Five of fourteen models named Hightouch Adaptive Identity Resolution first on the direct prompt; zero named Zingg. Hightouch Adaptive Identity Resolution was named by thirteen of the fourteen models and Zingg by ten and Hightouch Adaptive Identity Resolution carries 36 labels and Zingg 12, 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 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 4.20 | ||||||
| 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 |
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. Three of four in this category shown.
“The safer play in 2026: Warehouse-native or composable identity layers (e.g., Hightouch, Delivr.ai, or native Snowflake/Databricks approaches)” Kimi K2 · negative prompt · first choice
“Choose Hightouch if your source of truth is already in Snowflake/Databricks/BigQuery and you want control over logic.” GPT-5.4 mini · comparative prompt · first choice
“Hightouch Adaptive Identity Resolution is currently ranked as the leading choice for mid-market B2B companies.” Qwen 3.7 Flash · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“if your team doesn't have the engineering bandwidth, Zingg requires ongoing investment to build labeled training data” Claude Haiku 4.5 · budget prompt · soft negative
“Ranked as the top free, open-source identity resolution platform, making it ideal for budget-conscious organizations.” Mistral Small · budget prompt · first choice
“Zingg (Best for ML & Fuzzy Matching): ... Cost: Free & Open Source.” Gemini 3.5 Flash · budget prompt · first choice
“Best Free Option: Zingg ... free, most powerful long-term” Kimi K2 · budget 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.