I cut cost and latency on my search engine with Jev [D]
The developer of indiedex.gg, a game search engine, significantly improved its performance and cost-efficiency by integrating Jev. This hybrid setup reduced the search engine's end-to-end route time by approximately half, from 2871ms to about 1.5s for DeepSeek Jev Extract p50, and cut costs by roughly six times, from ~$0.014. Despite these improvements, the quality of search results, including title-resolve and hard-filter agreement, was maintained on their fixture set.
时间与来源
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发布当时偏移：UTC+02026年9月30日 01:55 UTC
收录当时偏移：UTC+02026年9月30日 07:00 UTC
- 发布
- 2026年9月30日 01:55
- 收录
- 2026年9月30日 07:00
- 来源类型
- 开发者社区
- 档位
- 社区
- 信源状态
- 正常
档位是按信源手工设定的编辑判断，不是逐条打分。
I built indiedex.gg, a hidden-gems game search engine on steam data. Search is the front door: type something like “a game like Hades that feels cozier and is co-op,” and it should actually understand that mix of reference + vibe + filters.
Those compound queries used to go through a DeepSeek extraction call that turned the sentence into structured pieces (reference game, filters, tags, vibe). It worked, but it was slow and expensive on the hot path.
I swapped that step to TypeSafe Jev on OpenRouter’s Decisions API. Jev doesn’t write a free-form answer. It answers a fixed set of closed questions in parallel (yes/no odds, choices), and I compose that with my existing regex helpers into the same extraction shape I already had. Same search pipeline after that, just much faster routing.
Bakeoff on 50 cases:
DeepSeek Jev Extract p50 ~1.5s Full route p50 2871ms Weird title-resolve 96–100% Hard-filter agree — Weird top-N overlap — Cost (fixture) ~$0.014 So extract got roughly 10× faster, end-to-end route roughly halved, cost dropped a lot (around 6x), and quality held on my fixture set.
If you’ve been building “NL in → structured intent out → tools do the work” instead of a chatbot, this pattern felt like a better fit than another chat completion.
I think models like Jev will open the doors to a lot of cool UX features, decision engines, smart filtering, auto moderation and different ways to interface with apps and machines.
Happy to answer questions about the hybrid setup.