Llama 3.2 Vision on NVIDIA GeForce RTX 3060 · 12GB VRAM

✅ Runs comfortably — Llama 3.2 Vision 11B @ Q4_K_M
Llama 3.2 Vision 11B at Q4_K_M needs ~7.8 GB (weights 6.0 GB + KV 1.3 GB + overhead 512 MB @ 8K ctx) of your 10.8 GB usable VRAM — plenty of headroom. Expect ~20–35 tok/s (fast).
context @ Q4_K_M: comfortable to 8K · runs to its full 128K
quantneedsspeed
~ Q8_012.3 GB~4–6 tok/s (slow)
✓ Q4_K_M7.8 GB~20–35 tok/s (fast)
$runlocal install llama3.2-vision:11b
⚠ 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
Llama 3.2 Vision: 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 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 Llama 3.2 Vision'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
Qwen2.5-Coder 8kv/128hd ✅ Runs (tight)
Llama 3.2 8kv/128hd ✅ Runs comfortably
Llama 3.3 8kv/128hd ❌ Won't fit
Mistral 7B 8kv/128hd ✅ Runs (tight)
Mistral Small 3 8kv/128hd ⚠️ Partial GPU offload
Mistral Nemo 8kv/128hd ✅ Runs (tight)
Codestral 8kv/128hd ⚠️ Partial GPU offload
Mixtral 8x7B 8kv/128hd 🐢 CPU-only (slow)

…and 7 more — see the Llama 3.2 Vision page.

Check any combo yourself: open the checker →