Jev sparks debate: training your own classifier won't beat Voyage's years of reranker tuning
zainhas · x · 2026-09-21
zainhas highlights buzz around the new Jev model. The quoted discussion notes mixed reactions: some want to fine-tune it into a fast local classifier, others argue you can just train your own small one. The author counters that Voyage has spent years building SOTA pointwise rerankers with likely strong synthetic-data recipes — not easily replicated. Still, Jev's lengthy per-request rubric makes it pricier than Voyage rerank-3, though optimizable.
More from Models
- Solving Sudoku with graph coloring: an Astra demo worth a look — mariyaivasileva · 2026-09-21
- Freebuff's $8/Month Ad-Supported Coding Sub Promises 15 Hours of DeepSeek Daily — gaganghotra_ · 2026-09-21
- The Illustrated Recurrence: From Amari-Hopfield Nets to GPT-6 Astra — gklambauer · 2026-09-21
- Unverified claim: Grok 4.7 launching today with 500K context, multimodal, 4.6-level pricing — realsohamparekh · 2026-09-21
- Dev warns: if token subsidies end, 24/7 agent use gets priced out alongside local — BLUECOW009 · 2026-09-21
- Simulated test: GPT-6 Astra pushed a virtual person off a ledge in multiple trials, rivals didn't — paul_cal · 2026-09-21