Zero of twelve models named FreshBooks first on the direct prompt; zero named Docyt. FreshBooks was named by eight of the twelve models and Docyt by seven and FreshBooks carries 14 labels and Docyt 11, so the shares are not directly comparable.
Named in eleven categories this edition.
Named in two 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 AI accounting assistants 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. One of one in this category shown.
“Xero at $25/month or FreshBooks at $23/month offer the best value” MiniMax M2.5 · budget prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Three of four in this category shown.
“I recommend starting with Vic.ai for accounts payable and Docyt for end‑to‑end bookkeeping.” GLM 4.7 FlashX · paraphrase prompt · first choice
“Accounting firm managing many clients → Dext + Karbon or Docyt.” DeepSeek V4 Flash · comparative prompt · alternative
“Best for: Multi-location businesses (e.g., hospitality/franchises)” Grok 4.1 Fast · comparative prompt · alternative
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.