Two of fourteen models named 15Five first on the direct prompt; five named Lattice. 15Five was named by nine of the fourteen models and Lattice by ten and both carry 11 labels, so the shares below are directly comparable.
Named in ten categories this edition.
Named in nineteen 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 coaching platforms page.
Across every category in the October 2026 Edition, 15Five and Lattice were named in the same answer 259 times, of the 327 answers naming 15Five and the 712 naming Lattice. In those answers Lattice took the first choice fifty-seven times and 15Five twenty.
| 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. Two of two in this category shown.
“Winner: 15Five 15Five is widely considered the gold standard for affordable, user-friendly continuous coaching.” Qwen 3.7 Flash · budget prompt · first choice
“I'd recommend starting with 15Five given its extremely low starting price of $4/user/month” 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.