惯性聚合 高效追踪和阅读你感兴趣的博客、新闻、科技资讯
阅读原文 在惯性聚合中打开

推荐订阅源

J
Java Code Geeks
腾讯CDC
博客园 - 聂微东
爱范儿
爱范儿
罗磊的独立博客
P
Proofpoint News Feed
博客园 - Franky
博客园 - 三生石上(FineUI控件)
OSCHINA 社区最新新闻
OSCHINA 社区最新新闻
酷 壳 – CoolShell
酷 壳 – CoolShell
Jina AI
Jina AI
Blog — PlanetScale
Blog — PlanetScale
让小产品的独立变现更简单 - ezindie.com
让小产品的独立变现更简单 - ezindie.com
博客园 - 司徒正美
美团技术团队
MongoDB | Blog
MongoDB | Blog
WordPress大学
WordPress大学
A
About on SuperTechFans
I
InfoQ
博客园_首页
钛媒体:引领未来商业与生活新知
钛媒体:引领未来商业与生活新知
H
Help Net Security
Microsoft Azure Blog
Microsoft Azure Blog
G
Google Developers Blog

Will Angel's Blog

Superhuman AI coding still makes software worse I did not say that, you did The AI Tarpit: Why You Can't Stop Reading Your Code Anthropic Fable The Stochastically K-Shaped Engineering Job Market Claude.AI Pro Plan quotas too small for deep research Jankmarking: Janky Benchmarking Offline Agentic Coding: OpenCode Offline Agentic Coding Washington DC on track for most volatile temperature year since 1959
Apple Silicon costs more than OpenRouter
2026-05-17 · via Will Angel's Blog

Tags: LLMs, Local LLMs, Apple Silicon, OpenRouter, AI Inference, Cost Analysis

Offline Agentic Coding part 3: Apple Silicon costs more than OpenRouter.

Published 2026-05-17

Apple silicon costs more than open router. Spreadsheet showing tokens per second and costs to show overall cost per million tokens.

Apple silicon costs more than OpenRouter.

At ~50-100 watts under load, and ~$0.20 per kWh, my M5 MacbookPro will cost a few cents per hour. Accelerated depreciation (if any) from shortening the lifespan of the device will be more expensive than the electricity. At a few tens of tokens per second this works out to ammortized costs of ~$1.50 per million tokens. Openrouter for comparable models is 1/3rd the price and ~2x the speed.

Electricity

In Northern Virginia my last electricity bill worked out to $0.18 per kilowatt hour. Let's round up to $0.20 per kWh.

EIA has average residential costs for 2025 at $0.1730 per kWh in the US.
https://www.eia.gov/electricity/monthly/epm_table_grapher.php?t=table_5_03

At ~50-100 watts and $0.18/kWh that's $0.009 or $0.018 per hour. $0.02 per hour. $0.48 cents per day for the electricity to be running inference at 100%.

Hardware

A 14 inch MBP with M5 Max and 64 gigs of ram is currently listed as $4299 on the apple website. 128 gigs will cost you more but 64 gigs should run a model like Gemma 4 31b, which is almost anthropic sonnet levels of performance.

For cost allocation, let's consider that this hardware will last 3, 5, or 10 years. The cost per year is $1433, $860, or $430 respectively.

The hourly cost over 3, 5, and 10 years is thus:

  • $0.16358
  • $0.09815
  • $0.04908

Depending on useful lifespan, I think 5 years is a reasonable estimate for normal use. 7 or 10 is very plausible. At maxed out inference 3 years may be a reasonable estimate as well.

Tokenomics

The big question is how many tokens per hour can you get out of a local model. My M5 Max testing seems to be in the 10-40 tokens per second range for a serious model like Gemma4:31b. At 10 tokens per second that's 36000 tokens per hour.

36000 tokens per hour across our 3-10 year lifespan at $0.18 per kwh gives a price per million tokens of $1.61 to $4.79 on the high end.

At 40 tokens per second that's 144000 tokens per hour which gets you to $0.40 to $1.20 per million tokens.

For apple silicon, the hardware cost dominates.

OpenRouter has Gemma4 31b at ~38-50 cents per million tokens. This means that on the optimistic side (50 watts, 40 tokens per second, and 10 years) the pro max is as cheap as openrouter. On the pessimistic side (100 watts and 3 years at 10 tokens per second) the pro max is 10x the cost. I think ~3x the cost per million tokens is likely the right number for local inference on the pro max from an accounting perspective.

Conclusion

Speed of inference is the biggest factor here though for most cases. Local inference is slower than cloud inference. Some of the gemma 4 providers on openrouter get up to 60-70 tokens per second, which is 3-7 times faster than what I'm seeing with the pro max (~10-20 tokens per second). For a human employee with a work laptop, their salary costs are going to be ~1000x the cost of the tokens they can generate locally. Throwing money at anthropic makes more sense in this context.

It's still wild that a consumer device can run models that are close to anthropic sonnet levels of performance.