Blinq vs BoothIQ
Six of fourteen models named Blinq first on the direct prompt; one named BoothIQ. Blinq was named by thirteen of the fourteen models and BoothIQ by nine and Blinq carries 46 labels and BoothIQ 14, so the shares are not directly comparable.
Named in one category this edition.
Named in one category this edition.
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 event lead capture apps page.
By framing
BlinqFirst choices, of fourteen modelsBoothIQ
Across every category in the October 2026 Edition, Blinq and BoothIQ were named in the same answer thirty-one times, of the 133 answers naming Blinq and the 39 naming BoothIQ. In those answers BoothIQ took the first choice seven times and Blinq six.
Every model, every framing
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | | | |||
| GPT-5.4 mini | | | ||||
| Gemini 3.5 Flash | | | | | | |
| Perplexity Sonar | | | | |||
| Grok 4.1 Fast | | | | | | |
| 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 | | |
Blinq BoothIQ first choice named as an alternative argued againstblank: not namedEach cell is one answer, Blinq on the left and BoothIQ on the right.The direct prompt
Blinq first, BoothIQ not the choice
6 of 14 modelsBoothIQ was named in the answer but not as the choice, or not at all.BoothIQ first, Blinq an alternative
1 of 14 modelsBlinq was named in the answer but not as the choice, or not at all.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.Neither was named
6 of 14 modelsThe answer made no first choice from these two in this category.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
What the models said about Blinq
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Budget Warning: This can get expensive quickly. Capturing just 100 leads would cost roughly $1,000 in credits alone” Qwen 3.7 Flash · budget prompt · soft negative
“Blinq ... Pricing model: Usage-based at $9.99 per lead captured — costs escalate quickly with volume” Kimi K2 · negative prompt · soft negative
“While Blinq holds high ratings (4.8/5 on G2), recent verified reviewers noted specific pain points” Qwen 3.7 Flash · negative prompt · soft negative
“Blinq - a top-rated app with a 4.8/5 rating from 9,426 reviews, offering AI enrichment, AI notetaker, and digital business cards.” Llama 4 Maverick · paraphrase prompt · first choice
“Blinq – Highly recommended for mid-market and enterprise teams, offering robust lead capture and management features.” Mistral Small · direct prompt · first choice
“the best single pick is usually Blinq if your priority is broad mid-market fit with strong lead capture workflows” Perplexity Sonar · direct prompt · first choice
What the models said about BoothIQ
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“but it does not have AI-powered follow-ups or field sales support” Llama 4 Maverick · negative prompt · soft negative
“BoothIQ (Best Overall Free Lead Capture App) ... is the top choice” Gemini 3.5 Flash · budget prompt · first choice
“Top Recommendation: BoothIQ (Best Free Option)” Kimi K2 · budget prompt · first choice
“BoothIQ and Mobly are the modern standard” Gemini 3.5 Flash · direct prompt · first choice
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.