实测：Jev 在重排任务上跑赢 Voyage 专用重排模型

search founder @n0riskn0r3ward原推发布于 2026.09.20

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There's a fun mix of excitement and cope on my timeline re-Jev: - OMG I made Jev a year ago this is dumb - You can fine tune this encoder into a better, faster, local classifier, etc Re the "just train your own small classifier" crew - Voyage trains great, SOTA pointwise rerankers that are obviously specialized to the reranking task and have been at it for years, likely also using a strong synthetic data recipe... Exact setup in the response tweet. Do note that using Jev is definitely more expensive than using Voyage rerank-3 bc of the tokens in the lengthy rubric included in every request (though you could definitely optimize this further) Jev is interesting to me bc I didn't expect it to be able to outperform domain specific models like these rerankers. Every other OpenJev etc type model I've benchmarked gets ~15% agreement at 20 on this eval. It's almost like it would be tough to perfect the data recipe to train a general classifier 🤔