Ollama MLX vs Metal: Apple Silicon Performance in 2026

Ollama 0.19 switched to Apple’s MLX framework for inference on Apple Silicon, delivering massive speed improvements over the previous Metal backend. Here’s what changed and what it means for local LLM users.

Last verified: April 2026

Quick Facts

Detail	Ollama MLX (0.19+)	Ollama Metal (0.18)
Framework	Apple MLX	Apple Metal
Prefill speed	~1851 tok/s (int4)	~1100 tok/s (int4)
Decode speed	~134 tok/s (int4)	~85 tok/s (int4)
Improvement	1.6-2x faster	Baseline
Memory usage	Better unified memory use	Standard
Status	Preview	Stable

What Changed

MLX is Apple’s machine learning framework built specifically for M-series chips. Unlike Metal (a general GPU framework), MLX is designed to exploit the unified memory architecture where CPU and GPU share the same memory pool.

Key improvements:

• Prompt processing ~1.6x faster
• Token generation ~1.6x faster
• Better memory efficiency — less overhead, more room for larger models
• NVFP4 quantization support — new precision format for even faster inference
• Smarter KV cache reuse — reduces repeated computation

Real-World Benchmarks (M4 Max, 128GB)

Model	Metal (0.18)	MLX (0.19)	Speedup
Llama 4 8B Q4	~85 tok/s	~134 tok/s	1.6x
Qwen 3.5 14B Q4	~45 tok/s	~72 tok/s	1.6x
Mistral Small 4 Q4	~55 tok/s	~88 tok/s	1.6x
DeepSeek V4 Q4	~30 tok/s	~48 tok/s	1.6x

Benchmarks from Ollama’s blog post. Your results will vary by model size and Mac configuration.

How to Enable MLX

# Update Ollama to 0.19+
brew upgrade ollama

# Or download directly
curl -fsSL https://ollama.com/install.sh | sh

# MLX is auto-detected on Apple Silicon
ollama run llama4:8b

No flags needed — Ollama 0.19 automatically uses MLX when running on Apple Silicon. You can verify with:

ollama --version
# Should show 0.19.x or later

When to Use What

Scenario	Recommendation
Apple Silicon Mac	Use Ollama 0.19+ (MLX auto)
NVIDIA GPU	Stick with CUDA backend
Intel Mac	Metal only (no MLX support)
Production server	NVIDIA + vLLM for throughput

MLX vs LM Studio on Apple Silicon

Both now leverage MLX. Ollama is better for CLI/API workflows and server use. LM Studio is better for GUI users who want a visual chat interface. Performance is comparable since both use the same underlying MLX framework.

Limitations

• MLX is in preview — some edge cases may have issues
• Only works on Apple Silicon (M1+)
• Not all quantization formats supported yet
• Large models (70B+) still need significant RAM

Last verified: April 2026