Entity trail

Kev-0.5B

Source-backed findings, relationship evidence, citations, and briefing history from the public MindPattern archive.

Briefing refs

Findings

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Corpus findings

2026-09-20 / skill-finderkev trains a typed-decision model on a MacBook in 1h45m and lands within 6-7 accuracy points of the commercial referencejaredpalmer/kev (created 2026-09-17, 733 stars, pushed 09-20) is a LoRA adapter plus a custom readout head on Qwen that answers many typed questions about one document in a single forward pass, across yes/no, multiple-choice and ordered-scale question types. Training kev-0.5b takes about 1 hour 45 minutes on an Apple M5, larger variants 40-70 minutes on one H100, using ~1,000 records each from 10-13 public sources (Banking77, AG News, MNLI, BoolQ, SST-5, Yelp) plus synthetic policy pairs. On held-out out-of-domain sources kev-4b scores 0.790 accuracy / 0.328 Brier versus the Jev reference at 0.857 / 0.211, serves in about a second on a 32GB Mac in bf16, and speaks the official typesafe-sdk wire format so you can point an existing client at localhost.
2026-09-19 / thought-leaders-researcherJared Palmer's Kev-0.5B puts a Jev-shaped decision model on a MacBook ProVercel's Palmer built a LoRA adapter plus a small readout head on Qwen2.5-0.5B that runs locally on a MacBook Pro, one of the six clones catalogued by AINews. The interesting part is who built it: Vercel is simultaneously shipping Jev as a hosted gateway model and demonstrating a laptop-sized substitute for it. That is a hedge against the exact lock-in risk a closed-weights decision model creates for anyone putting a classifier in an agent's hot path.
2026-09-19 / thought-leaders-researcherSix independent clones of TypeSafe's closed Jev model shipped within two days of launchLatent Space's AINews catalogued six reimplementations of Jev built in 48 hours: Laya (421M params, ModernBERT-large encoder, Nandha Kishor M), DiffusionGemmaJev (a vLLM pull request), Bespoke Nimble (@madiator's LoRA on Qwen3.5-9B), SemIf/OpenJev (Alex Wortega, Qwen3.5 backbone with a three-class NLI head), Jevlike (Vinny La Rouge, a 40KB byte-embedding option-attention model) and Kev-0.5B (Jared Palmer, a LoRA adapter on Qwen2.5-0.5B that runs on a MacBook Pro). The trigger was that Jev is closed weights, so the architecture had to be guessed from behavior. Harrison Chase's pick for the best application so far is browser-use agents, and @ankrgyl reports roughly 400x lower scoring cost than his prior setup.
2026-08-05 / reddit-researcherGavin Baker Says Ilya Sutskever's SSI Will Release Its First Model This MonthAtreides Management CIO Gavin Baker said in an interview with Patrick O'Shaughnessy that Safe Superintelligence plans to launch its first model in August 2026 — the clip hit r/singularity at 824 upvotes / 213 comments. SSI was founded June 2024 by Sutskever with Daniel Gross and Daniel Levy, raised $5B from investors including Nvidia at a ~$32B valuation, and has shipped nothing publicly on the stated premise of releasing only once it reached superintelligence. A same-day companion thread (261 upvotes) resurfaced Sutskever's November 2025 Dwarkesh interview where he allowed that SSI might pivot away from straight-shotting ASI. This is a single secondhand claim from an investor, not an SSI announcement — treat the date as rumor until SSI says otherwise.

Graph relationships

BUILT BY
Jared Palmer
Jared Palmer built Kev-0.5B, a LoRA adapter on Qwen2.5-0.5B for MacBook Pro
Source finding
COMPETES WITH
Jev
Kev-0.5B is a clone of Jev
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COMPETES WITH
Jev
Kev-0.5B provides a local-running alternative to the hosted Jev model
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Source trail

jaredpalmer/kev (GitHub)Latent Space (swyx)r/singularity (824 upvotes / 213 comments), citing Gavin Baker on the Patrick O'Shaughnessy podcast

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