Can DeepSeek V4 Flash 0731 run on MacBook Pro M4 Pro 24GB?

NO — Won’t fit
Q4_K_XL · 4K context · formula estimate

What this means

The checked Q4_K_XL build needs about 163.8GB, above this Mac's conservative 21GB working budget.

−142.8GB short
above the working budget
163.8GB
needed at Q4_K_XL
Q4_K_XL
quant selected
0GB
working headroom
needs 163.8 GBworking budget 21 GB · short 142.8 GB
Apple M4 Pro24 GB unified memoryMetalActive cooling

Where the memory goes

ComponentDetailGB
Model weightsQ4_K_XL GGUF (155.1 GB) + mmap overhead162.9
KV cache4K context window0.2
RuntimemacOS inference app + compute buffers0.8
Total neededat Q4_K_XL, 4K context163.8
Working budget24 GB unified memory − conservative macOS reserve21
Headroommemory shortfall−142.8

Pick your quant

QuantDownloadMemoryEstimated speedVerdict
IQ1_S82.5 GB87.6 GB Won't fit
IQ1_M86.9 GB92.2 GB Won't fit
IQ2_M90.9 GB96.4 GB Won't fit
IQ2_XXS90.9 GB96.4 GB Won't fit
Q2_K_XL96.8 GB102.6 GB Won't fit
IQ3_XXS104.2 GB110.4 GB Won't fit
IQ3_S116.1 GB122.9 GB Won't fit
Q3_K_M128.1 GB135.5 GB Won't fit
Q3_K_XL128.2 GB135.6 GB Won't fit
IQ4_NL136.7 GB144.5 GB Won't fit
IQ4_XS136.7 GB144.5 GB Won't fit
Q4_K_XL155.1 GB163.8 GB Won't fit
Q8_K_XL161.9 GB171 GB Won't fit

Other models on this Mac

DeepSeek V4 Flash 0731 on other MacBook Pro M4 Pro configurations

FAQ

Can the MacBook Pro M4 Pro · 24GB run DeepSeek V4 Flash 0731?

Not with the quants currently tracked. The selected Q4_K_XL build needs about 163.8GB, above the 21GB working budget.

Which DeepSeek V4 Flash 0731 quant should I use on this Mac?

None of the tracked quants fit this configuration safely. Choose a smaller model or a Mac with more unified memory.

Which app should I use for DeepSeek V4 Flash 0731 on this Mac?

Start with Unsloth Desktop. This page gives the complete point-and-click walkthrough.

Are these speeds measured on a MacBook Pro M4 Pro?

No. The displayed range remains a formula estimate for the tracked Unsloth IQ3 GGUF. Public M4 Max 128GB records range from about 8 tokens/s for stock llama.cpp on that IQ3 path to roughly 23–47 tokens/s for different, custom Q2 runtimes. Those are calibration evidence, not AICanRun verified benchmarks.