text model · DeepSeek-V4 · macOS

Can I run DeepSeek-V4-Pro on Apple M4 (24GB)?

Compatibility verdict VRAM threshold engine

No, not enough memory would not load

No. DeepSeek-V4-Pro needs ~965 GB even at Q4_K_M, but Apple M4 (24GB) only has ~16 GB usable.

Needs ~965 GB Device usable ~16 GB

Needs ~965 GB even at Q4_K_M, but only ~16 GB is usable.

That figure is at a 4k context and moves about ±15% as context length changes.

The gap is about 949 GB: DeepSeek-V4-Pro needs roughly 965 GB at Q4_K_M and Apple M4 (24GB) leaves only about 16 GB usable for a model. No single tracked device has enough memory; DeepSeek-V4-Pro needs a multi-GPU or high-memory rig.

Q4_K_M needed: ~965 GB
Usable on device: ~16 GB
Device memory: 24 GB

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Which quant fits

Quant ladder vs ~16 GB usable

Q2_K

~680.4 GB

Q3_K_M

~792.4 GB

Q4_K_M

~965 GB

Q5_K_M

~1150.4 GB

Q6_K

~1322.4 GB

Q8_0

~1682.2 GB

FP16

~3210.4 GB

The line marks Apple M4 (24GB)'s ~16 GB budget; rungs past it are too large.

How to run it

On macOS use LM Studio (Polished GUI, ships MLX on Apple Silicon, one-click model downloads.).

Model DeepSeek-V4

Parameters: 1600B (MoE, 49B active)
Q4_K_M size: 954.58 GB
Q8_0 size: 1671.82 GB
Context: 1000k

Full DeepSeek-V4-Pro requirements →

Device macOS

Memory: 24 GB unified
Usable for weights: ~16 GB
Power draw: ~65 W
Best runtime: Ollama (MLX backend, preview) / MLX direct

Best models for Apple M4 (24GB) →

What you can run instead

FAQ

Can Apple M4 (24GB) run DeepSeek-V4-Pro?

No. DeepSeek-V4-Pro needs ~965 GB even at Q4_K_M, but Apple M4 (24GB) only has ~16 GB usable.

How much memory does DeepSeek-V4-Pro need?

Apple M4 (24GB) does not have enough memory. At Q4_K_M the weights are ~954.58 GB; with KV cache and runtime overhead, budget ~965 GB at a 4k context. It is a Mixture-of-Experts model (1600B total / 49B active), so all experts must stay in memory; memory tracks total params, not active params.

What is the best tool to run DeepSeek-V4-Pro on macOS?

LM Studio for a simple setup; mlx-lm for the most speed. vLLM is NOT a Mac tool, it is a CUDA/Linux serving engine. Unified memory is not a fixed VRAM slice; ~70% is usable for weights.

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Markdown

[![DeepSeek-V4-Pro on Apple M4 (24GB)](https://localmodel.run/badge/deepseek-v4-pro/apple-m4-24gb.svg)](https://localmodel.run/can-i-run/deepseek-v4-pro/apple-m4-24gb)

Sources

Weights are measured from GGUF files; KV cache and overhead are computed, so totals can vary ~15% with context and runtime. Any tok/s is a bandwidth estimate. See methodology.