OLMo 2 7B on Apple M2 · 16GB

🐢 CPU-only (slow) — OLMo 2 7B @ Q8_0
OLMo 2 7B 7B at Q8_0 needs ~11.7 GB (weights 7.2 GB + KV 4.0 GB + overhead 512 MB @ 8K ctx) of your 8.2 GB usable (of 16.0 GB unified memory) — runs on CPU only. Expect ~0.6–1 tok/s (slow).
context @ Q8_0: runs to its full 4K
quantneedsspeed
~ Q8_011.7 GB~0.6–1 tok/s (slow)
~ Q6_K10.1 GB~0.7–1 tok/s (slow)
~ Q4_K_M8.7 GB~0.9–1 tok/s (slow)
$runlocal install olmo2:7b
runlocal verdict card
download card share on x share on reddit drop it in your model-drop post
OLMo 2 7B: 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 OLMo 2 7B's KV-cache geometry — they size memory the same way, so here's how they fit on a Apple M2 · 16GB too:

modelsharesverdict here
Code Llama 32kv/128hd 🐢 CPU-only (slow)
LLaVA 32kv/128hd 🐢 CPU-only (slow)

Check any combo yourself: open the checker →