A detailed cost analysis by developer William Angel challenges the assumption that running LLMs locally on Apple Silicon is more economical than cloud-based inference. According to Angel's calculations, OpenRouter delivers approximately one-third the cost of local Apple Silicon inference while providing roughly 2x the speed.
Hardware Depreciation Dominates Local Inference Costs
Angel's analysis, which tested the Gemma4:31b model on a 14-inch M5 Max MacBook Pro ($4,299), reveals that hardware depreciation significantly outweighs electricity costs for local inference. Across different device lifespans, the hourly hardware cost ranges from $0.05 (10-year lifespan) to $0.16 (3-year lifespan). Combined with electricity costs of approximately $0.48 per day at $0.20 per kWh, the total cost per million tokens ranges from $0.40 in the most optimistic scenario to $4.79 in pessimistic scenarios, with a realistic estimate around $1.50.
In comparison, OpenRouter's pricing for the same Gemma4:31b model sits at approximately $0.50 per million tokens, making it substantially cheaper for most use cases.
Cloud Services Deliver Superior Speed
Beyond cost advantages, Angel's testing revealed significant performance differences. While the M5 MacBook Pro generated 10-40 tokens per second for Gemma4:31b (translating to 36,000-144,000 tokens per hour), cloud providers like OpenRouter achieved 60-70 tokens per second—effectively doubling throughput.
The analysis sparked significant discussion on Hacker News, where it received 132 points and 100 comments. Developers debated the economics of local versus cloud inference, privacy tradeoffs, and specific edge cases where local inference might still make sense despite the cost disadvantage.
When Local Inference Makes Sense
While the numbers favor cloud services for most scenarios, Angel's analysis acknowledges situations where local inference remains valuable. Privacy-sensitive applications, offline requirements, and workflows that can fully amortize hardware costs over extended periods may still benefit from local deployment. However, for developers evaluating cost-effectiveness alone, the analysis suggests cloud APIs offer superior economics.
Key Takeaways
- OpenRouter costs approximately 1/3 the price of local Apple Silicon inference while delivering 2x the speed
- Hardware depreciation dominates local inference costs, ranging from $0.05 to $0.16 per hour depending on device lifespan
- Realistic cost per million tokens on Apple Silicon is around $1.50, compared to $0.50 on OpenRouter for Gemma4:31b
- Cloud providers achieve 60-70 tokens per second versus 10-40 tokens per second on local Apple Silicon
- The $4,299 M5 Max MacBook Pro requires significant utilization to justify costs purely for LLM inference