| Category | Function | Share | Rank | Negative rate | Labels | Quadrant | Since September 2026 |
|---|---|---|---|---|---|---|---|
| Candidate assessment | Talent acquisition | 19% | 2 of 118 | 14% | 35 | accepted challenger | ▲+7Since September 2026: 10% → 17%, +7 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Skills intelligence | Performance and talent management | 0% | 53 of 127 | 0% | 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. |
| Technical hiring assessments | Talent acquisition | 0% | 64 of 71 | 50% | 2 | under 10 labels · led by HackerRank at 17% | =heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked. |
| Category | September 2026 | Now | Change | Reading | Rank |
|---|---|---|---|---|---|
| Candidate assessment | 10% | 17% | ▲+7Since September 2026: 10% → 17%, +7 points. Inside the 13-point floor: within noise. Read over the models both editions asked. | Within noise | Rank 2 of 118, unchanged |
| 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 44 → 53 of 127 |
| Technical hiring assessm | 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 39 → 64 of 71 |
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 | 1 | 0 | 2 |
| GPT-5.4 mini | 0 | 0 | 0 | 0 | 0 |
| Gemini 3.5 Flash | 0 | 2 | 1 | 0 | 3 |
| Perplexity Sonar | 1 | 0 | 0 | 0 | 1 |
| Grok 4.1 Fast | 1 | 0 | 2 | 0 | 3 |
| Mistral Small | 1 | 0 | 2 | 0 | 3 |
| DeepSeek V4 Flash | 1 | 3 | 1 | 1 | 6 |
| Llama 4 Maverick | 1 | 0 | 1 | 0 | 2 |
| Qwen 3.7 Flash | 0 | 0 | 0 | 2 | 2 |
| Kimi K2 | 2 | 2 | 0 | 1 | 5 |
| GLM 4.7 FlashX | 0 | 0 | 2 | 1 | 3 |
| MiniMax M2.5 | 0 | 0 | 1 | 0 | 1 |
| GPT-6 Luna | 2 | 2 | 0 | 0 | 4 |
| Muse Glimmer 30B | 1 | 2 | 0 | 1 | 4 |
Verbatim evidence the judge attached to positive labels.
“Criteria Corp is a good choice for mid-market companies that want a validated battery embedded in an existing ATS or HRIS stack.” Llama 4 Maverick · Candidate assessment · paraphrase prompt · first choice
“For a 500-person company: Mid-market platforms (Criteria Corp, Plum, TestGorilla Plus tier) often hit the sweet spot” Kimi K2 · Candidate assessment · scale prompt · first choice
“For a mid-market B2B company the platform that is most consistently called out as a fit is Criteria Corp.” Muse Glimmer 30B · Candidate assessment · direct prompt · first choice
“choose SHL or Criteria when you need a broader, structured assessment program” GPT-6 Luna · Candidate assessment · 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.
“Avoid: Criteria Corp, Wonderlic, and HireVue if budget is a concern” Kimi K2 · Candidate assessment · budget prompt · hard negative
“Avoid platforms like Criteria Corp, Predictive Index, or HireVue” DeepSeek V4 Flash · Candidate assessment · budget prompt · hard negative
“Cons: User interface can feel dated/clunky ... implementation often requires a dedicated project manager.” Qwen 3.7 Flash · Candidate assessment · direct prompt · soft negative
“"Criteria Corp, SHL, HireVue, and Wonderlic publish nothing."” Muse Glimmer 30B · Candidate assessment · 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 98 of the 110 answers that named Criteria Corp and are not a share of its labels.
310 of the 337 domain citations in answers naming Criteria Corp 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.
What Criteria Corp's own pages state, read September 28, 2026: criteriacorp.com/assess/skills/criteria-basic-skills-test-cbst, criteriacorp.com/assessments/skills/criteria-basic-skills-test-2-cbst2, criteriacorp.com/assess/personality/criteria-personality-inventory-cpi, criteriacorp.com/assess/cognitive-aptitude/criteria-attention-skills-test-cast, criteriacorp.com/assess/cognitive-aptitude/criteria-cognitive-aptitude-test-ccat. 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 Criteria Corp'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 Criteria Corp, 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 Criteria Corp by email, built from the raw record of the edition. It shows:
Criteria Corp is among the products AI models recommend first in Candidate assessment this edition. Each badge says so in the buyer's words, names the edition, and links to the standing. The next edition issues a new badge; this one stays true as a record of October 2026.
Badges read on light and dark pages. Alt text carries the claim, the category, the edition and the index, so it stays a citation where the image does not load.