Procure-to-pay for small business buyers
Asked as “procure-to-pay platform”, and as “purchasing software”, on behalf of a small B2B company. 64 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
28%
Contested · Procurify 19%
28Precoro19Procurify17Ramp36others
28% of first choices, contested.
Since September 2026↗new leaderNew leader since September 2026: Precoro (28%) replaces Ramp (27% then, 17% now), 11 points clear, past the 10-point floor.Precoro leads at 28%, replacing Ramp, which led at 27% and stands at 17% now: 11 points clear, past the floor.
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.
Small business
Precoro28%Contested↗new leaderNew leader since September 2026: Precoro (28%) replaces Ramp (27% then, 17% now), 11 points clear, past the 10-point floor.This pageMid-market
Procurify42%Clear leader▼−3Since September 2026: 45% → 42%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.Standing →Enterprise
Coupa43%Clear leader▼−1Since September 2026: 42% → 41%, −1 point. Inside the 10-point floor: within noise. Read over the models both editions asked.Standing →
Precoro28%Contested↗new leaderNew leader since September 2026: Precoro (28%) replaces Ramp (27% then, 17% now), 11 points clear, past the 10-point floor.This pageMid-marketProcurify42%Clear leader▼−3Since September 2026: 45% → 42%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.Standing →EnterpriseCoupa43%Clear leader▼−1Since September 2026: 42% → 41%, −1 point. Inside the 10-point floor: within noise. Read over the models both editions asked.Standing →The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for a small B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01Precoro28%5%64accepted challenger▲+5Since September 2026: 24% → 28%, +5 points. Inside the 10-point floor: within noise. Read over the models both editions asked.24% → 28%
Precoro28%5%64accepted challenger▲+5Since September 2026: 24% → 28%, +5 points. Inside the 10-point floor: within noise. Read over the models both editions asked.24% → 28%02Procurify19%7%56accepted challenger▲+5Since September 2026: 16% → 21%, +5 points. Inside the 10-point floor: within noise. Read over the models both editions asked.16% → 21%
Procurify19%7%56accepted challenger▲+5Since September 2026: 16% → 21%, +5 points. Inside the 10-point floor: within noise. Read over the models both editions asked.16% → 21%03
Ramp17%0%37accepted challenger▼−10Since September 2026: 27% → 17%, −10 points. Past the 10-point floor: movement. Read over the models both editions asked.27% → 17%
Ramp17%0%37accepted challenger▼−10Since September 2026: 27% → 17%, −10 points. Past the 10-point floor: movement. Read over the models both editions asked.27% → 17%04
Tradogram11%0%43accepted challenger▲+3Since September 2026: 10% → 13%, +3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.10% → 13%
Tradogram11%0%43accepted challenger▲+3Since September 2026: 10% → 13%, +3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.10% → 13%05
BILL6%0%23accepted challenger▲+2Since September 2026: 6% → 8%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.6% → 8%
BILL6%0%23accepted challenger▲+2Since September 2026: 6% → 8%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.6% → 8%06
Spendwise5%0%18accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 4%
Spendwise5%0%18accepted challenger▲+4Since September 2026: 0% → 4%, +4 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 4%07
ProcureDesk2%8%24accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.2% → 2%
ProcureDesk2%8%24accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.2% → 2%08
Order.co2%0%13accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 2%
Order.co2%0%13accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 2%Show the three products at 0%, ordered by negative rate
11
SAP Ariba0%90%29criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%
SAP Ariba0%90%29criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%10Coupa0%75%32criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%
Coupa0%75%32criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%09
Kissflow Procurement0%30%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%
Kissflow Procurement0%30%10criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%The floor is 10 points of share, measured: how far the models move a leader on their own when the same questions are asked twice with nothing changed. A larger change is movement; a smaller one is noise, and both are shown. Movement is read over the twelve models both editions asked; GPT-6 Luna, Muse Glimmer 30B joined this edition and are in the standing but not yet in the comparison. How the floor is measured
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
Procurify vs SpendwiseProcurify vs CoupaProcurify vs ProcureDeskProcurify vs ZipPrecoro vs RampPrecoro vs TradogramPrecoro vs SpendwisePrecoro vs CoupaPrecoro vs ProcureDeskPrecoro vs ZipRamp vs TradogramRamp vs SpendwiseRamp vs CoupaRamp vs ProcureDeskRamp vs ZipTradogram vs SpendwiseTradogram vs CoupaTradogram vs ProcureDeskTradogram vs ZipSpendwise vs CoupaSpendwise vs ProcureDeskSpendwise vs ZipCoupa vs ProcureDeskCoupa vs ZipProcureDesk vs Zip
Recommended versus criticized
Every product with at least 10 labels here, on both axes. The 30% line names a quadrant, not the verdict above: that one needs more than 40%.
Criticized challengerCriticized default
Negative label rate →
0102030405060708091011Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative40%
Key
01Precoro28%
Precoro28%02Procurify19%
Procurify19%03Ramp17%
Ramp17%04Tradogram11%
Tradogram11%05BILL6%
BILL6%06Spendwise5%
Spendwise5%07ProcureDesk2%
ProcureDesk2%08Order.co2%
Order.co2%09Kissflow Procurement0%
Kissflow Procurement0%10Coupa0%
Coupa0%11SAP Ariba0%
SAP Ariba0%What they warned about
Zero of fourteen models held their first choice under the paraphrase. 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 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.
SAP Ariba90%
26 of 29 labels negative · 13 of 14 models · 17 hard negative
“The main platforms to be cautious about are **SAP Ariba, Coupa, Jaggaer, Ivalua, and GEP SMART**, because they are positioned for large, complex procurement environments” Perplexity Sonar, negative prompt
Coupa75%
24 of 32 labels negative · 12 of 14 models · 17 hard negative
“Platforms to Avoid or Be Cautious About ... Enterprise-Only Platforms - Coupa, SAP Ariba, Oracle Fusion Cloud Procurement, GEP SMART” GLM 4.7 FlashX, negative prompt
Oracle Fusion Cloud Procurement100%
7 of 7 labels negative · 7 of 14 models · 6 hard negative
“Enterprise S2P suites that are overkill / cost-prohibitive for SMBs... Oracle Fusion $175 to $625 per user monthly” Muse Glimmer 30B, negative prompt
GEP SMART86%
6 of 7 labels negative · 6 of 14 models · 6 hard negative
“GEP SMART requires significant customization for smaller businesses and is primarily designed for large enterprises” Claude Haiku 4.5, 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
80 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. 1082 links across 211 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 · G239 answers · 68 citations · 13 models
vendor site · Ramp39 answers · 48 citations · 13 models
vendor site · ProcureDesk37 answers · 84 citations · 12 models
vendor site · Spendflo35 answers · 50 citations · 12 models
vendor site · Tradogram32 answers · 34 citations · 12 models
vendor site · Precoro31 answers · 37 citations · 12 models
vendor site · G228 answers · 32 citations · 11 models
24 answers · 36 citations · 12 models
24 answers · 27 citations · 11 models
20 answers · 29 citations · 9 models
20 answers · 26 citations · 9 models
vendor site · BILL19 answers · 20 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.
32 answers · 12 models
31 answers · 12 models
25 answers · 10 models
20 answers · 11 models
20 answers · 9 models
19 answers · 11 models
17 answers · 8 models
17 answers · 11 models
16 answers · 10 models
14 answers · 8 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 procure-to-pay platform”, “procure-to-pay platform”, “procurement platforms”. 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 |
|---|---|---|---|---|---|---|---|---|
| Precoro precoro.com | 28% | 283 | 1,000 | 3 | 82,966 | 86 | ||
| Procurify procurify.com | 19% | 220 | 4,400 | 43 | 62,225 | $282 | 14 | |
| Ramp ramp.com | 17% | 1042 | 246,000 | 49,733 | 770,056 | $13,511 | 120 | |
| Tradogram tradogram.com | 11% | 151 | 880 | 4 | 208,129 | 1 | ||
| BILL bill.com BILL 6%, BILL AP/AR 2% | 8% | 444 | 2,740,000 | 1,063,001 | 1,783,039 | $199,231 | 119 | |
| Spendwise spendwise.com | 5% | 42 | 720 | 3 | 401 | 2 | ||
| Zoho parent site Zoho Inventory 2%, Zoho Procurement 2% | 3% | 8 | 6,600 | 330 | ||||
| ProcureDesk procuredesk.com | 2% | 57 | 720 | 1 | 11,677 | 5 | 5 | |
| Order.co order.co | 2% | 28 | 1,600 | 7 | 64,386 | $369 | 59 | |
| Teampay paystand.com | 2% | 16 | 590 | 11 | 59,075 | $55,504 | 51 |
Google's top ten for the three searches hold 24 sites; 3 of them are among the sites the models cited here (g2.com, learn.g2.com, procuredesk.com). The first result for “best procure-to-pay platform” is gartner.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 procure-to-pay platform for a small B2B company?”Paraphrase“Which purchasing software would you recommend to a small business that sells to other businesses?”Comparative“What are the top procurement platforms for a small team and how do they differ?”Budget-constrained“What is the best procure-to-pay platform for a small company with a tight budget?”Scale-constrained“We are a 30 person company evaluating a procure-to-pay platform. What should we look at?”Negative“Which procurement platforms should a small business avoid or be cautious about?”
Claude Haiku 4.5no first choiceTradogramChangedPrecoroPrecorono first choiceagainst: Coupa, GEP SMART, Pipefy, SAP Ariba
Three alternatives
Order.co, Precoro, ProcurifyFive alternatives
Pipefy, ProcureDesk, Procurify, Spendwise, TradogramThree alternatives
BILL, Cflow, Zoho ProcurementsGPT-5.4 miniProcurifyagainst: Oracle Fusion Cloud Procurement, SAP AribaPrecoroChangedPrecoroagainst: SAP AribaBILL AP/ARagainst: ProcureDeskno first choiceagainst: Agiliron, SAP Ariba
Five alternatives
Precoro, Ramp, Rippling Finance, Stampli, TipaltiFour alternatives
Order.co, ProcureDesk, Procurify, TradogramTwo alternatives
Procurify, TeampayFour alternatives
ProcurementExpress.com, Procurify, Ramp, TradogramGemini 3.5 FlashPrecoroagainst: Coupa, SAP AribaTradogramChangedPrecoroagainst: Coupa, SAP AribaRampagainst: Coupa, SAP AribaPrecoro, Procurifyagainst: Coupa, Jaggaer, SAP Aribaagainst: Coupa, Oracle Fusion Cloud Procurement, SAP Ariba
Five alternatives
Order.co, Procurify, Ramp, Tipalti, TradogramTwo alternatives
BILL, PrecoroFour alternatives
Order.co, ProcureDesk, Procurify, TradogramThree alternatives
Precoro, ProcureDesk, TradogramTwo alternatives
BILL, RampPerplexity SonarBILL, RampBILLChangedRampRampno first choiceagainst: Coupa, GEP SMART, Ivalua, Jaggaer, SAP Ariba
Two alternatives
Precoro, TeampayThree alternatives
Precoro, Procurify, SpendwiseFive alternatives
BILL, ProcureDesk, ProcurementExpress.com, Procurify, TeampayTwo alternatives
Precoro, TeampayGrok 4.1 FastPrecoro, Procurifyagainst: CoupaPrecoroChangedPrecoro, SpendwiseSpendwiseOrder.co, Precoro, Procurify, Rampagainst: Coupa, SAP Aribaagainst: Alibaba.com, Coupa, DHgate, GEP SMART, Global Sources, Ivalua, Made-in-China, Oracle Fusion Cloud Procurement, Procurify, SAP Ariba
Three alternatives
Nanonets, PLANERGY, RampThree alternatives
ProcureDesk, Procurify, Zoho InventoryThree alternatives
Order.co, Procurify, RampTwo alternatives
Precoro, TradogramMistral SmallBILL, ProcurifyPrecoro, ProcurifyChangedPrecoro, Procurifyagainst: Coupa, SAP AribaRampno first choicenothing named
Three alternatives
Cflow, Payhawk, StampliTwo alternatives
Order.co, TradogramEight alternatives
Kissflow Procurement, Order.co, ProcureDesk, Ramp, Spendwise, Tradogram, Xero, Zoho BooksTwo alternatives
BILL, SpendwiseDeepSeek V4 FlashRampTradogramChangedagainst: Procurifyno first choiceagainst: Coupa, Jaggaer, SAP AribaZoho Procurementagainst: Coupa, Precoro, ProcureDesk, Procurify, ZipPrecoroagainst: Coupa, Ivalua, SAP Aribaagainst: Coupa, GEP SMART, Ivalua, Oracle Fusion Cloud Procurement, SAP Ariba
Four alternatives
BILL, Precoro, ProcurementExpress.com, ProcurifyTwo alternatives
Precoro, SpendwiseSix alternatives
Precoro, ProcureDesk, Procurify, Ramp, Tradogram, Zoho ProcurementTwo alternatives
Ramp, TradogramThree alternatives
ProcureDesk, Procurify, SpendfloLlama 4 MaverickProcurifyRampChangedSpendfloPrecorono first choiceagainst: Coupa, Kissflow Procurement, SAP Ariba
Three alternatives
BILL, Precoro, SpendwiseSeven alternatives
ControlHub, Coupa, Kissflow Procurement, Order.co, Precoro, Procurify, TradogramFour alternatives
Precoro, Procurify, Ramp, SpendwiseTwo alternatives
Spendwise, TradogramQwen 3.7 FlashBILLCin7 CoreChangedPrecoro, Rampagainst: Coupa, Kissflow Procurement, SAP AribaSpendwisePrecoro, Procurify, Tradogramagainst: Alibaba, Oracle NetSuite, SAP Ariba
Four alternatives
Brex, QuickBooks Online, Ramp, RipplingFour alternatives
BILL, Odoo, Zoho Inventory, Zoho OneTwo alternatives
ProcureDesk, TradogramFour alternatives
Precoro, Tradogram, Zoho Creator, Zoho ExpenseFour alternatives
BILL, Brex, Ramp, TipaltiKimi K2PrecoroPrecoro, TradogramChangedRamp, Tradogramagainst: Kissflow ProcurementRamp, Tradogramagainst: Coupa, Oracle Fusion Cloud Procurement, Precoro, SAP AribaPrecoro, Procurifyagainst: Coupa, SAP Aribaagainst: Alibaba, DHgate, Global Sources, Made-in-China
Four alternatives
Nanonets, Procurify, Ramp, TipaltiThree alternatives
Procurify, Ramp, Zoho Purchase OrderThree alternatives
Precoro, ProcureDesk, ProcurifyThree alternatives
BILL, Fraxion, MelioThree alternatives
Ramp, Spendflo, TradogramGLM 4.7 FlashXPrecoro, ProcurifyProcureDeskChangedPrecoro, ProcureDeskTradogramagainst: Procurifyno first choiceagainst: Coupa, GEP SMART, Oracle Fusion Cloud Procurement, SAP Ariba
Three alternatives
ProcureDesk, Spendwise, TradogramTwo alternatives
BILL, PrecoroFour alternatives
AuraVMS, ProcurementExpress.com, Spendwise, TradogramTwo alternatives
Ramp, TeampayMiniMax M2.5no first choiceProcurifyChangedPrecoro, TradogramRampno first choiceagainst: Coupa, Ivalua, Jaggaer, SAP Ariba
Three alternatives
Precoro, Teampay, TradogramOne alternative
ProcurifyThree alternatives
BILL, Precoro, TeampayTwo alternatives
Precoro, ProcurifyGPT-6 LunaPrecoro, RampZoho InventoryChangedRampagainst: Precoro, ZipOdoono first choiceagainst: Amazon Business, samregistration.com
One alternative
BILLOne alternative
Cin7Three alternatives
Order.co, ProcurementExpress.com, ProcurifyOne alternative
RampMuse Glimmer 30BRamp, TeampayinFlow InventoryChangedPrecoro, Procurifyagainst: Coupa, SAP AribaPrecoro, SpendwisePrecoro, Procurifyagainst: Coupa, SAP Aribaagainst: Coupa, GEP SMART, Ivalua, Oracle Fusion Cloud Procurement, SAP Ariba
Two alternatives
Precoro, ProcurifyThree alternatives
Precoro, Tradogram, Zoho InventorySix alternatives
Fairmarkit, ProcIndex, ProcureDesk, ProcurementExpress.com, Spendwise, TradogramOne alternative
RampBold 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 | 2026-10-01 10:45 | no | 0 | 3 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:22 | yes | 4 | 7 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:37 | yes | 10 | 23 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 10:47 | yes | 16 | 4 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:07 | yes | 25 | 7 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:09 | yes | 5 | 6 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:25 | yes | 22 | 24 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:39 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:02 | yes | 10 | 23 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:17 | yes | 16 | 25 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:49 | yes | 24 | 36 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:58 | yes | 16 | 44 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:37 | yes | 3 | 22 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:20 | yes | 13 | 16 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:47 | yes | 9 | 7 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:28 | yes | 3 | 4 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:40 | yes | 18 | 22 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 08:40 | yes | 17 | 2 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:10 | yes | 23 | 6 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:08 | yes | 5 | 4 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:42 | yes | 19 | 20 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:55 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:06 | no | 0 | 29 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:02 | yes | 20 | 19 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 07:49 | yes | 15 | 15 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:41 | yes | 9 | 40 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:06 | yes | 3 | 10 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:54 | yes | 21 | 26 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:50 | yes | 9 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:20 | yes | 5 | 10 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:52 | yes | 16 | 21 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 11:05 | yes | 19 | 4 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:52 | yes | 20 | 8 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:01 | yes | 5 | 8 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:32 | yes | 20 | 36 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:11 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:18 | yes | 15 | 30 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:52 | yes | 18 | 29 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:44 | yes | 17 | 25 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:43 | yes | 18 | 30 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:44 | yes | 7 | 38 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:30 | yes | 14 | 28 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:43 | yes | 17 | 9 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:58 | yes | 3 | 4 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:59 | yes | 26 | 27 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 07:40 | yes | 20 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:18 | yes | 23 | 7 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:17 | yes | 10 | 4 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:19 | yes | 21 | 28 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:35 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:49 | yes | 13 | 39 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:59 | yes | 19 | 23 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:49 | yes | 22 | 25 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:32 | yes | 5 | 33 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:00 | yes | 2 | 18 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:18 | yes | 15 | 14 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:23 | yes | 16 | 10 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 07:54 | no | 0 | 6 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:14 | yes | 6 | 24 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 10:12 | yes | 15 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:27 | yes | 19 | 8 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:50 | no | 0 | 11 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:50 | yes | 17 | 30 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:21 | yes | 5 | 5 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:57 | yes | 9 | 47 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:23 | yes | 20 | 30 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:19 | yes | 13 | 17 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:18 | yes | 5 | 18 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:00 | yes | 3 | 15 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:04 | yes | 13 | 17 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:03 | yes | 18 | 14 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:23 | yes | 4 | 7 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:16 | yes | 16 | 24 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 11:14 | yes | 16 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:54 | yes | 23 | 7 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:10 | yes | 13 | 5 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:22 | yes | 25 | 32 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:00 | yes | 5 | 3 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:52 | yes | 12 | 48 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:06 | yes | 23 | 24 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:57 | yes | 22 | 23 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:24 | yes | 13 | 34 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:02 | yes | 5 | 17 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:50 | yes | 21 | 33 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
Bill.com read as BILL
Kissflow read as Kissflow Procurement
Oracle read as Oracle Fusion Cloud Procurement
Oracle Fusion read as Oracle Fusion Cloud Procurement
SAP Ariba Buying and Invoicing read as SAP Ariba
Zoho Procure read as Zoho Procurement
Unresolved, counted raw
Agiliron
Alibaba.com
ProcIndex
Procee
SAM.gov
Wonnda
Zoho Purchase Order
inFlow Inventory
samregistration.com
Discontinued, still offered
No shut-down product was recommended here.