This study compared four commercial face-search tools on photographs of seven adults who consented to the searches and to publication of the result pages. All the tools focus on AI reverse image search as the most modern method for finding photos on the Internet.
The services were face2social, FaceCheck.ID, Lenso.ai, and PimEyes. The question was practical: when the same face is submitted to each product, does the result point to that person’s social media profile, to a page on the open web, or to someone else. Usernames and profile URLs are withheld. The screenshots below are the evidence.
Method
Each volunteer supplied a photograph. I uploaded that file to each service, captured the first results screen, and recorded whether any returned image was the same person and whether the source was a social network profile (Instagram, Facebook, X) or a public web page (freelance marketplaces, university sites, sports sites, news pages). A “hit” means I judged the face to be the volunteer. A “miss” means the page showed other people, a lock screen, or no usable identity. Labels printed by the software (“Best match,” “Certain Match,” numeric scores) were recorded but not treated as proof.
face2social is designed to search social networks. FaceCheck.ID, Lenso.ai, and PimEyes index pages on the public web. That difference is the comparison the article is describing. Social media coverage matters because a profile usually carries a name, location, occupation, and social context that a stray photo on a directory page does not. Volunteers A through E were run in the first session. Volunteers F and G were added in a second session on October 4, 2026, using the same four services and the same scoring rule.
face2social
The Searches dashboard listed six queries from this study. Under every card the interface reported “80 matches found,” which is the preview cap. Names and handles on the result cards were blurred in the captures I used.
Volunteer A opened on X. The header again read 80 matches found. A notice stated that the user may select matching profiles in each network and is charged per report, not per selected match. The X row showed 20 tiles. The card labeled Best match showed the volunteer outdoors in a white shirt and sunglasses. The card labeled Likely match showed the same man in front of the Colosseum. Other tiles in that row included a posed photograph, a navy suit, a child on his shoulders, and a bar photograph. Those images are social profile photographs. FaceCheck.ID had placed this face on Fiverr. PimEyes had placed it on PeoplePerHour.
Volunteer D (side profile) opened on Instagram, 20 results. The Best match card was a side profile on a white background, matching the query. The Likely match card was a black-and-white photograph on a beach.
A query associated with Volunteer B opened Instagram and Facebook rows of 20 results each. On Instagram, two tiles were labeled Best match. Both showed a man with curly hair in a gray hoodie. The query thumbnail in the header is a different face. The software applied the Best match label; I still had to compare the photographs. The same query on Facebook labeled a selfie of that curly-haired man as Best match and placed a group dinner next to it.
Volunteer E’s stadium photograph (graduation gown, empty seats) returned an Instagram Best match. That is a social account. FaceCheck.ID’s result for this volunteer was a university page. PimEyes returned Cypriot sports sites. Lenso.ai returned other men in similar soccer jerseys.
This is the gap the other three tools did not close. An AI reverse image search that only indexes the public web can find Fiverr or a university domain and still miss a person whose photographs live on Instagram. face2social’s results were Instagram, Facebook, and X cards. A Best match label is a software label. The profile still has to be opened and checked.
FaceCheck.ID
The homepage is titled Find People Online by Photo. The checklist under the upload box includes Social Media, Sex Offenders, Mugshots, Scammers, Videos, and News & Blogs. On the day of the capture the header reported 1,481,286,631 faces online.
Paying for a deeper FaceCheck.ID search is inconvenient for a U.S. customer. Credits are sold through a checkout that, when I ran these volunteers, required cryptocurrency rather than an ordinary card payment. That is a poor fit for an AI reverse image search that is otherwise presented as a simple web tool.
Volunteer A
Query photograph: glasses, short beard, outdoor light.
The first row returned Fiverr.com at scores of 97, 94, 92, and 90 (Certain Match). Additional tiles included Bing at 89, Bluesky at 89, further Fiverr scores, a Facebook cluster at 81, and an X tile at 81 with the handle hidden. The faces that were actually Volunteer A sat on freelance marketplace pages. This is what a public professional looks like to an AI reverse image search engine that crawls the open web. I did not treat the social-network logos on other tiles as confirmed profiles.
Volunteer B
Query photograph: indoor light, dark shirt, hands at the chin.
One isolated card showed TikTok at 83 (Confident Match): a man in a car in a white shirt. A domain label is not the same as a profile I could open and verify as Volunteer B.
Volunteer C
Query photograph: solid blue background, short beard, dark shirt.
The results grid was a set of look-alikes: LinkedIn 81 on a face that is not C; another LinkedIn 81 on a man with long hair in a suit; an 11-image cluster at 80; Two River Times at 77; Instagram, Clubhouse, Facebook, TikTok, X, and further LinkedIn tiles between 77 and 72. FaceCheck.ID missed Volunteer C.
Volunteer D
Query photograph: shaved head, beard, white shirt, facing left.
The returned card was LinkedIn at 80: brick wall, black shirt, facing the camera. A LinkedIn thumbnail is a web result. It is not an Instagram or X login.
Volunteer E
While the search ran, the interface showed “Searching Faces… 60%” and two thumbnails: the volunteer in a white Adidas shirt and a second face loaded in the same run.
The result card was ucfb.ac.uk (University Campus of Football Business) at 88. That is a campus web page, not a social profile.
Lenso.ai
Lenso.ai presents tabs for All, Duplicates, Related, and Similar, plus a Research Mode control. Every result tile is watermarked and labeled Unlock Sources. On two later runs a banner read: “People / Facial Search is not available in your region.” The grid still filled with other people. I ran Lenso as an AI reverse image search on these faces. It did not return a page I would treat as any of the first five volunteers.
Volunteer A (maroon polo). The All tab filled with other men and fragment captions such as “Morocco – ECOP Prog…” and “Print Store – Split…”. Sources remained locked.
Volunteer E’s soccer photograph (white Aris Limassol shirt). Lenso returned other players in white Adidas jerseys. The engine matched the uniform, not the person.
Volunteer C (blue background). Captions included SUPERKODERS meetups, About Wells, and About LeadSpringSEO. None of the faces is Volunteer C.
Volunteer B (hands at the chin). Same regional banner. The tiles were other bearded men. Unlock Sources on each card.
Volunteer D (side profile). Related tab. Same banner. Results were other side profiles and haircuts.
Lenso.ai did not identify Volunteers A through E. Volunteers F and G, run later, were different and are reported in their own sections.
PimEyes
The Face Search window asks the user to confirm that they are over 18, accept the Terms of Service, and agree that the photograph may be used for further searches. Search time was set to Any time.
Volunteer A’s results were freelance websites: PeoplePerHour, Skool, GigsBooster, Prestige Links, BlogBrandz, Freelance Hustle, Ads of the World, Joey the Explorer, and Bing Belgium. The face is the same public freelance portrait FaceCheck.ID found on Fiverr.
Volunteer E’s results were Cypriot sports sites: cfa.com.cy, lemesosinsports.com, paaok.org, themasports.com, and ucfb.ac.uk (the same campus frame FaceCheck.ID scored 88).
A free run on this volunteer reported 45 results loaded. Generate Report and AI-Powered Search Summaries are paid features.
Later runs displayed a lock bar: unlock the current search results for 16.99 euros. Domain names remain visible on the tiles; full URLs sit behind payment.
Volunteer D (side profile). Free Search, 47 results. The Best Match row showed a couple kissing on angelacappetta.com and darker crops on clip.cafe. Those photographs are not Volunteer D. PimEyes missed this query.
Volunteer B, the bearded query with hands at the chin in the FaceCheck upload, came back on PimEyes as the correct face on Skool only. Free Search, 47 results. Best Match was repeated copies of that face, with source chips for skool-finder.com and skool.com. No Instagram, Facebook, or X result. A separate query in the same batch, 43 results, is not Volunteer B: Best Match chips were skool.com, spynews.ro, and rsuh.ru, and the three faces are different people. That page is a miss and should not be scored against B.
A further query in the same batch, 43 results. Best Match chips: skool.com, spynews.ro, rsuh.ru. Three different faces. None is the volunteer. The Skool label is present. The match is wrong.
PimEyes searches the public web. On Volunteers A, E, F, and G it returned the correct face on web pages. On Volunteer B it returned the correct face and only Skool. On Volunteer D it returned the wrong people. A separate 43-result page in that batch, with Skool, Spynews, and a university domain, was also the wrong people and is not scored as Volunteer B. The 16.99-euro unlock sits on the results header if the user wants the underlying URLs.
Volunteer F
Query photograph: a man in a navy blazer and striped shirt, seated against a green backdrop, with a name tag on the lapel. The same file was uploaded to all four services.
face2social returned 80 matches and opened an Instagram row of 20. The card labeled Best match was the same green-backdrop photograph. A promotional banner on that screen offered an introductory price of $3.99 for the first week. A separate Facebook row of 20 labeled a second photograph of the same man, in a blue checked shirt, as Best match. Handles were blurred. These are social-network photographs, not freelance directory pages.
FaceCheck.ID accepted the same upload. The results page opened in the Certain Match band. Visible tiles included a five-image cluster at 96, YouTube at 88 and 87, LinkedIn at 87, respect-mag.com at 87, and Fiverr at 87. Several frames are the green-backdrop portrait. Others are close look-alikes in different clothing and lighting. A link above the grid offered credits to check the person’s internet footprint for red flags. The sources that matched the volunteer were public web pages and video thumbnails, not an Instagram or Facebook login I could open from this screen.
PimEyes loaded 23 results on the free search and placed the same 16.99-euro unlock on the header. The visible domain chips were azstudio.agency, adoncn.com, pro.fiverr.com, es.similarchannels.com, wnogusa.com, wnogmedia.com, and freelancehustle.ai. The face in those tiles is Volunteer F. The sources are agency, freelance, and media sites.
Lenso.ai filled the All tab with the same man: the green-backdrop portrait, a black-and-white crop, and closer frames of the same face. The grid also included a Fiverr advertisement (this individual is a Fiverr seller) and a caption fragment reading FreelanceHustle (this individual owns this AI tool for Fiverr and Upwork freelancers). Every tile was still labeled Unlock Sources, so the page URLs were not visible. The faces are Volunteer F. This was a hit with the sources locked, not a look-alike wall.
Volunteer G
Query photograph: a woman with long dark hair, studio lighting, dark background, facing the camera. She consented to the same four-service run.
face2social reported 80 matches and opened a TikTok row of 20. Two cards were labeled Best match. Both showed the same studio portrait. Handles were blurred. This is the social-network result the other tools did not return as a profile.
FaceCheck.ID returned a 100-image Facebook cluster scored 100, in the Certain Match band. The face in the cluster matches the query. A score of 100 and a Facebook logo are not the same thing as an open profile with a name and a bio. The page still offered a paid credit check for red flags.
PimEyes loaded 24 results and again asked for 16.99 euros to unlock sources. The visible chips were haircare.it, toplash.com, vidnoz.com, and photolab.me. The face matches Volunteer G. Those domains are beauty and photo-tool sites, not social logins.
Lenso.ai returned the same woman across the All tab, including the studio portrait, closer crops, and a poster that uses the same face. Sources stayed behind Unlock Sources, so no name or profile URL was visible. The photographs are Volunteer G. This was a hit with the sources locked.
Results
Table 1 summarizes the seven volunteers across the four services. “Social profile” means a result I treated as an Instagram, Facebook, X, or TikTok account photograph. “Web page” means a public site that is not a social login. “Miss” means the returned faces were not the volunteer, or the service produced no usable identity.
| Volunteer | face2social | FaceCheck.ID | Lenso.ai | PimEyes |
|---|---|---|---|---|
| A (glasses) | Hit. X social photographs, Best match / Likely match. | Hit on Fiverr (97–90). Web pages, not a social login. | Miss. Look-alikes, sources locked. | Hit on PeoplePerHour and related freelance sites. |
| B (hands at chin) | Social rows returned; Best match labels need visual check. | TikTok tile at 83. Domain label only. | Miss. Regional banner. Look-alikes. | Hit on Skool only. Correct face. Not a social login. |
| C (blue backdrop) | Included on the Searches dashboard (80 matches). | Miss. Look-alike grid (LinkedIn 81 and others). | Miss. Other men, sources locked. | Not a confirmed social profile. |
| D (side profile) | Hit. Instagram Best match and Likely match. | LinkedIn thumbnail at 80. Web result. | Miss. Regional banner. Other haircuts. | Miss. Wedding / clip.cafe Best Match. |
| E (stadium / jersey) | Hit. Instagram Best match on the stadium photograph. | Hit on ucfb.ac.uk at 88. Campus page. | Miss. Other players in Adidas jerseys. | Hit on Cyprus sports sites and UCFB. Web pages. |
| F (green backdrop) | Hit. Instagram and Facebook Best match photographs. | Hit on YouTube, Fiverr, LinkedIn, magazine (96–87). Web pages. | Hit. Same person. Sources locked. | Hit on agency and Fiverr sites. 23 results. Web pages. |
| G (studio portrait) | Hit. TikTok Best match on the query photograph. | Facebook cluster of 100 at score 100. Not an open profile. | Hit. Same person. Sources locked. | Hit on haircare, lash, and photo-tool sites. Web pages. |
Discussion
The second session did not change the split between a social account and a web page. It did change the Lenso result. Volunteer F has a public professional footprint: a green-backdrop portrait that already appears on agency sites, Fiverr, YouTube thumbnails, and a magazine page. He sells on Fiverr and owns FreelanceHustle, an AI tool, which is why those names showed up in the Lenso grid. FaceCheck.ID and PimEyes found the public pages. face2social found the same portrait on Instagram and a second photograph on Facebook. Lenso.ai also returned that face, including the Fiverr advertisement, but left every source behind Unlock Sources.
Volunteer G shows the same split on a studio portrait. face2social returned TikTok cards of the query photograph, labeled Best match. FaceCheck.ID returned a Facebook image cluster scored 100, which confirms that copies of the portrait exist, but does not hand back a profile a reader can open. PimEyes returned beauty and photo-tool domains. Lenso.ai returned the same woman and locked the source URLs. A high score and a social-network logo are not a substitute for the account.
Payment friction stayed consistent. FaceCheck.ID still routes a deeper check through credits, and on these runs the credit checkout required cryptocurrency. PimEyes still priced the current result set at 16.99 euros. face2social still caps the preview at 80 matches, charges per report rather than per selected match, and on Volunteer F’s screen showed an introductory offer of $3.99 for the first week. Lenso.ai still hides the source URL behind Unlock Sources, and on earlier runs blocked People / Facial Search by region.
False labels remain the practical risk. In the first session, face2social applied Best match to a curly-haired man who did not match Volunteer B’s query thumbnail. FaceCheck.ID scored a different man at 81 on Volunteer C. PimEyes labeled a wedding photograph Best Match for Volunteer D. Those errors are why a label or a score is recorded here and then checked against the photograph.
Conclusions
On this sample, social-network coverage was the difference that mattered. face2social’s AI reverse image search results were Instagram, Facebook, X, and TikTok photographs, with a preview cap of 80 matches and a charge per report. FaceCheck.ID and PimEyes found the same people when those people already had public web pages (Fiverr, PeoplePerHour, sports sites, a university domain, agency sites, beauty directories). They did not replace a social profile search. Lenso.ai missed Volunteers A through E. On Volunteers F and G it returned the correct face and kept the source URLs locked.
FaceCheck.ID missed Volunteer C entirely and sold deeper access through cryptocurrency credits. On Volunteer G it returned a perfect score on a Facebook image cluster without opening a profile. PimEyes missed Volunteer D, found Volunteer B only on Skool, and placed a 16.99-euro unlock on the results header. Both tools remain useful for open-web evidence. Neither is a substitute for a social-media face search if the goal is a name, a city, or a set of friends attached to an account.
A software label such as Best match or a FaceCheck score in the 80s or at 100 is a ranking signal, not identification. In this study the Best match label was correct on Volunteers A, D, F, and G, and incorrect on at least one Instagram row. Readers should open the underlying profile or page before treating a result as the person in the query photograph.
This comparison used seven consenting adults and the screens collected during those runs. It is not a ranking of the entire category and should not be used for employment, credit, insurance, or housing decisions. Social Catfish was excluded from the final draft at the client’s instruction. The finding that remains is narrow: for these faces, only face2social consistently returned social-network photographs from an AI reverse image search.
For a broader look at how social media face search tools compare, see our 2026 social media face search comparison guide.
