Local Mac inference costs 3–5× more per token than OpenRouter APIs
A cost breakdown shows running LLMs on Apple Silicon burns more cash per token than cloud APIs—unless you already own the machine or prioritize privacy.
Running LLMs locally on Apple Silicon costs more per token than renting inference through OpenRouter, according to a detailed energy and hardware analysis. The breakdown factors in electricity, amortized hardware costs, and utilization rates—and the math tilts heavily toward cloud APIs when you treat the Mac as a dedicated inference box.
The analysis calculates the full economic cost of local inference: hardware depreciation over expected lifespan, power draw during generation, and opportunity cost of capital tied up in a $2,000–$4,000 Mac Studio or MacBook Pro. When those numbers stack up against OpenRouter's per-token pricing—which aggregates inference from multiple providers including model creators and resellers with excess GPU capacity—cloud inference comes out cheaper for users who don't already own the hardware. But the comparison sparked immediate debate. Many practitioners pointed out that hardware purchased for other purposes—a daily-driver MacBook Pro, a Mac Studio that also handles video editing—shouldn't carry the full amortized cost in an inference calculation. If the machine is already paid for and already running, the marginal cost of spinning up a local model drops to near-zero: just the incremental electricity for a few extra watts during generation. That changes the economics dramatically for anyone treating local AI as a secondary workload on existing gear.
OpenRouter's pricing may not reflect long-term equilibrium. Many providers on the platform are model creators promoting their own releases, or infrastructure operators dumping underutilized capacity at reduced margins. Both strategies rely on investor capital to subsidize below-cost pricing. That subsidy won't last forever—but for now, it makes cloud inference cheaper than running a dedicated Mac for LLM work. Privacy remains the strongest non-economic argument for local inference: users who prioritize keeping prompts and outputs off third-party servers will pay the premium regardless of per-token math. For hobbyists and researchers already invested in Apple Silicon, the hardware is a sunk cost. For anyone buying a machine specifically to run models locally, OpenRouter currently wins on pure economics.