Ministral 3 14B on NVIDIA GeForce RTX 3060 · 12GB VRAM

✅ Runs (tight) — Ministral 3 14B @ Q4_K_M
Ministral 3 14B 14B at Q4_K_M needs ~9.4 GB (weights 7.7 GB + KV 1.3 GB + overhead 512 MB @ 8K ctx) of your 10.8 GB usable VRAM — fits, but little headroom — close other apps or trim context. Expect ~18–30 tok/s (fast).
context @ Q4_K_M: comfortable to 2K · runs to 64K · won't fit past that on this rig
quantneedsspeed
~ Q8_015.3 GB~3–5 tok/s (slow)
✓ Q4_K_M9.4 GB~18–30 tok/s (fast)
⚠ NVIDIA support is best-effort in v0.1 — verify before relying on it.
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Ministral 3 14B: 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 3060: Qwen3 · DeepSeek-R1 (distill) · Qwen2.5 · Llama 3.1 · Gemma 4

Best models for a NVIDIA GeForce RTX 3060 · 12GB VRAM →

Architecturally similar

These share Ministral 3 14B'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
Llama 3.2 Vision 8kv/128hd ✅ Runs comfortably

…and 8 more — see the Ministral 3 14B page.

Check any combo yourself: open the checker →