Apollo.io vs Clay
Eleven of fourteen models named Apollo.io first on the direct prompt; one named Clay. Both were named by all fourteen models and Apollo.io carries 72 labels and Clay 37, so the shares are not directly comparable.
San Francisco, United States, founded 2015. Named in twenty-six categories this edition.
Named in eleven 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
Apollo.ioFirst choices, of fourteen modelsClay
Across every category in the October 2026 Edition, Apollo.io and Clay were named in the same answer 170 times, of the 1056 answers naming Apollo.io and the 234 naming Clay. In those answers Clay took the first choice nine times and Apollo.io seventy-six.
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 4.20 | | | | | ||
| 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 | | | | | |
Apollo.io Clay first choice named as an alternative argued againstblank: not namedEach cell is one answer, Apollo.io on the left and Clay on the right.The direct prompt
Apollo.io first, Clay an alternative
11 of 14 modelsClay was named in the answer but not as the choice, or not at all.Clay first, Apollo.io an alternative
1 of 14 modelsApollo.io was named in the answer but not as the choice, or not at all.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.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
Apollo.io77%#1 of 10Clay4%#3 of 10Apollo.io73%#1 of 12Clay6%#2 of 12Apollo.io6%#3 of 9Clay6%#4 of 9What the models said about Apollo.io
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“data accuracy and billing are the top pain points at scale” Muse Glimmer 30B · negative prompt · hard negative
What the models said about Clay
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“multi-provider setups built with tools such as Apollo’s waterfall feature or Clay... may make it harder to trace where a particular field came from” GPT-6 Luna · negative prompt · soft negative
“Don't adopt Clay unless you have technical staff to manage workflows.” DeepSeek V4 Flash · negative prompt · soft negative
“requires 3 to 4 additional tools and has unpredictable credit costs” Claude Haiku 4.5 · comparative prompt · soft negative
“Choose Clay if you have a modern, tech-savvy sales/marketing team ... wants the best possible email-finding coverage” Gemini 3.5 Flash · paraphrase prompt · first choice
“Clay (Best for Workflow Orchestration & Waterfall Enrichment): Clay is a market leader for modern GTM teams.” Gemini 3.5 Flash · scale prompt · first choice
“If your strategy is personalized outbound and you want maximum data coverage: Go with Clay.” Gemini 3.5 Flash · comparative 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.