Gemma 3 on NVIDIA GeForce RTX 5080 · 16GB VRAM

✅ Runs (tight) — Gemma 3 12B @ Q5_K_M
Gemma 3 12B at Q5_K_M needs ~11.6 GB (weights 8.1 GB + KV 3.0 GB + overhead 512 MB @ 8K ctx) of your 14.4 GB usable VRAM — fits, but little headroom — close other apps or trim context. Expect ~35–55 tok/s (fast).
context @ Q5_K_M: comfortable to 4K · runs to 32K · won't fit past that on this rig
quantneedsspeed
~ Q8_015.7 GB~8–13 tok/s (usable)
✓ Q5_K_M11.6 GB~35–55 tok/s (fast)
✓ Q4_K_M10.4 GB~40–65 tok/s (very fast)
✓ Q3_K_M9.0 GB~45–75 tok/s (very fast)
$runlocal install gemma3:12b
⚠ 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 3: 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 5080: DeepSeek-R1 (distill) · Qwen2.5 · Qwen3 · Gemma 4 · Llama 3.1

Best models for a NVIDIA GeForce RTX 5080 · 16GB VRAM →

Architecturally similar

These share Gemma 3's KV-cache geometry — they size memory the same way, so here's how they fit on a NVIDIA GeForce RTX 5080 · 16GB VRAM too:

modelsharesverdict here
Gemma 2 16kv/128hd4kv/256hd8kv/256hd ✅ Runs (tight)
Falcon3 7B 4kv/256hd ✅ Runs comfortably

Check any combo yourself: open the checker →