| quant | needs | speed |
|---|---|---|
| ✗ Q8_0 | 75.8 GB | — |
| ✗ Q5_K_M | 51.3 GB | — |
| ✗ Q4_K_M | 44.1 GB | — |
| ✗ Q3_K_M | 36.0 GB | — |
| ~ Q2_K | 28.3 GB | ~4–7 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 AMD Radeon RX 7900 XTX: DeepSeek-R1 (distill) · Qwen3 · Qwen2.5 · Gemma 3 · Mistral Small 3
Best models for a AMD Radeon RX 7900 XTX · 24GB VRAM →
These share Llama 3.3's KV-cache geometry — they size memory the same way, so here's how they fit on a AMD Radeon RX 7900 XTX · 24GB VRAM too:
| model | shares | verdict here |
|---|---|---|
| Llama 3.1 | 8kv/128hd | ✅ Runs comfortably |
| Qwen2.5-Coder | 8kv/128hd | ✅ Runs (tight) |
| Llama 3.2 | 8kv/128hd | ✅ Runs comfortably |
| Mistral 7B | 8kv/128hd | ✅ Runs comfortably |
| Mistral Nemo | 8kv/128hd | ✅ Runs comfortably |
| Codestral | 8kv/128hd | ✅ Runs comfortably |
| Llama 3.2 Vision | 8kv/128hd | ✅ Runs comfortably |
| Mixtral 8x7B | 8kv/128hd | ⚠️ Partial GPU offload |
…and 7 more — see the Llama 3.3 page.
Check any combo yourself: open the checker →