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RFP response software · October 2026 Edition

Proposify vs Qwilr

Zero of fourteen models named Proposify first on the direct prompt; zero named Qwilr. Proposify was named by fourteen of the fourteen models and Qwilr by ten and Proposify carries 32 labels and Qwilr 13, so the shares are not directly comparable.

Proposify

criticized challenger

Named in six categories this edition.

Qwilr

accepted challenger

Redfern, Australia, founded 2014. Named in six categories this edition.

First-choice share5%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate28%8%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#5#8A position in a field of 10; printed, not drawn.
Labels3213A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Proposify reading right to left. Rank and label count are printed, not drawn.Loopio was named alongside these two in thirteen of the fourteen direct answers. Loopio vs Proposify · Loopio vs Qwilr · PandaDoc vs Proposify

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

How many of the fourteen models made each the first choice, per way of asking, and how many argued against it.
ProposifyFirst choices, of fourteen modelsQwilr
Direct001 against Proposify
Paraphrase31
Comparative001 against Proposify
Budget-constrained00
Scale-constrained00
Negative007 against Proposify · 1 against Qwilr
Bars are first choices, 0 to 14 each sideModels that argued againstA model can name both, so the two sides of a row do not sum to fourteen.

Across every category in the October 2026 Edition, Proposify and Qwilr were named in the same answer 141 times, of the 287 answers naming Proposify and the 177 naming Qwilr. In those answers Qwilr took the first choice five times and Proposify four.

Every model, every framing

The eighty-four answers behind the chart above, one cell each: where Proposify and Qwilr stood in it.
ModelDirectParaphraseComparativeBudget-constrainedScale-constrainedNegative
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
Proposify Qwilr first choice named as an alternative argued againstblank: not namedEach cell is one answer, Proposify on the left and Qwilr on the right.

The direct prompt

The plain question, one answer per model, grouped by where Proposify and Qwilr stood in it.

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.
Mistral SmallLoopio, Responsive alternatives: Expedience Proposal Software, Proposify
DeepSeek V4 FlashLoopio alternatives: AutoRFP.ai, Proposify, QorusDocs, Responsive
Qwen 3.7 FlashAutoRFP.ai, Loopio alternatives: Qwilr, Upland Qvidian

Neither was named

11 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Tribble alternatives: AutoRFP.ai, Loopio, Steerlab
GPT-5.4 miniLoopio alternatives: Responsive
Gemini 3.5 FlashTribble alternatives: AutoRFP.ai, Loopio, Steerlab
Perplexity SonarLoopio alternatives: Responsive
Grok 4.1 FastResponsive alternatives: Loopio
Llama 4 MaverickExpedience Proposal Software alternatives: AutoRFP.ai, Conveyor
Kimi K2Loopio alternatives: AutoRFP.ai, PandaDoc, Responsive
GLM 4.7 FlashXLoopio alternatives: Responsive, Upland Qvidian
MiniMax M2.5Loopio, Responsive alternatives: SiftHub, Upland Qvidian
GPT-6 LunaLoopio alternatives: Responsive
Muse Glimmer 30BLoopio alternatives: AutoRFP.ai, Responsive

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

The same question asked on behalf of a different buyer. Each standing is computed within its segment and they are never added together. The figures above are the mid-market standing, which is the one the category orders by.
Small business
Proposify leads by four points.
Proposify4%#5 of 14
Qwilr0%#12 of 14
The full small business standing →
Mid-marketThe figures above
Proposify leads by four points.
Proposify5%#5 of 10
Qwilr2%#8 of 10
The full mid-market standing →
Enterprise
Level: the same share of first choices.
Proposify0%#8 of 8
Qwilr0%#– of 8
The full enterprise standing →

What the models said about Proposify

Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of six in this category shown.

“General proposal tools like Proposify and PandaDoc: These excel at sales proposals but fall short for true RFPs.” Grok 4.1 Fast · negative prompt · hard negative
“Proposify and PandaDoc - They are proposal tools rather than RFP tools, and the difference matters.” Llama 4 Maverick · negative prompt · hard negative
“Proposify and PandaDoc are frequently cited as problematic choices for RFP response work” Kimi K2 · negative prompt · hard negative
“I'd generally recommend Proposify as the default choice.” GPT-5.4 mini · paraphrase prompt · first choice
“I'd recommend Proposify as the default choice” Perplexity Sonar · paraphrase prompt · first choice
“Start with Proposify for sales proposals” GPT-6 Luna · paraphrase 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
Also compared

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.