0 GB (weights 12.1 GB + KV 1.3 GB + overhead 621 MB @ 8K ctx) of your 18.4 GB usable (of 32.0 GB unified memory) — plenty of headroom. Expect ~8–13 tok/s (usable).
context @ Q8_0: comfortable to 8K · runs to 64K · won't fit past that on this rig
quantneedsspeed
✓ Q8_014.0 GB~8–13 tok/s (usable)
✓ Q6_K11.1 GB~10–17 tok/s (usable)
✓ Q5_K_M9.9 GB~11–19 tok/s (usable)
✓ Q4_K_M8.7 GB~13–20 tok/s (usable)
$runlocal install mistral-nemo:12b
runlocal verdict card
download card share on x share on reddit drop it in your model-drop post
Mistral Nemo: Runs comfortably
for your own README — links back here

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

Also runs on a Apple M2 Pro: DeepSeek-R1 (distill) · Mistral Small 3 · Qwen3 · Llama 3.1 · Qwen2.5

Best models for a Apple M2 Pro · 32GB →

Architecturally similar

These share Mistral Nemo's KV-cache geometry — they size memory the same way, so here's how they fit on a Apple M2 Pro · 32GB too:

modelsharesverdict here
Qwen2.5-Coder 8kv/128hd ✅ Runs (tight)
Llama 3.2 8kv/128hd ✅ Runs comfortably
Llama 3.3 8kv/128hd 🐢 CPU-only (slow)
Mistral 7B 8kv/128hd ✅ Runs comfortably
Codestral 8kv/128hd ✅ Runs (tight)
Llama 3.2 Vision 8kv/128hd ✅ Runs comfortably
Mixtral 8x7B 8kv/128hd 🐢 CPU-only (slow)
Phi-4-mini 8kv/128hd ✅ Runs comfortably

…and 6 more — see the Mistral Nemo page.

Check any combo yourself: open the checker →