| quant | needs | speed |
|---|---|---|
| ~ Q8_0 | 25.8 GB | — |
| ~ Q5_K_M | 17.6 GB | — |
| ~ Q4_K_M | 15.3 GB | ~3–5 tok/s (slow) |
| ~ Q3_K_M | 12.5 GB | ~4–6 tok/s (slow) |
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 →
These share Mistral Small 3'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:
| model | shares | verdict 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 Nemo | 8kv/128hd | ✅ Runs (tight) |
| Codestral | 8kv/128hd | ⚠️ Partial GPU offload |
| Llama 3.2 Vision | 8kv/128hd | ✅ Runs comfortably |
| Mixtral 8x7B | 8kv/128hd | 🐢 CPU-only (slow) |
…and 7 more — see the Mistral Small 3 page.
Check any combo yourself: open the checker →