OLMo 2 7B on NVIDIA GeForce RTX 5080 · 16GB VRAM

✅ Runs (tight) — OLMo 2 7B @ Q8_0
OLMo 2 7B 7B at Q8_0 needs ~11.7 GB (weights 7.2 GB + KV 4.0 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 @ Q8_0: comfortable to 4K
quantneedsspeed
✓ Q8_011.7 GB~35–55 tok/s (fast)
✓ Q6_K10.1 GB~40–70 tok/s (very fast)
✓ Q4_K_M8.7 GB~50–80 tok/s (very fast)
$runlocal install olmo2:7b
⚠ 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
OLMo 2 7B: 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 OLMo 2 7B'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
Code Llama 32kv/128hd ✅ Runs (tight)
LLaVA 32kv/128hd ✅ Runs (tight)

Check any combo yourself: open the checker →