Mistral Nemo on Apple M2 · 16GB

🐢 CPU-only (slow) — 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 8.2 GB usable (of 16.0 GB unified memory) — runs on CPU only. Expect ~0.5–0.9 tok/s (slow).
context @ Q8_0: runs to 8K · won't fit past that on this rig
quantneedsspeed
~ Q8_014.0 GB~0.5–0.9 tok/s (slow)
~ Q6_K11.1 GB~0.7–1 tok/s (slow)
~ Q5_K_M9.9 GB~0.7–1 tok/s (slow)
~ Q4_K_M8.7 GB~0.9–1 tok/s (slow)
$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: CPU-only (slow)
for your own README — links back here

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

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

Best models for a Apple M2 · 16GB →

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 · 16GB too:

modelsharesverdict here
Qwen2.5-Coder 8kv/128hd ✅ Runs (tight)
Llama 3.2 8kv/128hd ✅ Runs comfortably
Llama 3.3 8kv/128hd ❌ Won't fit
Mistral 7B 8kv/128hd ✅ Runs (tight)
Mistral Small 3 8kv/128hd 🐢 CPU-only (slow)
Codestral 8kv/128hd 🐢 CPU-only (slow)
Llama 3.2 Vision 8kv/128hd ✅ Runs (tight)
Mixtral 8x7B 8kv/128hd ❌ Won't fit

…and 7 more — see the Mistral Nemo page.

Check any combo yourself: open the checker →