Mistral 7B on Apple M1 · 8GB

🐢 CPU-only (slow) — Mistral 7B @ Q6_K
Mistral 7B 7B at Q6_K needs ~7.0 GB (weights 5.5 GB + KV 1.0 GB + overhead 512 MB @ 8K ctx) of your 2.9 GB usable (of 8.0 GB unified memory) — runs on CPU only. Expect ~0.7–1 tok/s (slow).
context @ Q6_K: runs to 8K · won't fit past that on this rig
quantneedsspeed
✗ Q8_08.7 GB—
~ Q6_K7.0 GB~0.7–1 tok/s (slow)
~ Q5_K_M6.3 GB~0.8–1 tok/s (slow)
~ Q4_K_M5.6 GB~0.9–2 tok/s (slow)
$runlocal install mistral:7b
runlocal verdict card
download card share on x share on reddit drop it in your model-drop post
Mistral 7B: CPU-only (slow)
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: DeepSeek-R1 (distill) · Qwen2.5 · Qwen3 · Llama 3.2 · Gemma 2

Best models for a Apple M1 · 8GB →

Architecturally similar

These share Mistral 7B'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 8kv/128hd ✅ Runs comfortably
Llama 3.3 8kv/128hd ❌ Won't fit
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
Mixtral 8x7B 8kv/128hd ❌ Won't fit

…and 7 more — see the Mistral 7B page.

Check any combo yourself: open the checker →