RFP response software for enterprise buyers
Asked as “RFP response software”, and as “proposal management software”, on behalf of an enterprise B2B company. 52 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each. Added to the October 2026 Edition on October 4, 2026; its answers are read by the distilled judge (ai-indexes-judge-qwen3-14b-run3), not the claude-opus-5 judge of the earlier categories: how the two compare.
Standing · first-choice share
56%
Clear leader
56Responsive13Loopio10AutoRFP.ai21others
56% of first choices, clear leader.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrant
Show the three products at 0%, ordered by negative rate
Bars are the share of first choices, 0 to 100Every product with at least 10 labels here. Every product name links to its product page.
For buyers
All twenty-eight head-to-head pages: the top eight products, each against each
Loopio vs ProposifyLoopio vs AutoRFP.aiLoopio vs 1upLoopio vs QwilrPandaDoc vs ResponsivePandaDoc vs DeepRFPPandaDoc vs ProposifyPandaDoc vs AutoRFP.aiPandaDoc vs 1upPandaDoc vs QwilrResponsive vs DeepRFPResponsive vs ProposifyResponsive vs AutoRFP.aiResponsive vs 1upResponsive vs QwilrDeepRFP vs ProposifyDeepRFP vs AutoRFP.aiDeepRFP vs 1upDeepRFP vs QwilrProposify vs AutoRFP.aiProposify vs 1upProposify vs QwilrAutoRFP.ai vs 1upAutoRFP.ai vs Qwilr1up vs Qwilr
One product takes 56% of first choices here, so the chart would put seven markers in one corner and one at the far edge. The two measurements it plots are columns in the standing above: share, and the negative label rate. Two products carry a negative rate above 25% in this category.
What they warned about
Nine of fourteen models held their first choice under the paraphrase. Mistral Small, Llama 4 Maverick, GLM 4.7 FlashX, MiniMax M2.5 and Muse Glimmer 30B changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
PandaDoc69%
11 of 16 labels negative · 9 of 14 models · 7 hard negative
“Tools like Proposify and PandaDoc are primarily designed for general proposal creation and lack the specialized features required for RFP response management” Mistral Small, negative prompt
Responsive15%
10 of 65 labels negative · 8 of 14 models · 3 hard negative
“Avoid per-seat pricing models like Responsive, which historically starts near $5,000/year for a small team and scales per user” Claude Haiku 4.5, budget prompt
Upland Qvidian20%
9 of 45 labels negative · 8 of 14 models · 3 hard negative
“Legacy enterprise tier tools like Qvidian are being squeezed because the AI layer was retrofitted onto a 50-year platform” Claude Haiku 4.5, negative prompt
Proposify70%
7 of 10 labels negative · 7 of 14 models · 5 hard negative
“Tools like Proposify and PandaDoc are primarily designed for general proposal creation and lack the specialized features required for RFP response management” Mistral Small, negative prompt
What they cite
Citations exist only for the models that return a source list: fourteen of the fourteen in this edition, and all six flagship models on the expanded tier.
Sites the answers cite
78 of 84 answers in this category came back with a source list, from 14 of 14 models: citations where the model returns them, or the search results it consulted. 1122 links across 176 sites, every framing counted. Ranked by the number of answers carrying the site or page. None of the 252 answers across every segment cited this index's own page for the category.
vendor site · Responsive50 answers · 103 citations · 14 models
vendor site · Inventive48 answers · 109 citations · 13 models
vendor site · Loopio38 answers · 60 citations · 13 models
29 answers · 46 citations · 12 models
vendor site · Storyflow29 answers · 29 citations · 10 models
vendor site · AutoRFP.ai27 answers · 50 citations · 10 models
27 answers · 27 citations · 11 models
vendor site · SiftHub24 answers · 29 citations · 8 models
vendor site · Gartner22 answers · 29 citations · 12 models
vendor site · SparrowGenie20 answers · 28 citations · 11 models
vendor site · AutogenAI20 answers · 26 citations · 11 models
vendor site · Guideflow19 answers · 19 citations · 10 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
29 answers · 10 models
28 answers · 11 models
27 answers · 11 models
25 answers · 10 models
21 answers · 11 models
18 answers · 9 models
17 answers · 10 models
16 answers · 8 models
15 answers · 8 models
14 answers · 10 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best rfp response software”, “rfp response software”. US estimates from DataForSEO and Google's Ads Transparency Center. A small company's site, or a mid-sized company's site for its flagship, is marked company; a product on a large parent's site (Google, Microsoft) has no site figures. A column with no figures for this category is left out, and an empty cell means none were seen, not none exist. Two measurements side by side: neither is read as the cause of the other.
| Company and products | Share | Own site cited | Name searches, Google | AI search demand, est. | Organic visits | Paid search a month, est. | Google ads, last 30 days | Best Google position |
|---|---|---|---|---|---|---|---|---|
| Responsive responsive.io Responsive 56%, Responsive formerly RFPIO 2%, Responsive.io 2% | 60% | 213 | 12,100 | 210,141 | 37,620 | 16 | 5 | |
| Loopio loopio.com | 13% | 220 | 3,600 | 80 | 4,640 | 26 | ||
| AutoRFP.ai autorfp.ai | 10% | 76 | 70 | 0 | 38,771 | 2 | 2 | |
| Inventive AI inventive.ai | 8% | 50 | 260 | 558 | 9,514 | $694 | 4 | 7 |
| DealHub dealhub.io | 4% | 175 | 1,900 | 83 | 319,299 | $372 | 62 | |
| QorusDocs qorusdocs.com | 2% | 22 | ||||||
| Conga conga.com Conga 2%, Conga CPQ 0% | 2% | 108 | 27,100 | 2,882 | 46,363 | $224 | 120 | |
| PandaDoc pandadoc.com | 2% | 527 | 60,500 | 510 | 425,196 | $42,516 | 119 | |
| Upland Qvidian uplandsoftware.com | 0% | 124 | 40 | 1 | 67,149 | $1,203 | 26 | |
| Arphie arphie.ai | 0% | 33 | 320 | 0 | 9,807 | 13 |
Google's top ten for the two searches hold 13 sites; 4 of them are among the sites the models cited here (autorfp.ai, inventive.ai, responsive.io, sifthub.io). The first result for “best rfp response software” is kantiv.com.
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.ShowHide
How they answered
Six framings of the same buying question, each sent to every model in a fresh session with search on. One row per model, so a row shows whether it held its answer under rewording, what it named when cost was the constraint, and what it argued against. Computed from the raw judge labels.
ShowHideModelDirect“What is the best RFP response software for an enterprise B2B company?”Paraphrase“Which proposal management software would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade RFP response tools and how do they differ?”Budget-constrained“What is the best RFP response software for a large company that needs predictable total cost across thousands of users?”Scale-constrained“We are a 5,000 person company with SSO, SOC 2 and procurement review requirements evaluating a RFP response software. What should we look at?”Negative“Which RFP response tools should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5ResponsiveResponsiveHeldLoopioInventive AIagainst: Responsiveno first choiceagainst: ChatGPT, MS Copilot, Responsive, Upland Qvidian
Five alternatives
AutoRFP, Inventive AI, Loopio, Realm, Upland QvidianFour alternatives
Conga CPQ, DealHub, Loopio, PandaDocFive alternatives
Arphie, AutogenAI, Responsive, Thalamus AI, Upland QvidianOne alternative
AutoRFP.aiGPT-5.4 miniResponsiveagainst: Upland QvidianResponsiveHeldResponsiveagainst: AutoRFPResponsiveno first choicenothing named
One alternative
LoopioTwo alternatives
Loopio, Upland QvidianTwo alternatives
Loopio, Upland QvidianTwo alternatives
Loopio, Upland QvidianGemini 3.5 FlashResponsiveResponsiveHeldagainst: Upland QvidianLoopio, ResponsiveAutoRFP.aiagainst: Loopio, ResponsiveResponsiveagainst: PandaDoc, Proposify
Seven alternatives
Arphie, AutoRFP.ai, GovDash, Inventive AI, Loopio, Procurement Sciences, Upland QvidianThree alternatives
AutogenAI, Loopio, QorusDocsFour alternatives
AutoRFP.ai, Procurement Sciences AI, Upland Qvidian, VisibleThreadTwo alternatives
Inventive AI, TribbleTwo alternatives
Loopio, QorusDocsPerplexity SonarResponsiveResponsiveHeldResponsiveagainst: AutoRFP.ai, Rohirrim, TribbleResponsiveno first choiceagainst: ChatGPT, Claude
Four alternatives
AutoRFP.ai, Loopio, OrbitShift rfpOS, Upland QvidianFour alternatives
DealHub, GetAccept, PandaDoc, Upland QvidianThree alternatives
Loopio, RocketDocs, Upland QvidianOne alternative
LoopioGrok 4.1 FastResponsiveResponsiveHeldLoopioAutoRFP.aiagainst: Loopio, Responsive, Upland QvidianLoopio, Responsiveagainst: AutoRFP.ai, Better Proposals, Loopio, PandaDoc
Two alternatives
Loopio, Thalamus AITwo alternatives
Loopio, Upland QvidianThree alternatives
Arphie, Responsive, Upland QvidianOne alternative
Inventive AIOne alternative
ArphieMistral SmallResponsiveDealHubChangedLoopioResponsiveno first choiceagainst: Conveyor, GovDash, GovWin, PandaDoc, Proposify
Two alternatives
Inventive AI, SteerlabFour alternatives
QorusDocs, RFP360, Responsive, Thalamus AIDeepSeek V4 FlashResponsiveResponsiveHeldagainst: PandaDocResponsiveagainst: PandaDocAutoRFP.aiagainst: LoopioResponsiveagainst: ChatGPT, PandaDoc
Two alternatives
Loopio, Upland QvidianTwo alternatives
Conga, LoopioThree alternatives
AutoRFP.ai, Loopio, Upland QvidianOne alternative
ResponsiveThree alternatives
AutoRFP.ai, Loopio, Upland QvidianLlama 4 Maverickno first choiceDealHubChangedUpland QvidianResponsiveno first choiceagainst: Responsive
Three alternatives
GetAccept, HoneyBook, OneflowTwo alternatives
Loopio, ResponsiveQwen 3.7 FlashLoopio, ResponsiveLoopio, ResponsiveHeldLoopioAutoRFP.aiagainst: Loopio, Responsive, Upland Qvidianno first choiceagainst: PandaDoc, Proposify
Three alternatives
Qvida, Seismic, XymityFour alternatives
Conga, DealHub, PandaDoc, Upland QvidianThree alternatives
AutoRFP.ai, Responsive, Upland QvidianOne alternative
Inventive AIKimi K2ResponsiveResponsiveHeldagainst: PandaDoc, ProposifyResponsiveInventive AIagainst: Loopio, Responsive, Upland QvidianResponsiveagainst: ChatGPT, Conveyor, Loopio, Ombud, Responsive, Upland Qvidian
Two alternatives
Loopio, Upland QvidianTwo alternatives
Loopio, Upland QvidianThree alternatives
AutoRFP.ai, Loopio, Upland QvidianOne alternative
AutoRFP.aiThree alternatives
Loopio, QorusDocs, RocketDocsGLM 4.7 FlashXLoopio, Responsive.ioLoopioChangedResponsive, Upland QvidianInventive AIno first choiceagainst: PandaDoc, Proposify, Storyflow
One alternative
BidSparqThree alternatives
Responsive, Steerlab, Upland QvidianSix alternatives
Arphie, AutoRFP.ai, Inventive AI, Loopio, SiftHub, TribbleThree alternatives
Loopio, Responsive, TribbleMiniMax M2.5Loopio, ResponsiveConga, PandaDocChangedLoopioLoopio, Responsiveagainst: AutoRFP.aino first choiceagainst: PandaDoc, Proposify
Three alternatives
AutoRFP.ai, Tribble, Upland QvidianThree alternatives
Loopio, Proposify, QwilrFour alternatives
Proposify, Responsive, SiftHub, Upland QvidianOne alternative
Inventive AIGPT-6 LunaResponsiveResponsiveHeldResponsiveagainst: ConveyorAutoRFP.aiagainst: Loopiono first choiceagainst: Loopio, Responsive, Upland Qvidian
One alternative
LoopioTwo alternatives
Loopio, Upland QvidianThree alternatives
Arphie, Loopio, Upland QvidianTwo alternatives
Inventive AI, ResponsiveMuse Glimmer 30BResponsive formerly RFPIOQorusDocsChangedagainst: IcertisResponsive formerly RFPIOInventive AIagainst: Loopio, Responsive, Upland Qvidianno first choiceagainst: PandaDoc, Proposify, Storyflow
Two alternatives
Loopio, Upland QvidianThree alternatives
Loopio, Responsive, Upland QvidianTwo alternatives
Loopio, Upland QvidianTwo alternatives
Arphie, AutoRFP.aiBold is the first choiceAlternatives are counted; the count opens them.What the answer argued against
The record
One row per call: the version string exactly as returned, whether the model searched, sources cited, and latency. Full answer text is in the free responses file. Download the record
Eighty-four rows: every prompt, every model, every answer.
| Prompt | Model | Version string | Time (UTC) | Searched | Sources | Latency |
|---|---|---|---|---|---|---|
| Direct recommendation | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 00:53 | yes | 9 | 7 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 23:36 | yes | 3 | 5 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:42 | yes | 14 | 27 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-05 00:16 | yes | 18 | 5 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 23:19 | yes | 23 | 11 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 23:28 | yes | 5 | 3 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 00:24 | yes | 22 | 61 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 23:12 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 23:36 | no | 0 | 24 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-05 00:16 | yes | 13 | 22 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 22:28 | yes | 21 | 101 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 22:17 | yes | 22 | 21 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-04 23:38 | yes | 2 | 19 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-05 00:21 | yes | 15 | 21 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 23:51 | yes | 9 | 11 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 00:35 | yes | 4 | 8 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:26 | yes | 23 | 25 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-04 23:18 | yes | 18 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 23:33 | yes | 22 | 9 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 22:18 | yes | 12 | 6 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 22:22 | yes | 22 | 27 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 23:15 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:41 | yes | 8 | 29 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 23:18 | yes | 24 | 27 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 00:29 | yes | 14 | 16 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:11 | yes | 10 | 23 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-04 22:18 | yes | 3 | 12 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:49 | yes | 15 | 22 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 00:36 | yes | 19 | 12 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-05 00:26 | yes | 3 | 6 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 23:10 | yes | 22 | 32 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-05 00:42 | yes | 19 | 4 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 23:22 | yes | 24 | 11 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 23:26 | yes | 20 | 12 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 00:11 | yes | 24 | 46 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 23:43 | yes | 5 | 3 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-05 00:42 | yes | 20 | 58 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 22:47 | yes | 25 | 59 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 23:04 | yes | 14 | 54 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 22:15 | yes | 15 | 26 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-05 00:32 | yes | 6 | 23 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 23:36 | yes | 15 | 24 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 22:20 | yes | 17 | 10 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 22:32 | yes | 5 | 6 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:57 | yes | 19 | 27 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-04 23:01 | yes | 19 | 4 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 22:17 | yes | 19 | 10 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-05 00:47 | yes | 5 | 3 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 23:33 | yes | 21 | 45 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 22:25 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-05 00:32 | yes | 23 | 92 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 23:11 | yes | 18 | 26 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 00:02 | yes | 15 | 23 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:36 | yes | 15 | 44 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-05 00:04 | yes | 4 | 18 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:33 | yes | 21 | 31 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-05 00:43 | no | 0 | 7 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 23:56 | yes | 0 | 8 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 22:26 | no | 0 | 17 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-05 01:02 | yes | 17 | 6 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 22:26 | yes | 23 | 13 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 23:54 | no | 0 | 9 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 23:38 | yes | 22 | 56 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 22:17 | yes | 5 | 5 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:18 | no | 0 | 28 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-05 00:47 | yes | 10 | 18 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 00:22 | yes | 22 | 53 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-05 00:36 | yes | 5 | 15 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-04 22:40 | yes | 1 | 20 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:47 | yes | 14 | 21 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 22:18 | yes | 18 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 23:04 | yes | 4 | 6 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-05 00:15 | yes | 21 | 30 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-04 23:17 | yes | 20 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 23:07 | yes | 22 | 12 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 22:16 | yes | 5 | 5 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-05 00:57 | yes | 23 | 37 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-05 00:56 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 23:18 | yes | 5 | 24 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 23:01 | yes | 25 | 22 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-05 00:17 | yes | 21 | 30 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:00 | yes | 17 | 42 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-05 00:13 | yes | 2 | 26 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-05 00:47 | yes | 17 | 22 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
Inventive read as Inventive AI
Unresolved, counted raw
GovWin
MS Copilot
OrbitShift rfpOS
Procurement Sciences AI (Awarded AI)
Qvida
RM Nimbus
Realm
Rohirrim
SEQUESTO
Xymity
Discontinued, still offered
No shut-down product was recommended here.