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Recruitment marketing and career sites · September 2026 Edition

100Hires vs TalentLyft

Zero of twelve models named 100Hires first on the direct prompt; one named TalentLyft. 100Hires was named by eleven of the twelve models and TalentLyft by six and 100Hires carries 16 labels and TalentLyft 10, so the shares are not directly comparable.

100Hires

accepted challenger

Named in four categories this edition.

TalentLyft

accepted challenger

Named in two categories this edition.

First-choice share6%4%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%10%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#7A position in a field of 15; printed, not drawn.
Labels1610A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, 100Hires reading right to left. Rank and label count are printed, not drawn.Jobvite was named alongside these two in seven of the twelve direct answers. Teamtailor vs 100Hires · Teamtailor vs TalentLyft · Workable vs 100Hires

Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve 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 recruitment marketing and career sites page.

By framing

How many of the twelve models made each the first choice, per way of asking, and how many argued against it.
100HiresFirst choices, of twelve modelsTalentLyft
Direct01
Paraphrase00
Comparative001 against TalentLyft
Budget-constrained31
Scale-constrained00
Negative00
Bars are first choices, 0 to 12 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to twelve.

Across every category in the September 2026 Edition, 100Hires and TalentLyft were named in the same answer thirteen times, of the 62 answers naming 100Hires and the 31 naming TalentLyft. In those answers TalentLyft took the first choice two times and 100Hires two.

Every model, every framing

The seventy-two answers behind the chart above, one cell each: where 100Hires and TalentLyft stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
Claude Haiku 4.5
GPT-5.4 mini
Gemini 3.5 Flash
Perplexity Sonar
Grok 4.1 Fast
Mistral Small
DeepSeek V4 Flash
Llama 4 Maverick
Qwen 3.7 Flash
Kimi K2
GLM 4.7 FlashX
MiniMax M2.5
100Hires TalentLyft first choice named as an alternative argued againstblank: not namedEach cell is one answer, 100Hires on the left and TalentLyft on the right.

The direct prompt

The plain question, one answer per model, grouped by where 100Hires and TalentLyft stood in it.

TalentLyft first, 100Hires not the choice

1 of 12 models100Hires was named in the answer but not as the choice, or not at all.
GLM 4.7 FlashXTalentLyft, Workable alternatives: Recruitee

Neither was the first choice, one was named

1 of 12 modelsThe answer put something else first and named one of the two as an alternative.
Grok 4.1 FastTeamtailor alternatives: Jobvite, Recruitee, TalentLyft

Neither was named

10 of 12 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5SmartDreamers alternatives: Greenhouse, Jobilla, LinkedIn Talent Solutions, Loxo
GPT-5.4 miniPhenom alternatives: Beamery, Joveo, Radancy
Gemini 3.5 FlashGem alternatives: Lever, Teamtailor
Perplexity SonarPhenom alternatives: SmartDreamers, Teamtailor
Mistral SmallJobvite alternatives: Joveo, Phenom, iCIMS
DeepSeek V4 FlashJobvite alternatives: Beamery, Phenom, Teamtailor, Workable
Llama 4 MaverickJobvite
Qwen 3.7 FlashJobvite alternatives: SmartDreamers, iCIMS
Kimi K2Jobvite, Workable alternatives: Beamery, Phenom
MiniMax M2.5Jobvite, Workable alternatives: Gem, Phenom, Teamtailor

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
100Hires leads by sixteen points.
100Hires20%#1 of 16
TalentLyft5%#7 of 16
The full small business standing →
Mid-marketThe figures above
100Hires leads by two points.
100Hires6%#4 of 15
TalentLyft4%#7 of 15
The full mid-market standing →
Enterprise
100Hires is not named for this buyer.
100Hiresnot named
TalentLyft0%#– of 13
The full enterprise standing →

What the models said about 100Hires

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.

“100Hires - Specifically designed for teams on tight budgets, offering job posting, email campaigns, and candidate tracking in a lean, easy-to-implement platform.” MiniMax M2.5 · budget prompt · first choice
“For most limited budgets: Start with 100Hires at $49/month – it offers the most comprehensive feature set at the lowest price point” Kimi K2 · budget prompt · first choice
“Recommendation: Start with 100Hires if you need to automate posting to social media to fill seats quickly.” Qwen 3.7 Flash · budget prompt · first choice

What the models said about TalentLyft

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.

“SMB options like TalentLyft (~$99/mo) exist but rank lower” Grok 4.1 Fast · comparative prompt · soft negative
“For most mid-market B2B companies, TalentLyft or Workable offer the best balance of features, pricing, and ease of use.” GLM 4.7 FlashX · direct prompt · first choice
“TalentLyft's free tier and Manatal's low starting price make them ideal starting points for companies with limited budgets” Claude Haiku 4.5 · budget prompt · first choice
“all-in-one recruiting + CRM/marketing suites for small-to-mid-size businesses” DeepSeek V4 Flash · comparative prompt · alternative
Also compared

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.