Show HN: Sunk Cost – How long until a local LLM rig pays for itself?
The article introduces a tool designed to calculate the break-even point for local LLM hardware compared to API usage. It allows users to customize variables such as daily token volume, context window size, and electricity costs to determine financial viability. The calculation method relies on specific assumptions regarding API price trends and local processing speeds derived from memory bandwidth.
- ▪The tool estimates when a local LLM rig will pay for itself by comparing it against API costs.
- ▪Users can adjust inputs like electricity rates, API speed, and the ratio of input to output tokens.
- ▪Local processing speed is estimated using memory bandwidth divided by bytes read per token.
- ▪The model assumes that API prices will continue to fall over time.
- ▪API speed primarily affects the time comparison rather than the direct cost calculation.
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Story provenance
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 | Sunk Cost |
| Canonical URL | https://sunkcost.ai/ |
| Publication time | Tue, 15 Sep 2026 01:37:43 +0000 |
| Retrieval time | 2026-09-15T01:51:52.656Z |
| Last seen | 2026-09-15T01:51:52.656Z |
| 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 | QUsme--QdJ3V · 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
The break-even Copy link Download card Post on X How you’d use it Mostly for Tokens a day Context window you want Custom input to output ratio Assumptions you can change Electricity, $/kWh API speed, tok/s Assume API prices keep falling How fast they fall Where nothing has been measured, local speed is estimated as memory bandwidth ÷ bytes read per token × , and labelled as such. API speed only affects the time comparison. How this is calculated The small print that isn't small
Excerpt limited to ~120 words for fair-use compliance. The full article is at Sunk Cost.
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