Wave Connect vs B2Brain
One of fourteen models named Wave Connect first on the direct prompt; one named B2Brain. Wave Connect was named by ten of the fourteen models and B2Brain by ten and Wave Connect carries 22 labels and B2Brain 21, so the shares are not directly comparable.
Wave Connect
accepted challengerNamed 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
Across every category in the October 2026 Edition, Wave Connect and B2Brain were named in the same answer seventeen times, of the 65 answers naming Wave Connect and the 46 naming B2Brain. In those answers B2Brain took the first choice three times and Wave Connect six.
Every model, every framing
| Model | DirectWC | ParaphraseWC | ComparativeWC | Budget-constrainedWC | Scale-constrainedWC | NegativeWC |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | | WC | ||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | WC | |||||
| Perplexity Sonar | | WC | WC | |||
| Grok 4.1 Fast | WC | WC | ||||
| Mistral Small | ||||||
| DeepSeek V4 Flash | | WC | WC | | ||
| Llama 4 Maverick | | |||||
| Qwen 3.7 Flash | WC | | | |||
| Kimi K2 | WC | WC | WC | | WC | |
| GLM 4.7 FlashX | WC | WC | ||||
| MiniMax M2.5 | | WC | ||||
| GPT-6 Luna | ||||||
| Muse Glimmer 30B | WC | WC | WC |
B2BrainWC first choiceWC named as an alternativeWC argued againstblank: not namedEach cell is one answer, Wave Connect on the left and B2Brain on the right.The direct prompt
Wave Connect first, B2Brain not the choice
1 of 14 modelsB2Brain was named in the answer but not as the choice, or not at all.B2Brain first, Wave Connect not the choice
1 of 14 modelsWave Connect was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
3 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
9 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
B2Brain5%#5 of 13B2Brain4%#7 of 13B2Brain4%#6 of 12What the models said about Wave Connect
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Odd pricing structure ($10/lead); no handheld rental, app-only; not ideal for high-volume scanning.” DeepSeek V4 Flash · paraphrase prompt · soft negative
“Wave Connect and Captello are the two named in the recent review as the only platforms backing their security posture with named, audited certifications.” Muse Glimmer 30B · negative prompt · first choice
“Better Alternatives to Consider ... Wave Connect — pay-per-lead model ($10/enriched lead), no per-user fees” Kimi K2 · negative prompt · first choice
“I would recommend Wave Connect as the best default trade show badge scanning and lead retrieval tool” Perplexity Sonar · paraphrase prompt · first choice
What the models said about B2Brain
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Low-Velocity Review Platforms (e.g., B2Brain, Mobly) ... require more due diligence before enterprise adoption.” Qwen 3.7 Flash · negative prompt · soft negative
“I'd recommend starting with Mobly Capture or B2Brain” MiniMax M2.5 · direct prompt · first choice
“I would recommend B2Brain as the top choice” DeepSeek V4 Flash · paraphrase prompt · first choice
“B2Brain is purpose-built to turn scans into booked meetings and attributable pipeline — the strongest ROI case in the category.” DeepSeek V4 Flash · direct prompt · alternative
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.