Comparisons
Honest model comparisons, benchmarks and side-by-side evaluations for local AI on Apple Silicon Macs: Ollama, LM Studio, MLX, Whisper and more.
- Compare models
- Understand benchmarks
- Find the right tool
- Make decisions
How to read these comparisons
Benchmarks are not always comparable
A score only makes sense with model version, benchmark version, quantization, prompting, tool use, context length and runtime.
Local vs cloud is a data-flow question
Local models can keep files on your Mac. Cloud APIs can offer larger context, stronger tools and better agent workflows.
Mac memory changes the answer
A model that looks great on paper may be unrealistic on 8 GB or 16 GB Macs once context, KV cache and other apps are included.
Price is more than tokens
Cloud models have input/output/tool costs. Local models have hardware, power, storage, setup and maintenance costs.
How we compare models
Our comparisons separate model claims from practical Mac usage. When an article discusses benchmarks, it should identify the model variant, source, benchmark version, tool use, context length and whether the result comes from a vendor claim or an independent test. For Mac recommendations, we consider Apple Silicon generation, unified memory, quantization, context size, local runtime, privacy and real-world workflow fit.