Zero of fourteen models named 1up first on the direct prompt; zero named Qwilr. 1up was named by eight of the fourteen models and Qwilr by ten and 1up carries 11 labels and Qwilr 13, so the shares are not directly comparable.
Named in one category this edition.
Redfern, Australia, founded 2014. 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 RFP response 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 four in this category shown.
“Best budget-friendly pick: 1up” GPT-6 Luna · budget prompt · first choice
“Prioritize tools like Loopio, Responsive, or AI-native ones (e.g., 1up, AutoRFP.ai) with proven traceability.” Grok 4.1 Fast · negative prompt · alternative
“1up or AutoRFP.ai if you want lightweight AI assistance without a heavy admin burden.” Perplexity Sonar · budget prompt · alternative
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. One of one in this category shown.
“I'd recommend starting with PandaDoc or Qwilr” GLM 4.7 FlashX · paraphrase prompt · first choice
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.