Four of twelve models named Tealium first on the direct prompt; one named Demandbase. Tealium was named by eleven of the twelve models and Demandbase by seven and Tealium carries 25 labels and Demandbase 11, so the shares are not directly comparable.
San Diego, United States, founded 2008. Named in six categories this edition.
San Francisco, United States, founded 2006. Named in eighteen categories this edition.
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 identity resolution page.
| 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 |
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.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“Tealium or Amperity offer deeper identity resolution while remaining scalable for mid-market companies” Claude Haiku 4.5 · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“Widely considered the gold standard for ABM. It uses deep identity resolution to map anonymous website visitors to accounts with high accuracy.” Qwen 3.7 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.