Zero of twelve models named Fathom first on the direct prompt; zero named Prophix. Fathom was named by ten of the twelve models and Prophix by nine and Fathom carries 10 labels and Prophix 17, so the shares are not directly comparable.
Named in nine categories this edition.
Named in nine categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all twelve 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 FP&A platforms page.
| 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 |
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.
“Fathom (cheapest) or Clockwork (best overall for forecasting + AI) are your strongest picks” DeepSeek V4 Flash · budget prompt · first choice
“Fathom – Best Value for Money ... Fathom is the most cost-effective professional solution” Kimi K2 · budget prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Two of two in this category shown.
“Prophix (slow performance, limited functionality, steep learning curve)” GLM 4.7 FlashX · negative prompt · hard negative
“Be wary of mid-market tools (Centage, Datarails, Vena, Prophix) if you are a small business” Mistral Small · negative prompt · soft negative
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.