Zero of fourteen models named BILL Spend & Expense first on the direct prompt; zero named Navan. Both were named by all fourteen models and BILL Spend & Expense carries 43 labels and Navan 42, so the shares are not directly comparable.
Named in four categories this edition.
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 expense management page.
Across every category in the November 2026 Edition, BILL Spend & Expense and Navan were named in the same answer eighty-one times, of the 363 answers naming BILL Spend & Expense and the 366 naming Navan. In those answers Navan took the first choice four times and BILL Spend & Expense four.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.20 | ||||||
| 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.
“the two I'd most strongly caution against based on user experiences” DeepSeek V4 Flash · negative prompt · hard negative
“Choose Ramp or BILL Spend & Expense if: You qualify for corporate cards and want an end-to-end software platform with $0 fees.” Gemini 3.5 Flash · 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.