Background screening · November 2026 Edition
Checkr vs Accurate Background
Eleven of fourteen models named Checkr first on the direct prompt; one named Accurate Background. Checkr was named by fourteen of the fourteen models and Accurate Background by thirteen and Checkr carries 63 labels and Accurate Background 27, so the shares are not directly comparable.
Named in two categories this edition.
Named in one category this edition.
First-choice share53%6%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate13%7%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#1#4A position in a field of 15; printed, not drawn.
Labels6327A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Checkr reading right to left. Rank and label count are printed, not drawn.Certn was named alongside these two in eleven of the fourteen direct answers. Checkr vs Certn · Checkr vs GoodHire · Checkr vs AccuSourceHR
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the background screening page.
By framing
How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
CheckrFirst choices, of fourteen modelsAccurate Background
Direct111
Paraphrase112
Comparative100
Budget-constrained402 against Checkr
Scale-constrained20
Negative106 against Checkr · 2 against Accurate Background
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.
Across every category in the November 2026 Edition, Checkr and Accurate Background were named in the same answer sixty-two times, of the 194 answers naming Checkr and the 70 naming Accurate Background. In those answers Accurate Background took the first choice four times and Checkr twenty-six.
Every model, every framing
The eighty-four answers behind the chart above, one cell each: where Checkr and Accurate Background stood in it.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | |||
| GPT-5.4 mini | | | | | ||
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | | | ||
| Grok 4.20 | | | | | | |
| Mistral Small | | | | | ||
| DeepSeek V4 Flash | | | | | | |
| Llama 4 Maverick | | | | | ||
| Qwen 3.7 Flash | | | | |||
| Kimi K2 | | | | | ||
| GLM 4.7 FlashX | | | | |||
| MiniMax M2.5 | | | | | ||
| GPT-6 Luna | | | | | ||
| Muse Glimmer 30B | | | |
Checkr Accurate Background first choice named as an alternative argued againstblank: not namedEach cell is one answer, Checkr on the left and Accurate Background on the right.The direct prompt
The plain question, one answer per model, grouped by where Checkr and Accurate Background stood in it.
Checkr first, Accurate Background an alternative
11 of 14 modelsAccurate Background was named in the answer but not as the choice, or not at all.GPT-5.4 miniCheckr alternatives: Certn, GoodHire, VICTIG
Gemini 3.5 FlashCheckr alternatives: Accurate Background, Certn, Verified First
Perplexity SonarCheckr alternatives: AccuSourceHR, Certn, Mitratech AssureHire, Verified First
Grok 4.20Checkr alternatives: Certn, GoodHire
Mistral SmallCertn, Checkr alternatives: ADP RUN, Mitratech AssureHire, Verified First
DeepSeek V4 FlashCertn, Checkr alternatives: Accurate Background, GoodHire, Turn
Llama 4 MaverickCheckr alternatives: AccuSourceHR, Bchex, Certn, ClearStar, First Advantage, GoodHire, Mitratech AssureHire, Turn, Verified First
Kimi K2Certn, Checkr alternatives: First Advantage, GoodHire, Verified First
GLM 4.7 FlashXCheckr alternatives: Certn, GoodHire
MiniMax M2.5Checkr alternatives: Accurate Background, Certn, GoodHire
Muse Glimmer 30BCheckr alternatives: AccuSourceHR, Accurate Background, BackgroundChecks.com, Certn, HireShield, Mitratech AssureHire, Turn, Verified First
Accurate Background first, Checkr an alternative
1 of 14 modelsCheckr was named in the answer but not as the choice, or not at all.GPT-6 LunaAccurate Background alternatives: Checkr
Neither was the first choice, one was named
1 of 14 modelsThe answer put something else first and named one of the two as an alternative.Claude Haiku 4.5AccuSourceHR alternatives: Accurate Background, Bchex, Mitratech AssureHire
Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.Qwen 3.7 FlashCheckster alternatives: BrightCheck, Certified Background, GoodHire
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Checkr leads by twenty-nine points.
Checkr31%#2 of 10Accurate Background2%#6 of 10Mid-marketThe figures above
Checkr leads by forty-seven points.
Checkr53%#1 of 15Accurate Background6%#4 of 15Enterprise
Checkr leads by forty-six points.
Checkr46%#1 of 10Accurate Background0%#7 of 10What the models said about Checkr
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Checkr drew 469 of the 1,051 complaints the CFPB received in 2025 about the 8 employment background check company names studied, 44.6%, more than any other screening company” Muse Glimmer 30B · negative prompt · hard negative
“Even large, fully accredited employment background screeners (e.g., *Checkr, First Advantage, HireRight, Sterling*) are legitimate, FCRA-compliant CRAs, but job seekers and employers frequently register complaints about them” Gemini 3.5 Flash · negative prompt · soft negative
“Tops CFPB complaints (469 in 2025, ~45% of total for major firms). Users report frequent inaccuracies, delays in results, and frustrating support.” Grok 4.20 · negative prompt · soft negative
“Checkr is widely considered the "Apple" of background checks—featuring a mobile-first applicant experience, an open API, and aggressive use of AI” Qwen 3.7 Flash · comparative prompt · first choice
“mid-market modern screening platforms (like Checkr, Rippling built-in checks, or GoodHire) often outperform legacy enterprise vendors” Gemini 3.5 Flash · scale prompt · first choice
“I'd recommend starting with Accurate ... or Checkr if you prefer a modern, automation-focused platform. Both are well-suited” Claude Haiku 4.5 · paraphrase prompt · first choice
What the models said about Accurate Background
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“The worst background check agency on the planet. They will take MONTHS to complete your background check...” Muse Glimmer 30B · negative prompt · hard negative
“Major established players like Accurate, Checkr, HireRight, and First Advantage are widely used, but even they have some consumer complaints about accuracy and turnaround times.” MiniMax M2.5 · negative prompt · soft negative
“I'd start with Accurate Background. It explicitly serves mid-market employers” GPT-6 Luna · direct prompt · first choice
“the strongest default recommendation is Accurate Background” Perplexity Sonar · paraphrase prompt · first choice
“Accurate (Top Pick for Mid-Sized Businesses)” Claude Haiku 4.5 · paraphrase prompt · first choice
Also compared
Checkr vs CertnCheckr vs GoodHireCheckr vs AccuSourceHRCheckr vs BackgroundChecks.comCheckr vs SpokeoCertn vs Accurate BackgroundGoodHire vs Accurate BackgroundAccurate Background vs AccuSourceHRAccurate Background vs BackgroundChecks.comAccurate Background vs SpokeoAll twenty-one head-to-head pages and the full background screening standing
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.