| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Recruiting CRM and sourcing | Talent acquisition | 2% | 18 of 111 | 0% | 2 | under 10 labels · led by Gem at 15% | newNew since September 2026: not ranked then, 2% now. |
| Job advertising and distribution | Talent acquisition | 0% | 22 of 111 | 38% | 26 | criticized challenger | ▼−3Since September 2026: 3% → 0%, −3 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Skills intelligence | Performance and talent management | 0% | 58 of 127 | 0% | 1 | under 10 labels · led by Skills Base at 18% | newNew since September 2026: not ranked then, 0% now. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Job advertising | 3% | 0% | ▼−3Since September 2026: 3% → 0%, −3 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 8 → 22 of 111 |
| Recruiting CRM | 0% | 2% | newNew since September 2026: not ranked then, 2% now. | New this edition | Rank 18 of 111, unchanged |
| Skills intelligence | 0% | 0% | newNew since September 2026: not ranked then, 0% now. | New this edition | Rank 58 of 127, 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 | 1 | 0 | 1 | 2 |
| GPT-5.4 mini | 1 | 1 | 0 | 0 | 2 |
| Gemini 3.5 Flash | 1 | 0 | 0 | 1 | 2 |
| Perplexity Sonar | 0 | 1 | 0 | 1 | 2 |
| Grok 4.1 Fast | 1 | 1 | 0 | 1 | 3 |
| Mistral Small | 0 | 1 | 0 | 1 | 2 |
| DeepSeek V4 Flash | 1 | 0 | 0 | 1 | 2 |
| Llama 4 Maverick | 0 | 0 | 0 | 0 | 0 |
| Qwen 3.7 Flash | 1 | 1 | 1 | 1 | 4 |
| Kimi K2 | 1 | 0 | 1 | 1 | 3 |
| GLM 4.7 FlashX | 1 | 1 | 0 | 0 | 2 |
| MiniMax M2.5 | 1 | 0 | 0 | 1 | 2 |
| GPT-6 Luna | 0 | 1 | 0 | 0 | 1 |
| Muse Glimmer 30B | 0 | 1 | 0 | 1 | 2 |
Verbatim evidence the judge attached to positive labels.
“The premium destination for professional and white-collar talent (~27.7% market share)... primary paired destinations for general hiring.” Qwen 3.7 Flash · Job advertising · comparative prompt · first choice
“If you need a specialized corporate hire: Use LinkedIn to search for and message candidates directly.” Gemini 3.5 Flash · Job advertising · comparative prompt · first choice
“LinkedIn Jobs / Hiring Pro — best for occasional hiring and minimal upfront cost.” GPT-5.4 mini · Recruiting CRM · budget prompt · first choice
“Best for: Professional, salaried, white-collar, and executive roles” DeepSeek V4 Flash · Job advertising · comparative prompt · first choice
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.
“LinkedIn (1.2/5 rating) - Arbitrary account suspensions - Data privacy concerns” Kimi K2 · Job advertising · negative prompt · hard negative
“While major platforms like LinkedIn and Indeed are legitimate, they have massive scale, making them prime targets for scammers” Qwen 3.7 Flash · Job advertising · negative prompt · soft negative
“Some platforms are not inherently unsafe, but they are common places for scams and deserve extra caution: - LinkedIn” Perplexity Sonar · Job advertising · negative prompt · soft negative
“Scammers post fakes here impersonating real companies ... Stick to vetted alternatives: LinkedIn (networking strength)” Grok 4.1 Fast · Job advertising · negative prompt · soft negative
Citations exist only for the models that return a source list, five of the fourteen in this edition, so these counts come from 77 of the 79 answers that named LinkedIn Jobs and are not a share of its labels.
199 of the 221 domain citations in answers naming LinkedIn Jobs 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.
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.
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 LinkedIn Jobs'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 LinkedIn Jobs, 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 LinkedIn Jobs by email, built from the raw record of the edition. It shows: