How Much Does a Local LLM Actually Cost to Run? I Measured Every Watt on Apple Silicon
Large Language Models How Much Does a Local LLM Actually Cost to Run? I Measured Every Watt on Apple Silicon Five models, sustained generation, real wall-socket energy at $0.31/kWh — and the surprise the RTX-3090 numbers predicted, only bigger. Justin Stewart Jul 28, 2026 12 min read Share The folk wisdom about running LLMs on your own hardware is that it’s free.
- ▪Large Language Models How Much Does a Local LLM Actually Cost to Run?
- ▪I Measured Every Watt on Apple Silicon Five models, sustained generation, real wall-socket energy at $0.31/kWh — and the surprise the RTX-3090 numbers predicted, only bigger.
- ▪Justin Stewart Jul 28, 2026 12 min read Share The folk wisdom about running LLMs on your own hardware is that it’s free.
Towards Data Science files mainly under ai. We currently carry 87 of its stories.
Story provenance
Source · retrieval · rights · ranking — open for full record
inspect →
Attribution is not the same as permission. This drawer separates discovery metadata, excerpts, WeSearch-generated summaries, reuse status, and whether the publisher receives the visit. Nothing here claims a legal grant the publisher has not made.
Record
| Original publisher | Towards Data Science |
| Canonical URL | https://towardsdatascience.com/how-much-does-a-local-llm-actually-cost-to-run-i-measured-every-watt-on-apple-silicon/ |
| Publication time | Tue, 28 Jul 2026 16:30:00 +0000 |
| Retrieval time | 2026-07-28T16:35:32.170Z |
| Last seen | 2026-07-28T16:35:32.170Z |
| Headline source | Publisher (no WeSearch rewrite) |
| Excerpt source | publisher body |
| Excerpt method | First ~120 words (~800 chars) of extracted publisher body, fair-use limited. |
| Summary | WeSearch · cerebras-chat (WeSearch summarizer) |
| Summary source text | contentText |
| Citation coverage | Summary is a WeSearch-generated derivative; primary citation is the original publisher URL. |
| Cluster | q6HQhiQw-CFG · 1 stories |
| Cluster logic | Grouped by semantic title/content similarity across sources within a rolling window. Same-publisher template collisions are excluded from coverage comparison. |
| Ranking reason | Story pages are not engagement-ranked. Hub feeds use recency, with optional source-diversified chronological ordering (cap consecutive stories per source). No personalized ranking. |
| Publisher visit | Yes — open original |
| Substitutes article? | No — link-out required for full text |
Rights status (four layers)
WeSearch handling by dimension
| Indexing | May the item be indexed (stored, ranked, made findable)? | Allowed |
| Snippet | May a short excerpt of the publisher's text be shown? | Allowed |
| AI summary | May WeSearch generate its own short summary of the article? | Limited |
| Retrieval / RAG | May the content be exposed for third-party retrieval-augmented generation? | Not asserted |
| Model training | May the content be used to train AI models? | Not asserted |
| Commercial reuse | May the content be reused commercially? | Not permitted |
Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
Opening excerpt (first ~120 words) tap to expand
Large Language Models How Much Does a Local LLM Actually Cost to Run? I Measured Every Watt on Apple Silicon Five models, sustained generation, real wall-socket energy at $0.31/kWh — and the surprise the RTX-3090 numbers predicted, only bigger. Justin Stewart Jul 28, 2026 12 min read Share The folk wisdom about running LLMs on your own hardware is that it’s free. You bought the machine, the electricity is a rounding error, and every token after that is gravy. A recent Towards Data Science piece, How Much Does It Actually Cost to Run a Local LLM?, put a number on that gravy by sampling the power draw of an RTX 3090 and pricing it against a real electricity tariff. Its finding stuck with me: the most expensive model to run wasn’t the biggest one.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at Towards Data Science.
Discussion
0 commentsMore from Towards Data Science
