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RFP response software · October 2026 Edition

Responsive vs Qwilr

Three of fourteen models named Responsive first on the direct prompt; zero named Qwilr. Responsive was named by fourteen of the fourteen models and Qwilr by ten and Responsive carries 46 labels and Qwilr 13, so the shares are not directly comparable.

Responsive

accepted challenger

founded 2015. Named in two categories this edition.

Qwilr

accepted challenger

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

First-choice share14%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate20%8%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#3#8A position in a field of 10; printed, not drawn.
Labels4613A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, Responsive 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 Responsive · Loopio vs Qwilr · PandaDoc vs Responsive

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.
ResponsiveFirst choices, of fourteen modelsQwilr
Direct301 against Responsive
Paraphrase11
Comparative60
Budget-constrained003 against Responsive
Scale-constrained40
Negative105 against Responsive · 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, Responsive and Qwilr were named in the same answer thirty-eight times, of the 219 answers naming Responsive and the 177 naming Qwilr. In those answers Qwilr took the first choice two times and Responsive six.

Every model, every framing

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

The direct prompt

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

Responsive first, Qwilr not the choice

3 of 14 modelsQwilr was named in the answer but not as the choice, or not at all.
Grok 4.1 FastResponsive alternatives: Loopio
Mistral SmallLoopio, Responsive alternatives: Expedience Proposal Software, Proposify
MiniMax M2.5Loopio, Responsive alternatives: SiftHub, Upland Qvidian

Neither was the first choice, one was named

8 of 14 modelsThe answer put something else first and named one of the two as an alternative.
GPT-5.4 miniLoopio alternatives: Responsive
Perplexity SonarLoopio alternatives: Responsive
DeepSeek V4 FlashLoopio alternatives: AutoRFP.ai, Proposify, QorusDocs, Responsive
Qwen 3.7 FlashAutoRFP.ai, Loopio alternatives: Qwilr, Upland Qvidian
Kimi K2Loopio alternatives: AutoRFP.ai, PandaDoc, Responsive
GLM 4.7 FlashXLoopio alternatives: Responsive, Upland Qvidian
GPT-6 LunaLoopio alternatives: Responsive
Muse Glimmer 30BLoopio alternatives: AutoRFP.ai, Responsive

Neither was named

3 of 14 modelsThe answer made no first choice from these two in this category.
Claude Haiku 4.5Tribble alternatives: AutoRFP.ai, Loopio, Steerlab
Gemini 3.5 FlashTribble alternatives: AutoRFP.ai, Loopio, Steerlab
Llama 4 MaverickExpedience Proposal Software alternatives: AutoRFP.ai, Conveyor

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
Responsive leads by four points.
Responsive4%#7 of 14
Qwilr0%#12 of 14
The full small business standing →
Mid-marketThe figures above
Responsive leads by twelve points.
Responsive14%#3 of 10
Qwilr2%#8 of 10
The full mid-market standing →
Enterprise
Responsive leads by fifty-six points.
Responsive56%#1 of 8
Qwilr0%#– of 8
The full enterprise standing →

What the models said about Responsive

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

“Be Cautious With: Responsive (formerly RFPIO) ... This is the most criticized major platform based on consistent negative feedback” Qwen 3.7 Flash · negative prompt · hard negative
“The AI assistant that generates RFP responses isn't always reliable, and users say it often repeats content from the library instead of creating accurate, tailored answers.” Claude Haiku 4.5 · negative prompt · soft negative
“It has a very steep learning curve and can be intimidating for casual SME reviewers. Implementation can take anywhere from 1 to 2 months.” Gemini 3.5 Flash · direct prompt · soft negative
“Shortlist 3-5 Tools: Responsive (enterprise-grade collaboration), Loopio (content-focused), Arphie/1up (AI-heavy for speed), Upland Qvidian (analytics-rich).” Grok 4.1 Fast · scale 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
“focus on those specifically designed for RFP workflows like Loopio, Responsive (formerly RFPIO), or Qvidian” MiniMax M2.5 · negative 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.