Can I run it?

Can I run Hy MT2 1.8B on Apple M4 Pro?

Runs great

Runs great fully in unified memory on your Apple M4 Pro at Q8_0, 8K context, about 61–84 tok/s. Weights 1.78 GB plus 0.50 GB of KV cache — 2.60 GB of 18.0 GB usable. Up to 200K context still fits.

Best quantQ8_0

Working context8K

Max that fits200K

Speed61–84 tok/s

Weights1.78 GB

KV cache0.50 GB

Total2.60 GB

Usable18.0 GB

Hy MT2 1.8B details · Apple M4 Pro page · How this estimate is made

Run commands

llama.cpp

llama-server -hf tencent/Hy-MT2-1.8B-GGUF:Q8_0 -c 8192 -ngl 32

No matching name in the Ollama library snapshot.

LM Studio

lms get tencent/Hy-MT2-1.8B-GGUF
# Then load quant Q8_0

Assumptions

Estimate, not a benchmark. Decode speed uses a memory-bandwidth model at 55–75% of peak.
KV cache is FP16. Engine overhead assumes llama.cpp (0.3 GB + 1% of the weights). Ollama is closer to 0.9 GB + 3%, LM Studio closer to 1 GB + 3%.
Q8_0 size is the real GGUF file size from Hugging Face.
Unified memory uses 75% for the GPU by default, and always leaves about 5 GB for the OS.
Speed is quoted at 8K context, not at the maximum context that still fits.

Larger models that also fit

Can I run Qwen3.8 27B on Apple M4 Pro? — Tight fit, UD-Q4_K_XL, 8.3–11 tok/s
Can I run gemma 4 12b it on Apple M4 Pro? — Runs, UD-Q8_K_XL, 8.9–12 tok/s
Can I run Qwen3.5 9B on Apple M4 Pro? — Tight fit, BF16, 8.3–11 tok/s

Updated 2026-10-24. Profile on this page is the device default.