Six of fourteen models named Oracle NetSuite first on the direct prompt; zero named Wave. Both were named by all fourteen models and Oracle NetSuite carries 49 labels and Wave 30, so the shares are not directly comparable.
Named in twenty categories this edition.
Named in seventeen 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 accounting software 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 | ||||||
| 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. Three of three in this category shown.
“Who should avoid it: Small businesses, startups, and organizations that don't need enterprise-level ERP capabilities.” DeepSeek V4 Flash · negative prompt · hard negative
“NetSuite is the market's default ERP-grade ledger: multi-entity consolidation, multiple currencies, and revenue recognition rules running under one system” Muse Glimmer 30B · paraphrase prompt · first choice
“Top contenders: NetSuite (scalable ERP)... *Tip*: If expanding, choose ERP finance modules (e.g., NetSuite) over standalone accounting.” Grok 4.1 Fast · scale 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.