Two of fourteen models named Gong first on the direct prompt; one named Highspot. Both were named by all fourteen models and Gong carries 40 labels and Highspot 38, so the shares are not directly comparable.
By Gong.io, Ramat Gan, Israel, founded 2015. Named in fourteen categories this edition.
Seattle, United States, founded 2012. 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 sales coaching and training page.
Across every category in the October 2026 Edition, Gong and Highspot were named in the same answer eighty-three times, of the 578 answers naming Gong and the 460 naming Highspot. In those answers Highspot took the first choice one time and Gong nineteen.
| 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 |
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. One of one in this category shown.
“1. Gong 🏆 ... Differentiator: The deepest after-the-call analytics on the market with behavioral benchmarking and revenue intelligence. Named a Leader in Gartner's 2025 Magic Quadrant.” Kimi K2 · comparative 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.