Lingua Detective vs fastText: text-classification model vs managed language audit
Verdict: If you're building a data pipeline and need to classify large volumes of text by language offline, fastText's lid.176 model is free, fast, and proven — use it directly. If what you actually need is to know whether a multilingual website serves the right language on every page, you need crawling, JS rendering, and per-page verdicts wrapped around that kind of model — which is what Lingua Detective provides.
| fastText | Lingua Detective | |
|---|---|---|
| What it is | Meta's open-source text classifier; the lid.176 model does language identification | Managed service that crawls a site and audits every page's actual language |
| Setup | Install the library, download and load the ~126MB lid.176 model, call it from Python/C++ | Give it a URL or a list of URLs — no model to download, no code |
| Pricing | Free, no account | Free trial (20 pages, no account/card); then $0.015→$0.010→$0.006/page, +$0.005/page if it crawls for you; or pay-per-call API from $0.002 |
| Privacy / offline | Fully offline — runs on your own machine once the model is loaded | Offline detection engine by default; uncertain pages can optionally go to AI arbitration |
| Output | A language label and confidence score for a string you supply | A per-page verdict — Conforming, Non-conforming, Uncertain, Error, or Undetermined — plus a site report |
| Best for | Data/ML teams classifying large text corpora in a pipeline they control | Teams that need an auditable view of a whole multilingual site, not a batch classification job |
Pick fastText if…
- You're building or running a data pipeline (Python/C++) and want a proven, offline classifier for bulk text.
- You can afford to host and load a ~126MB model as part of your own infrastructure.
- You're classifying text you already have, not crawling and rendering live web pages.
- You're comfortable that the library is mature and stable but sees little active development — that's fine for a well-understood task like language ID.
- You want zero licensing cost and full control over batching, hardware, and integration.
Pick Lingua Detective if…
- You need per-page verdicts across a real, possibly JavaScript-rendered website, not a classification call on text you've already extracted.
- You don't want to host, load, and update a ~126MB model, or build the crawler and renderer that would feed it real page content.
- You want a report and scheduled audits an SEO or compliance team can use directly, not a raw label and score.
- Borderline pages should get a smarter second look — Lingua Detective's optional AI arbitration handles that instead of a fixed confidence threshold.
- You'd rather pay per page than build and maintain a classification pipeline yourself.
Pricing math
Auditing a 500-page site with URLs supplied: 200 pages at $0.015 ($3.00) plus 300 pages at $0.010 ($3.00) comes to $6.00 total. If Lingua Detective needs to crawl the site itself, add $0.005/page (+$2.50) for $8.50. The fastText model itself costs nothing to download, but hosting it, keeping it warm, and building the crawler and renderer around it is real engineering time that a price tag of zero doesn't capture.
FAQ
Q: Is fastText still maintained?
It's stable and widely used, but sees little active development now — that's fine for language ID, a task that hasn't needed to change much.
Q: Does Lingua Detective use fastText internally?
Lingua Detective runs its own offline detection engine, comparable in spirit to models like fastText's, plus crawling, rendering, and per-page verdicts.
Q: Why is fastText's model 126MB?
lid.176 embeds representations for 176 languages in one file — the tradeoff for broad, offline coverage without calling an external service.