Sauce Finder
The reverse image search Apple should have shipped
Sauce Finder launched on May 18, 2026 with 8 votes, #1,430 of 20,538 launches that month and more than 90% of that year's launches.
What it does
Stop screenshotting and opening 4 browser tabs to source an image. Sauce Finder runs any image through Google Lens, SauceNAO, TinEye, and Yandex with a single share-sheet tap. Live Activity progress. Search history. iPhone + iPad. Free to try.
Reverse image search across Google Lens, SauceNAO, TinEye, and Yandex — in one native iOS app. No accounts, no tracking, images auto-delete after 10 minutes.
A precise, system-native reverse image search. One tap, four engines, zero noise. Built for collectors, designers, and the relentlessly curious. Drop any image, screenshot, or photo. Get matches in under a second. Google Lens, SauceNAO, TinEye, and Yandex — switch with a floating monospace toggle. List-based archive grouped by date with high-contrast thumbnails. WKWebView-integrated results render instantly without leaving the app. Images auto-delete from our temporary host after 10 minutes. No accounts, no tracking. Sticky help icon on every screen. No tutorials, no friction. Sauce Finder integrates with the iOS Share Sheet. See an image in Safari, Photos, Messages, or Twitter? Share →…from saucefinder.app
Does a similar job
all alternatives →
Reverse Image Search ToolsDec 2025 · chromewebstore.google.com · ▲5Search by image on Google, Bing, Yandex & TinEye instantly
TinEye Reverse Img Search2014 · chromewebstore.google.com · ▲101Find out where an image came from & how it's used.




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Source: Product Hunt launch ↗
Launched alongside, May 2026
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Hey HN, Henry here from Cactus. We open-sourced Needle, a 26M parameter function-calling (tool use) model. It runs at 6000 tok/s prefill and 1200 tok/s decode on consumer devices. We were always frustrated by the little effort made towards building agentic models that run on budget phones, so we conducted investigations that led to an observation: agentic experiences are built upon tool calling, and massive models are overkill for it. Tool calling is fundamentally retrieval-and-assembly (match query to tool name, extract argument values, emit JSON), not reasoning. Cross-attention…
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