Gemma 2 on NVIDIA GeForce RTX 5090 · 32GB VRAM

✅ Runs comfortably — Gemma 2 27B @ Q5_K_M
Gemma 2 27B at Q5_K_M needs ~21.8 GB (weights 18.0 GB + KV 2.9 GB + overhead 923 MB @ 8K ctx) of your 28.8 GB usable VRAM — plenty of headroom. Expect ~35–60 tok/s (fast).
context @ Q5_K_M: comfortable to 8K
quantneedsspeed
~ Q8_031.2 GB~7–12 tok/s (usable)
✓ Q5_K_M21.8 GB~35–60 tok/s (fast)
✓ Q4_K_M19.0 GB~40–65 tok/s (very fast)
✓ Q3_K_M15.9 GB~50–80 tok/s (very fast)
$runlocal install gemma2:27b
⚠ NVIDIA support is best-effort in v0.1 — verify before relying on it.
runlocal verdict card
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Gemma 2: Runs comfortably
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 5090: DeepSeek-R1 (distill) · Qwen2.5 · Qwen3 · Llama 3.1 · Gemma 3

Best models for a NVIDIA GeForce RTX 5090 · 32GB 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 5090 · 32GB VRAM too:

modelsharesverdict here
Gemma 4 8kv/256hd ✅ Runs comfortably
Falcon3 7B 4kv/256hd ✅ Runs comfortably

Check any combo yourself: open the checker →