Lusha vs Hunter
Zero of fourteen models named Lusha first on the direct prompt; zero named Hunter. Lusha was named by fourteen of the fourteen models and Hunter by eleven and Lusha carries 45 labels and Hunter 15, so the shares are not directly comparable.
By Lusha Systems, Boston, United States, founded 2016. Named in five categories this edition.
By Hunter.io, United States, founded 2015. Named in seven categories 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 data enrichment page.
By framing
LushaFirst choices, of fourteen modelsHunter
Across every category in the October 2026 Edition, Lusha and Hunter were named in the same answer forty-six times, of the 340 answers naming Lusha and the 81 naming Hunter. In those answers Hunter took the first choice one time and Lusha zero.
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 | | |
Lusha Hunter first choice named as an alternative argued againstblank: not namedEach cell is one answer, Lusha on the left and Hunter on the right.The direct prompt
Neither was the first choice, one was named
2 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
12 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
Lusha2%#6 of 12Hunter2%#7 of 12What the models said about Lusha
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of five in this category shown.
“Low email accuracy: Independent checks suggest only about 68% email return at roughly 82% accuracy, which is below industry standards.” Mistral Small · negative prompt · hard negative
“Tools that have faced regulatory actions (e.g., Lusha's Italy fine) should be avoided in sensitive jurisdictions.” GLM 4.7 FlashX · negative prompt · hard negative
“Some users report issues with outdated contact information and relatively high pricing for infrequent use.” Claude Haiku 4.5 · negative prompt · soft negative
“Safer bets from reviews: Tools like Lusha (98% email accuracy, free tier)” Grok 4.1 Fast · negative prompt · first choice
“Apollo.io or Lusha are the right entry points. Both offer free tiers” Claude Haiku 4.5 · budget prompt · first choice
What the models said about Hunter
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“Hunter.io for the cheapest email-only option” Muse Glimmer 30B · budget prompt · first choice
“Hunter (Best for email-focused teams) - Cheap and reliable for email enrichment specifically” MiniMax M2.5 · budget prompt · alternative
“If you only need email addresses, Hunter.io or Lusha may be the most cost-effective choices.” Mistral Small · budget 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.