PandaDoc vs Loopio
Nine of twelve models named PandaDoc first on the direct prompt; zero named Loopio. PandaDoc was named by twelve of the twelve models and Loopio by nine and PandaDoc carries 58 labels and Loopio 18, so the shares are not directly comparable.
South San Francisco, United States, founded 2013. Named in five categories this edition.
Named in one category 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 proposal software page.
By framing
PandaDocFirst choices, of twelve modelsLoopio
Across every category in the September 2026 Edition, PandaDoc and Loopio were named in the same answer fifty-five times, of the 405 answers naming PandaDoc and the 62 naming Loopio. In those answers Loopio took the first choice eleven times and PandaDoc eighteen.
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 | | | | |
PandaDoc Loopio first choice named as an alternative argued againstblank: not namedEach cell is one answer, PandaDoc on the left and Loopio on the right.The direct prompt
PandaDoc first, Loopio an alternative
9 of 12 modelsLoopio was named in the answer but not as the choice, or not at all.Neither was the first choice, one was named
2 of 12 modelsThe answer put something else first and named one of the two as an alternative.Neither was named
1 of 12 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
PandaDoc49%#1 of 10Loopio0%#10 of 10PandaDoc49%#1 of 10Loopio2%#6 of 10What the models said about PandaDoc
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Four of five in this category shown.
“Avoid: Tools like PandaDoc for government contracts, RFPs, or complex enterprise bids ... PandaDoc - Good for general sales proposals” GLM 4.7 FlashX · negative prompt · soft negative
“PandaDoc is currently the industry standard for mid-market businesses because it strikes the best balance between ease of use, functionality, and price.” Qwen 3.7 Flash · direct prompt · first choice
“Best for mid-market sales teams needing an all-in-one document workflow, it's the most widely adopted proposal AI-powered sales platform in B2B” Claude Haiku 4.5 · direct prompt · first choice
“Pick PandaDoc if you need one platform for proposals *and* contracts, NDAs, quotes, and other documents, with deep CRM integration.” DeepSeek V4 Flash · comparative prompt · first choice
What the models said about Loopio
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Five of six in this category shown.
“Choose Loopio only if RFPs are central to your sales process — it's overkill for standard proposals.” Kimi K2 · direct prompt · soft negative
“notoriously expensive ($$$) and require weeks of training and configuration” Qwen 3.7 Flash · negative prompt · soft negative
“Loopio is often recommended for mid-market teams (50–300 RFPs/year), priced around $25K–$75K/year” DeepSeek V4 Flash · scale prompt · first choice
“invest in Enterprise Response Management systems like Responsive (formerly RFPIO) or Loopio” Gemini 3.5 Flash · negative prompt · alternative
“If you answer security questionnaires or complex RFPs, go with SiftHub or Loopio.” Gemini 3.5 Flash · 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.