X post · by Albiona Hoti
One prompt, 100 images from Cosmos, NASA and The Met.
Albiona Hoti
@albicodes
I built a visual reference finder with Jev One single prompt → 100 images from Cosmos, NASA, and The Met my new rabbit hole for creative work 🌻
Sep 17, 2026 · 530 likesOpen on X
Albiona Hoti built a visual reference finder with Jev. One prompt returns 100 images from Cosmos, NASA and The Met, for creative work.
Open the source
Ian Nuttall
@iannuttall
Cloudflare Workers has Jev now so I'm putting it to the test on keep.md - 7x faster search rerank compared to the current hybrid - 50x faster tagging of content vs GLM 4.7 Flash with no failures
生ビール
@wmoto_ai
ローカルTypesafe Jev、できたんやないか？ もうちょい速度は改善余地ありそう
X postResearch and data
Hassan
@nutlope
I used Jev to classify 1,018 AI research papers. The result: $0.08 total cost and 256ms median end-to-end latency per paper. The pipeline was: 1. Summarize each paper with DeepSeek V4 Flash 2. Send the title + summary + 24 possible topics to Jev 3. Use Jev to classify each paper 4. Visualize everything on http://1kpapers.com The summaries cost $3.99 on @togethercompute. The classifications cost $0.08 on @typesafeai. So for just over $4 of inference, I ended up with a pretty useful way to explore the top AI research papers from the past year. I think this is where things are heading: different models for different parts of the workflow, instead of using one model for everything. I’m running evals on the Jev classifications before replacing the current ones, but the site is already live: http://1kpapers.com
