Show HN: Jevstiller – Distill Jev into a local model, with a disagreement bound
A local model that answers like Jev 98% of the time, and how we know September 2026. Every number here is from the benchmarks, and bash experiments/bench.sh --no-record reruns them without an API key. If you classify text with Jev, every answer is a network call to one vendor and comes back in about 300 ms, at any load.
- ▪A local model that answers like Jev 98% of the time, and how we know September 2026.
- ▪Every number here is from the benchmarks, and bash experiments/bench.sh --no-record reruns them without an API key.
- ▪If you classify text with Jev, every answer is a network call to one vendor and comes back in about 300 ms, at any load.
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Record
| Original publisher | Jevstiller |
| Canonical URL | https://jevstiller.pages.dev/posts/the-guarantee/ |
| Publication time | Tue, 29 Sep 2026 12:05:07 +0000 |
| Retrieval time | 2026-09-29T14:41:38.660Z |
| Last seen | 2026-09-29T14:41:38.660Z |
| 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 | 5SvisyUJ-ZSt · 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
A local model that answers like Jev 98% of the time, and how we know September 2026. Every number here is from the benchmarks, and bash experiments/bench.sh --no-record reruns them without an API key. If you classify text with Jev, every answer is a network call to one vendor and comes back in about 300 ms, at any load. For a batch job that is fine. For an agent loop that decides, acts, and decides again, or a game tick, or anything that classifies then acts, 300 ms per step is the whole budget. Jevstiller sits in front of that call, learns a small local model from Jev’s own answers, and lets it answer what it is sure about in about 15 ms on a CPU. The interesting part is not the small model. It is the contract: Set one number, say 98%.
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Excerpt limited to ~120 words for fair-use compliance. The full article is at Jevstiller.
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