ZoomInfo vs G2 Buyer Intent
One of fourteen models named ZoomInfo first on the direct prompt; two named G2 Buyer Intent. Both were named by all fourteen models and ZoomInfo carries 44 labels and G2 Buyer Intent 46, so the shares are not directly comparable.
Vancouver, Washington, United States, founded 2000. Named in fifteen categories this edition.
By G2, Chicago, United States, founded 2012. Named in ten 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 B2B intent data providers page.
By framing
ZoomInfoFirst choices, of fourteen modelsG2 Buyer Intent
Across every category in the November 2026 Edition, ZoomInfo and G2 Buyer Intent were named in the same answer ninety-seven times, of the 617 answers naming ZoomInfo and the 176 naming G2 Buyer Intent. In those answers G2 Buyer Intent took the first choice six times and ZoomInfo seven.
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 | | | | |
ZoomInfo G2 Buyer Intent first choice named as an alternative argued againstblank: not namedEach cell is one answer, ZoomInfo on the left and G2 Buyer Intent on the right.The direct prompt
ZoomInfo first, G2 Buyer Intent an alternative
1 of 14 modelsG2 Buyer Intent was named in the answer but not as the choice, or not at all.G2 Buyer Intent first, ZoomInfo not the choice
2 of 14 modelsZoomInfo was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
8 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
3 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
G2 Buyer Intent7%#3 of 13ZoomInfo2%#7 of 13ZoomInfo9%#3 of 12G2 Buyer Intent4%#5 of 12ZoomInfo4%#4 of 9G2 Buyer Intent0%#6 of 9What the models said about ZoomInfo
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“Bidstream-based providers (e.g., ZoomInfo, Demandbase) - Why avoid: These providers harvest intent data from ad auctions, which is legally contested” Mistral Small · negative prompt · hard negative
“Data accuracy issues: Multiple sources cite outdated contacts, incorrect job titles, and stale information as persistent problems” Kimi K2 · negative prompt · hard negative
What the models said about G2 Buyer Intent
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of three in this category shown.
“G2 Buyer Intent can be valuable for software companies, but it only reflects activity on categories G2 indexes well” Perplexity Sonar · negative prompt · soft negative
“Bombora layered with G2 Buyer Intent is the pragmatic starting point” Claude Haiku 4.5 · direct prompt · first choice
“or G2 Buyer Intent (if you're in software/SaaS)” Kimi K2 · direct 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.