What if MiniCPM5 2B runs out of memory on Mac M4 16GB?

Unload idle models, cap GPU layers with --num-gpu, and cut context to 2048. KV cache grows with context and is the usual OOM cause.

Should I use Q4 or Q8 for MiniCPM5 2B?

Start Q4_K_M. Bigger model at Q4 beats smaller at Q8. Use Q8 only with 2GB+ headroom.

can i run · seo

Yes — MiniCPM5 2B runs on Mac M4 16GB

MiniCPM5 2B (2.5B) needs 5GB VRAM at FP16 vs your 16GB unified. Estimated ~11–14 tok/s.

Sept-2026 edge refresh: 2.5B, 128k context, tool-calling. CPU-first; Q4 ≈ 1.6 GB.

best fit on this rig · weights + KV + headroom

FP16 · 5GB weights+0.2GB KV @ 8kfits GPU~11–14 tok/s

quant	weights	+ KV 8k	fits 16GB?
Q4	1.6GB	~1.8GB	✓ yes
Q5	1.9GB	~2.1GB	✓ yes
Q8	2.7GB	~2.9GB	✓ yes
FP16	5GB	~5.2GB	✓ yes

File size ≠ runtime. KV grows with context — halve to 4k/2k if long chats OOM. Leave 1–2GB free.

llama-cli -hf openbmb/MiniCPM5-2B-GGUF:Q4_K_M

Run it: 1) install Ollama · 2) copy command · 3) verify with ollama ps (want 100% GPU).

huggingface GGUF

faq · straight answers

Can MiniCPM5 2B run on Mac M4 16GB?

MiniCPM5 2B (2.5B) needs 5GB VRAM at FP16 vs your 16GB unified. Estimated ~11–14 tok/s. Model context 128k. Compare with all models or re-check with your exact specs on the bench.

What if it OOMs?

Unload with ollama stop, cap layers --num-gpu 28, cut context to 2k. See the OOM fixer on the homepage.

Q4 or Q8 on this rig?

Start FP16. Bigger model at Q4 beats smaller at Q8. Only go Q8 if 2GB+ headroom remains.

How fast will it be?

About ~11–14 tok/s when 100% on GPU. Any CPU offload drops speed 5–20× — check ollama ps.

Is Apache-2.0 commercial-safe?

Yes — Apache-2.0 allows commercial use.

also fits Mac M4 16GB

Qwen3.5 9B · Q8 InternVL3 8B · Q8 DeepSeek-R1 Distill 8B · Q8

MiniCPM5 2B on other rigs

8 GB laptop RTX 3060 12GB RTX 4070 12GB RTX 4090 24GB 2x RTX 3090 (48GB)RTX 5090 32GB

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