RTX 4070 vs Apple M4: GPU or Apple Silicon for Local AI?

The RTX 4070 is the most popular mid-range GPU for local AI at around $550. The Apple M4 powers MacBook Air and Mac Mini starting at $1,099. They represent two fundamentally different approaches: dedicated VRAM vs unified memory. This comparison reveals which is better for running LLMs locally.

GPU5 categories compared

Verdict

Tie

Apple M4 with 32 GB unified memory can run larger models (14B+) because it is not limited to 12 GB VRAM. The RTX 4070 is faster per token on models that fit in its 12 GB VRAM. For maximum model size and simplicity, choose M4. For maximum speed on 7B models, choose RTX 4070.

NVIDIA RTX 4070 (12 GB)

wins

Ties

draws

Apple M4 (16-32 GB unified)

wins

Category-by-Category Breakdown

Category	NVIDIA RTX 4070 (12 GB)	Apple M4 (16-32 GB unified)	Winner
Maximum Model Size	7B Q4 (12 GB VRAM limit)	14B Q4 (32 GB unified memory)	Apple M4 (16-32 GB unified)
Speed on 7B Models	~40-50 tok/s (fast GDDR6X)	~25 tok/s (slower bandwidth)	NVIDIA RTX 4070 (12 GB)
Setup Simplicity	Needs Linux/Windows, CUDA drivers	Just install Ollama, works immediately	Apple M4 (16-32 GB unified)
Power Consumption	200W TDP under load	15-30W total system power	Apple M4 (16-32 GB unified)
Total Cost of Ownership	~$550 (GPU) + PC ($800+)	$1,099-$1,499 (complete Mac)	Tie

Detailed Analysis

Maximum Model Size

Apple M4 (16-32 GB unified)

The RTX 4070 is hard-limited to 12 GB VRAM. Models that exceed this must offload to system RAM, which is very slow. M4 unified memory has no such split.

NVIDIA RTX 4070 (12 GB)

7B Q4 (12 GB VRAM limit)

Apple M4 (16-32 GB unified)

14B Q4 (32 GB unified memory)

Speed on 7B Models

NVIDIA RTX 4070 (12 GB)

When the model fits in VRAM, the RTX 4070 generates tokens 60-80% faster than M4 thanks to higher memory bandwidth.

NVIDIA RTX 4070 (12 GB)

~40-50 tok/s (fast GDDR6X)

Apple M4 (16-32 GB unified)

~25 tok/s (slower bandwidth)

Setup Simplicity

Apple M4 (16-32 GB unified)

M4 Mac with Ollama is install-and-go. RTX 4070 requires CUDA setup, driver management, and is not available on macOS.

NVIDIA RTX 4070 (12 GB)

Needs Linux/Windows, CUDA drivers

Apple M4 (16-32 GB unified)

Just install Ollama, works immediately

Power Consumption

Apple M4 (16-32 GB unified)

M4 uses a fraction of the power. For always-on AI inference, the electricity savings add up significantly.

NVIDIA RTX 4070 (12 GB)

200W TDP under load

Apple M4 (16-32 GB unified)

15-30W total system power

Total Cost of Ownership

Tie

Similar total cost. RTX 4070 needs a PC to install in ($800+), bringing total to $1,350+. Mac is an all-in-one solution.

NVIDIA RTX 4070 (12 GB)

~$550 (GPU) + PC ($800+)

Apple M4 (16-32 GB unified)

$1,099-$1,499 (complete Mac)

Frequently Asked Questions

Is RTX 4070 faster than M4 for AI?

Yes, for models that fit in 12 GB VRAM (7B Q4 and smaller). The RTX 4070 generates tokens 60-80% faster. But it cannot run 14B+ models that M4 with 32 GB handles easily.

Can RTX 4070 run 14B models?

Not well. 14B Q4 needs about 11 GB, which fits in VRAM but leaves almost no room for context. In practice, you need to offload to system RAM, which makes inference very slow.

Should I buy a Mac or build a PC for local AI?

For models up to 14B: Mac with 32 GB unified memory offers the best experience. For maximum speed on 7B models: a PC with RTX 4070 is faster. For 30B+ models: neither works well. You need 24 GB+ VRAM or a Mac with 64 GB+ unified memory.