Running Kimi K3 on a M1 Mac
It is not fast — about 16 seconds per token on our M1 Max — but it is exact, reproducible, and it works on a 64 GB laptop. Newer chips and more RAM make it faster automatically. Install Three commands, then you're generating.
- ▪It is not fast — about 16 seconds per token on our M1 Max — but it is exact, reproducible, and it works on a 64 GB laptop.
- ▪Newer chips and more RAM make it faster automatically.
- ▪Install Three commands, then you're generating.
Hacker News (Front Page) files mainly under programming. We currently carry 797 of its stories. Top-voted stories on Hacker News.
Story provenance
Source · retrieval · rights · ranking — open for full record
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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 | GitHub |
| Canonical URL | https://github.com/gavamedia/deltafin |
| Publication time | Tue, 28 Jul 2026 21:35:19 +0000 |
| Retrieval time | 2026-07-28T22:16:28.586Z |
| Last seen | 2026-07-28T22:16:28.586Z |
| 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 | _nml-Vl9BRxW · 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
____ _ _ __ _ | _ \ ___| | |_ __ _ / _(_)_ __ | | | |/ _ \ | __/ _` | |_| | '_ \ | |_| | __/ | || (_| | _| | | | | |____/ \___|_|\__\__,_|_| |_|_| |_| An experiment in running Kimi K3 (2.8T parameters) on one Apple Silicon Mac Deltafin is a small research project that runs a Mixture-of-Experts model far larger than the machine it sits on. It is not fast — about 16 seconds per token on our M1 Max — but it is exact, reproducible, and it works on a 64 GB laptop. Newer chips and more RAM make it faster automatically. Install Three commands, then you're generating. The only real decision is step 3. # 1.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at GitHub.