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RFP response software · October 2026 Edition

DeepRFP vs AutoRFP.ai

Zero of fourteen models named DeepRFP first on the direct prompt; one named AutoRFP.ai. DeepRFP was named by eight of the fourteen models and AutoRFP.ai by eleven and DeepRFP carries 10 labels and AutoRFP.ai 21, so the shares are not directly comparable.

DeepRFP

accepted challenger

Named in one category this edition.

AutoRFP.ai

accepted challenger

Named in two categories this edition.

First-choice share7%2%Of first choices across the direct, paraphrase, budget and scale prompts, 0 to 100.
Negative rate0%5%Negative labels as a share of the product's labels, 0 to 100.
Rank in category#4#6A position in a field of 10; printed, not drawn.
Labels1021A count; the two differ.
The two percentage rows are drawn on one 0 to 100 track, DeepRFP 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 DeepRFP · Loopio vs AutoRFP.ai · PandaDoc vs DeepRFP

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.
DeepRFPFirst choices, of fourteen modelsAutoRFP.ai
Direct01
Paraphrase00
Comparative00
Budget-constrained401 against AutoRFP.ai
Scale-constrained00
Negative00
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, DeepRFP and AutoRFP.ai were named in the same answer seventeen times, of the 38 answers naming DeepRFP and the 76 naming AutoRFP.ai. In those answers AutoRFP.ai took the first choice one time and DeepRFP seven.

Every model, every framing

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

The direct prompt

The plain question, one answer per model, grouped by where DeepRFP and AutoRFP.ai stood in it.

AutoRFP.ai first, DeepRFP not the choice

1 of 14 modelsDeepRFP was named in the answer but not as the choice, or not at all.
Qwen 3.7 FlashAutoRFP.ai, Loopio alternatives: Qwilr, Upland Qvidian

Neither was the first choice, one was named

6 of 14 modelsThe answer put something else first and named one of the two as an alternative.
Claude Haiku 4.5Tribble alternatives: AutoRFP.ai, Loopio, Steerlab
Gemini 3.5 FlashTribble alternatives: AutoRFP.ai, Loopio, Steerlab
DeepSeek V4 FlashLoopio alternatives: AutoRFP.ai, Proposify, QorusDocs, Responsive
Llama 4 MaverickExpedience Proposal Software alternatives: AutoRFP.ai, Conveyor
Kimi K2Loopio alternatives: AutoRFP.ai, PandaDoc, Responsive
Muse Glimmer 30BLoopio alternatives: AutoRFP.ai, Responsive

Neither was named

7 of 14 modelsThe answer made no first choice from these two in this category.
GPT-5.4 miniLoopio alternatives: Responsive
Perplexity SonarLoopio alternatives: Responsive
Grok 4.1 FastResponsive alternatives: Loopio
Mistral SmallLoopio, Responsive alternatives: Expedience Proposal Software, Proposify
GLM 4.7 FlashXLoopio alternatives: Responsive, Upland Qvidian
MiniMax M2.5Loopio, Responsive alternatives: SiftHub, Upland Qvidian
GPT-6 LunaLoopio alternatives: 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
DeepRFP leads by fourteen points.
DeepRFP16%#2 of 14
AutoRFP.ai2%#8 of 14
The full small business standing →
Mid-marketThe figures above
DeepRFP leads by five points.
DeepRFP7%#4 of 10
AutoRFP.ai2%#6 of 10
The full mid-market standing →
Enterprise
The order flips: AutoRFP.ai leads at enterprise.
AutoRFP.ai10%#3 of 8
DeepRFP0%#– of 8
The full enterprise standing →

What the models said about DeepRFP

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

“The best RFP response software for a company with a limited budget is DeepRFP, as it is the low-friction choice for freelancers or very small teams on a tight budget.” Llama 4 Maverick · budget prompt · first choice
“DeepRFP and iQuoteXpress offer the most transparent, truly affordable pricing for budget-conscious companies.” Claude Haiku 4.5 · budget prompt · first choice
“My recommendation: Start with DeepRFP or BreezeDocs if you need AI assistance” Kimi K2 · budget prompt · first choice

What the models said about AutoRFP.ai

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

“priced out of AutoRFP.ai's $899/month Scale plan” DeepSeek V4 Flash · budget prompt · soft negative
“points to Loopio and AutoRFP.ai as the top two contenders for this specific segment” Qwen 3.7 Flash · direct prompt · first choice
“Best for: High-growth SaaS and financial services companies requiring extreme accuracy and source transparency.” Gemini 3.5 Flash · direct prompt · alternative
“Prioritize tools like Loopio, Responsive, or AI-native ones (e.g., 1up, AutoRFP.ai) with proven traceability.” Grok 4.1 Fast · negative prompt · alternative
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.