One of fourteen models named FullContact first on the direct prompt; zero named Zingg. FullContact was named by eleven of the fourteen models and Zingg by ten and FullContact carries 22 labels and Zingg 12, so the shares are not directly comparable.
Denver, United States, founded 2010. Named in two categories 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. Four of five in this category shown.
“These suit lighter needs but may lack depth for full CRM unification.” Grok 4.20 · paraphrase prompt · soft negative
“If you are budget-conscious: FullContact offers great entry points. You can pay for what you use and grow as you go.” Muse Glimmer 30B · budget prompt · first choice
“Begin with FullContact's free tier (100 API calls/month) or Hightouch's free tier (2 active syncs)” GLM 4.7 FlashX · budget prompt · first choice
“Start with FullContact or Customers.ai. They offer lower barriers to entry than D&B” Qwen 3.7 Flash · paraphrase 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.