Gemma 2 on NVIDIA GeForce RTX 3060 · 12GB VRAM

✅ Runs (tight) — Gemma 2 9B @ Q6_K
Gemma 2 9B at Q6_K needs ~10.2 GB (weights 7.1 GB + KV 2.6 GB + overhead 512 MB @ 8K ctx) of your 10.8 GB usable VRAM — fits, but little headroom — close other apps or trim context. Expect ~14–25 tok/s (usable).
context @ Q6_K: comfortable to 2K · runs to its full 8K
quantneedsspeed
~ Q8_012.3 GB~4–6 tok/s (slow)
✓ Q6_K10.2 GB~14–25 tok/s (usable)
✓ Q5_K_M9.2 GB~16–25 tok/s (fast)
✓ Q4_K_M8.3 GB~19–30 tok/s (fast)
$runlocal install gemma2:9b
⚠ NVIDIA support is best-effort in v0.1 — verify before relying on it.
runlocal verdict card
download card share on x share on reddit drop it in your model-drop post
Gemma 2: Runs (tight)
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 NVIDIA GeForce RTX 3060: Qwen3 · DeepSeek-R1 (distill) · Qwen2.5 · Llama 3.1 · Gemma 3

Best models for a NVIDIA GeForce RTX 3060 · 12GB VRAM →

Architecturally similar

These share Gemma 2's KV-cache geometry — they size memory the same way, so here's how they fit on a NVIDIA GeForce RTX 3060 · 12GB VRAM too:

modelsharesverdict here
Gemma 4 8kv/256hd ✅ Runs (tight)
Falcon3 7B 4kv/256hd ✅ Runs (tight)

Check any combo yourself: open the checker →