Loopio vs Qwilr
Ten of fourteen models named Loopio first on the direct prompt; zero named Qwilr. Loopio was named by fourteen of the fourteen models and Qwilr by ten and Loopio carries 56 labels and Qwilr 13, so the shares are not directly comparable.
Named in three categories 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.
By framing
LoopioFirst choices, of fourteen modelsQwilr
Across every category in the October 2026 Edition, Loopio and Qwilr were named in the same answer forty-nine times, of the 234 answers naming Loopio and the 177 naming Qwilr. In those answers Qwilr took the first choice four times and Loopio seven.
Every model, every framing
| 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 | | | | | |
Loopio Qwilr first choice named as an alternative argued againstblank: not namedEach cell is one answer, Loopio on the left and Qwilr on the right.The direct prompt
Loopio first, Qwilr an alternative
10 of 14 modelsQwilr was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
3 of 14 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 of 14 modelsThe answer made no first choice from these two in this category.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.
By buyer segment
What the models said about Loopio
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of seven in this category shown.
“Loopio specifically called out as "not AI-native"—built in 2014 with AI added around 2021” Kimi K2 · negative prompt · hard negative
“The answers Magic populates are surface-level at best, and the feature fails to generate responses for complex RFP requirements and often needs a lot of manual editing.” Claude Haiku 4.5 · negative prompt · soft negative
“Full-blown enterprise RFP suites (like Loopio or Responsive) typically start at $10,000–$20,000+ per year, which is out of reach” DeepSeek V4 Flash · budget prompt · soft negative
“Best for structured proposal teams with dedicated content managers who need a strong content library, easier content reuse, and reliable customer support.” Claude Haiku 4.5 · comparative prompt · first choice
“Widely regarded as the most intuitive interface with the lowest learning curve. Teams can often be onboarded in days rather than months.” Qwen 3.7 Flash · comparative prompt · first choice
“mainstream platforms (like Responsive/RFPIO, Loopio, or AI-first startups like 1up.ai or Tribble) are ideal” Gemini 3.5 Flash · scale prompt · first choice
What the models said about Qwilr
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.