Gong vs Fathom
Three of fourteen models named Gong first on the direct prompt; zero named Fathom. Gong was named by fourteen of the fourteen models and Fathom by eleven and Gong carries 63 labels and Fathom 27, so the shares are not directly comparable.
By Gong.io, Ramat Gan, Israel, founded 2015. Named in fourteen 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 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 conversational intelligence and call recording page.
By framing
GongFirst choices, of fourteen modelsFathom
Across every category in the October 2026 Edition, Gong and Fathom were named in the same answer ninety-four times, of the 578 answers naming Gong and the 180 naming Fathom. In those answers Fathom took the first choice thirty-one times and Gong nine.
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 | | | | | |
Gong Fathom first choice named as an alternative argued againstblank: not namedEach cell is one answer, Gong on the left and Fathom on the right.The direct prompt
Gong first, Fathom not the choice
3 of 14 modelsFathom was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
6 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
5 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
Fathom29%#2 of 11Gong0%#11 of 11Gong14%#3 of 10Fathom6%#5 of 10What the models said about Gong
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“you should immediately bypass enterprise-level conversation intelligence (CI) giants like Gong and Chorus by ZoomInfo” Gemini 3.5 Flash · budget prompt · hard negative
“Gong.io — The Most Expensive and Complicated Option ... Pricing transparency issues (major red flag)” DeepSeek V4 Flash · negative prompt · hard negative
“Gong is widely considered the market leader in Revenue Intelligence... If you have the budget ($1k-$1.5k/user/month) and want rigorous sales optimization, this is the one.” Qwen 3.7 Flash · paraphrase prompt · first choice
“The market-leading conversation intelligence platform focused on revenue analytics... For large sales teams needing deep revenue intelligence: Gong or Clari Copilot.” GLM 4.7 FlashX · comparative prompt · first choice
What the models said about Fathom
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of four in this category shown.
“not a replacement for CI platforms because it lacks the deal-risk layer, coaching workflow, and forecasting use case” Perplexity Sonar · negative prompt · hard negative
“users report frequent issues with "hallucinated" insights where the AI summarizes a call incorrectly” Qwen 3.7 Flash · negative prompt · soft negative
“Fathom is widely considered the gold standard for teams seeking maximum value with minimal or zero spend.” Gemini 3.5 Flash · budget prompt · first choice
“### 1. Fathom - Best Free Option ... want to start completely free with no usage limits.” GLM 4.7 FlashX · 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.