Ten of twelve models named Apollo.io first on the direct prompt; two named Cleanlist. Apollo.io was named by twelve of the twelve models and Cleanlist by eight and Apollo.io carries 64 labels and Cleanlist 20, so the shares are not directly comparable.
San Francisco, United States, founded 2015. Named in twenty categories this edition.
Named in six 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 data enrichment 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. Three of three in this category shown.
“Tools with Significant Data Quality Issues ... Bounce rates of 20-35% reported by multiple users, even for emails labeled "verified"” MiniMax M2.5 · negative prompt · hard negative
“Be cautious with these B2B data enrichment tools... Apollo.io: Frequently criticized for 15-30% email bounce rates” Grok 4.1 Fast · negative prompt · hard negative
“Apollo.io is widely recommended for budget-conscious teams.... Apollo provides more functionality at a lower price point than almost any competitor” Claude Haiku 4.5 · budget prompt · first choice
No label in this category carried a quote.
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.