| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Internal talent marketplace | Performance and talent management | 0% | 100 of 102 | 50% | 26 | criticized challenger | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Contingent workforce management | Workforce planning and analytics | 0% | 22 of 121 | 27% | 15 | criticized challenger | ▼−4Since September 2026: 4% → 0%, −4 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Skills intelligence | Performance and talent management | 0% | 74 of 127 | 50% | 2 | under 10 labels · led by Skills Base at 18% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Compensation management | Compensation and total rewards | 0% | 118 of 140 | 100% | 1 | under 10 labels · led by Pave at 18% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Job advertising and distribution | Talent acquisition | 0% | 46 of 111 | 0% | 1 | under 10 labels · led by JobTarget at 23% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Mentoring software | Learning and development | 0% | 63 of 77 | 100% | 1 | under 10 labels · led by Together at 28% | newNew since September 2026: not ranked then, 0% now. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Contingent workforce man | 4% | 0% | ▼−4Since September 2026: 4% → 0%, −4 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 7 → 22 of 121 |
| Internal talent marketpl | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 77 → 100 of 102 |
| Skills intelligence | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 156 → 74 of 127 |
| Compensation management | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 140 → 118 of 140 |
| Job advertising | 0% | 0% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 56 → 46 of 111 |
| Mentoring software | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 63 of 77, unchanged |
Shares here are read over the models both editions asked, so they can differ by a point or two from the standing above, which counts every model in this edition.
The floor is 13 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured · The editions
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 1 | 1 | 2 |
| GPT-5.4 mini | 0 | 1 | 1 | 1 | 3 |
| Gemini 3.5 Flash | 0 | 1 | 2 | 2 | 5 |
| Perplexity Sonar | 0 | 0 | 1 | 1 | 2 |
| Grok 4.1 Fast | 0 | 1 | 1 | 4 | 6 |
| Mistral Small | 0 | 1 | 1 | 2 | 4 |
| DeepSeek V4 Flash | 0 | 0 | 3 | 2 | 5 |
| Llama 4 Maverick | 0 | 0 | 0 | 1 | 1 |
| Qwen 3.7 Flash | 1 | 0 | 1 | 2 | 4 |
| Kimi K2 | 0 | 1 | 1 | 1 | 3 |
| GLM 4.7 FlashX | 0 | 2 | 1 | 0 | 3 |
| MiniMax M2.5 | 0 | 1 | 0 | 1 | 2 |
| GPT-6 Luna | 0 | 1 | 0 | 1 | 2 |
| Muse Glimmer 30B | 0 | 2 | 1 | 1 | 4 |
Verbatim evidence the judge attached to positive labels.
“Stick to large, well-established marketplaces (Upwork, Toptal, Fiverr, LinkedIn Jobs)” Qwen 3.7 Flash · Skills intelligence · negative prompt · first choice
“Deel/Fiverr Business are strong if you want marketplace scale with enterprise-grade onboarding and payments” Muse Glimmer 30B · Contingent workforce man · paraphrase prompt · alternative
“Fiverr Enterprise is called out as "Best for enterprise-scale freelancer engagement workflows"” Muse Glimmer 30B · Contingent workforce man · paraphrase prompt · alternative
“For creative/digital services and simplicity, Fiverr Business is a solid choice.” Mistral Small · Contingent workforce man · paraphrase prompt · alternative
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Platforms to Be Cautious About ... Fiverr ... Severe quality variability ... Fiverr's standard marketplace has the most reliability issues” DeepSeek V4 Flash · Internal talent marketpl · negative prompt · hard negative
“If your managers use Upwork or Fiverr to hire "contractors"... you are highly exposed to worker misclassification lawsuits.” Gemini 3.5 Flash · Contingent workforce man · negative prompt · hard negative
“Has a Trustpilot score of 2.5 out of 5 with 14,000 reviews, with lots of negative reviews mentioning poor customer support” Claude Haiku 4.5 · Internal talent marketpl · negative prompt · hard negative
“Fiverr, in particular, is built for quick fixed-price gigs and may have heavy IP transfer and security gaps” Mistral Small · Contingent workforce man · negative prompt · hard negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 129 of the 131 answers that named Fiverr and are not a share of its labels.
285 of the 313 domain citations in answers naming Fiverr came from somebody else's page.
Pages are listed as the models cited them.
Search figures are US estimates from DataForSEO, read September 28, 2026; AI search demand is its modeled, directional estimate, not a count of queries to any assistant. The answers are this edition's. Two measurements side by side: neither is read as the cause of the other.
| Kind | Pages | Last 90 days | 2025-10 to 2026-09 | Latest | Categories named |
|---|---|---|---|---|---|
| Report or ebook | 67 | undated | |||
| Webinar or virtual event | 16 | undated | |||
| Conference or event | 16 | undated | |||
| Podcast or video | 7 | undated | |||
| Case study | 3 | undated | |||
| Blog | 1 | undated | |||
| Comparison | 1 | undated | |||
| Template or tool | 1 | undated | |||
| News or press | 1 | undated |
Every page fiverr.com exposes, subdomains included. Kind is read from the address and title. The last 90 days, the latest date and the twelve months count pages by when they were published, from the site's feeds, a date in the address, or the page's own publication date, read from up to a hundred of its most recently changed pages; a page that says only when it last changed is counted in its kind but not in when, so the recent counts are a floor, and a kind none of whose pages gives a publication date reads undated. An event counts as online when its address or title says so (webinar, on demand, virtual or online summit); a conference, summit, trade show, expo or roadshow that does not say so is counted as a conference or event, which on a vendor's site is mostly in person. Read September 29, 2026.
An email the morning each edition publishes: where this product moved, where it held, and by how much against the noise floor. One address, confirmed by a click; a stop link in every email.
Already following? Everything you follow, with a stop for each.
What Fiverr's own pages state, read September 28, 2026: fiverr.com, fiverr.com/logo-maker/pricing, fiverr.com/logo-maker/ideas/tag/security. A claimed page can correct any of them.
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when Fiverr's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as Fiverr, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
A new claim receives the current edition's vendor brief for Fiverr by email, built from the raw record of the edition. It shows: