VectorTrace vs vectorizer.ai

Both trace raster images into vector paths. The structural difference is where the tracing happens — their server, or your tab — and everything else follows from that.

Public web app and API, as documented on their sitevectorizer.ai 방문
제품
vectorizer.ai
확인일
2026-08-26
규칙
출처와 날짜 명시
가격
무료 미리보기
01

나란히 비교

행 5개 · 각각 출처와 날짜 명시
나란히 비교vectortracevectorizer.ai
Where the image is processedThe image is traced by WebAssembly in a Web Worker in your own tab. It is never uploaded, so there is nothing to store, delete or leak.A hosted service: the image is sent to their servers, traced there, and the result returned. Their site describes the API and the web app in those terms.출처 · 확인일 2026-08-26
Works offlineYes, once the page has loaded. The engine is a WebAssembly module in the tab, not a request.No — a server-side tracer needs the network by definition.출처 · 확인일 2026-08-26
Output formatsSVG, PDF, EPS and DXF, all written by the same Rust exporters from one document.Multiple vector formats, listed on their site. Check the current list there rather than here — ours would go stale and theirs is authoritative.출처 · 확인일 2026-08-26
Pricing modelPreviews are free and unlimited. Downloads need Pro at €9.00 per month or €69.00 per year, tax inclusive.Credit-based, per their pricing page. We do not restate a competitor price: it changes without telling us, and a stale number is worse than a link.출처 · 확인일 2026-08-26
Public APIPOST /api/v1/vectorize, documented with a generated OpenAPI 3.1 document at /api/openapi.json.An HTTP API is documented on their site.출처 · 확인일 2026-08-26
02

알아두면 좋은 점

vectorizer.ai is a hosted service: you upload an image, their machines trace it, and you download the result. That design buys them a straightforward path to heavy models and a lot of server-side compute, and it costs you the upload.

VectorTrace runs the engine as WebAssembly in your browser. That costs us the ability to throw a large GPU model at the problem and buys you a product that works offline, has no queue, and never holds your artwork. Which trade is right depends on whether the file is yours to send.

We have not published a quality comparison, because we have not run one that meets our own standard (D13). Our own figures on the committed corpus are published — boundary error, region count and node ratio, with the date and the engine version attached — and the row below points at them. Theirs are absent because we have not measured them, not because they lost.

03

아직 측정하지 않은 것

미확인 질문 3개
  1. Which produces fewer nodes for the same boundary accuracy on YOUR artwork? Trace the same file in both and compare the node count your editor reports.
  2. How does each handle the anti-aliased edge of a small logo? Zoom both results to 800% and look at where the boundary sits relative to the original pixels.
  3. Does their licence permit the use you have in mind for the output? Read their terms; ours are at /legal/terms.
04

벤치마크

수치와 날짜, 버전이 없는 주장은 하지 않습니다.
smoke (30 fixtures) · 2026-09-05 · 0.3.34

마케팅이 아니라 측정입니다. 코퍼스, 방법론, 그리고 실행이 만들어낸 모든 수치를 빠짐없이 게시합니다.

방법론/benchmarks
boundary error, p95
0.09 px
region-count error
0.000
node-count ratio
1.00×
05

vectortrace를 선택하는 이유

주장 3개 · 고정된 순서
06

질문

질문 3개
01Is VectorTrace better than vectorizer.ai?
We have not measured their output, so we are not going to claim it. Our own numbers on the committed corpus are on /benchmarks, dated and versioned; theirs are not, and a comparison needs both. What we can state is structural: our tracing runs in your browser and theirs runs on their servers. Trace the same file in both and judge the output yourself.
02Why does the in-browser difference matter?
Because an unreleased brand mark, a client file under NDA or a medical scan should not travel to a third party to be traced. If your file is not sensitive, the difference is convenience: no upload wait, no queue, and it works on a plane.
03When will there be actual benchmark numbers on this page?
Ours are there now: boundary error, region count and node ratio on the committed smoke set, each with the date and the engine version. A head-to-head needs their output under terms that clearly permit publishing it, which is a decision about their licence rather than about our harness.
07

관련

링크 5개