Gemma 2 on NVIDIA GeForce RTX 5080 · 16GB VRAM

✅ Runs (tight) — Gemma 2 9B @ Q8_0
Gemma 2 9B at Q8_0 needs ~12.3 GB (weights 9.1 GB + KV 2.6 GB + overhead 512 MB @ 8K ctx) of your 14.4 GB usable VRAM — fits, but little headroom — close other apps or trim context. Expect ~30–50 tok/s (fast).
context @ Q8_0: comfortable to 4K · runs to its full 8K
quantneedsspeed
✓ Q8_012.3 GB~30–50 tok/s (fast)
✓ Q6_K10.2 GB~40–65 tok/s (very fast)
✓ Q5_K_M9.2 GB~45–75 tok/s (very fast)
✓ Q4_K_M8.3 GB~50–85 tok/s (very 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 5080: DeepSeek-R1 (distill) · Qwen2.5 · Qwen3 · Gemma 4 · Gemma 3

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

modelsharesverdict here
Falcon3 7B 4kv/256hd ✅ Runs comfortably

Check any combo yourself: open the checker →