Can I run Code Llama?

Meta's Llama-2-based code models. Still popular on Ollama for completion.

coding · sizes: 7B, 13B, 34B · Llama 2 Community

What runs it

machinebest fitverdictspeed
Apple M1 · 8GB 34B Q3_K_M ❌ Won't fit
Apple M1 Pro · 16GB 13B Q4_K_M 🐢 CPU-only (slow) 0.9–2 tok/s
Apple M2 · 16GB 13B Q4_K_M 🐢 CPU-only (slow) 0.5–0.9 tok/s
Apple M3 Pro · 18GB 7B Q5_K_M ✅ Runs (tight) 9–15 tok/s
Apple M2 Pro · 32GB 34B Q3_K_M ✅ Runs (tight) 6–10 tok/s
Apple M4 Pro · 48GB 34B Q5_K_M ✅ Runs comfortably 6–9 tok/s
Apple M3 Max · 36GB 34B Q3_K_M ✅ Runs (tight) 10–17 tok/s
Apple M2 Max · 64GB 34B Q8_0 ✅ Runs (tight) 5–8 tok/s
Apple M4 Max · 128GB 34B Q8_0 ✅ Runs comfortably 6–11 tok/s
Apple M2 Ultra · 192GB 34B Q8_0 ✅ Runs comfortably 7–11 tok/s
NVIDIA GeForce RTX 3060 · 12GB VRAM 7B Q5_K_M ✅ Runs (tight) 16–25 tok/s
NVIDIA GeForce RTX 4070 · 12GB VRAM 7B Q5_K_M ✅ Runs (tight) 25–40 tok/s
NVIDIA GeForce RTX 4090 · 24GB VRAM 34B Q4_K_M ✅ Runs (tight) 19–30 tok/s
NVIDIA GeForce RTX 5080 · 16GB VRAM 13B Q4_K_M ✅ Runs (tight) 25–45 tok/s
NVIDIA GeForce RTX 5090 · 32GB VRAM 34B Q5_K_M ✅ Runs (tight) 30–50 tok/s
AMD Radeon RX 7900 XTX · 24GB VRAM 34B Q4_K_M ✅ Runs (tight) 17–30 tok/s

Shopping for a machine? What hardware do I need to run Code Llama? →

Check your exact rig: open the checker →

$npx runlocal-sh can-i-run codellama

Architectural kin

21 models share Code Llama's KV-cache geometry — they size memory the same way, so a rig that fits one tends to fit its same-size kin.

…and 9 more.

Explore the whole catalog by architecture: open the graph →