Strategic sourcing for enterprise buyers
Asked as “strategic sourcing software”, and as “e-sourcing and RFP tool”, on behalf of an enterprise B2B company. 53 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
36%
Contested · Coupa 26%
36SAP Ariba26Coupa21Ivalua17others
36% of first choices, contested.
Since September 2026↗new leaderNew leader since September 2026: SAP Ariba (37%) replaces Coupa (35% then, 28% now), 9 points clear, inside the 10-point floor.SAP Ariba leads at 37%, replacing Coupa, which led at 35% and stands at 28% now: 9 points clear, inside the floor, so the swap reads as unsettled.
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
Tradogram31%Contested▼−9Since September 2026: 45% → 35%, −9 points. Inside the 10-point floor: within noise. Read over the models both editions asked.Standing →Mid-market
oboloo15%Contested▼−3Since September 2026: 17% → 14%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.Standing →Enterprise
SAP Ariba36%Contested↗new leaderNew leader since September 2026: SAP Ariba (37%) replaces Coupa (35% then, 28% now), 9 points clear, inside the 10-point floor.This page
Tradogram31%Contested▼−9Since September 2026: 45% → 35%, −9 points. Inside the 10-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketoboloo15%Contested▼−3Since September 2026: 17% → 14%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.Standing →EnterpriseSAP Ariba36%Contested↗new leaderNew leader since September 2026: SAP Ariba (37%) replaces Coupa (35% then, 28% now), 9 points clear, inside the 10-point floor.This pageThe 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 rateLabelsQuadrantSince September 2026
01SAP Ariba36%20%61endorsed leader▲+2Since September 2026: 35% → 37%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.35% → 37%
SAP Ariba36%20%61endorsed leader▲+2Since September 2026: 35% → 37%, +2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.35% → 37%02
Coupa26%13%60accepted challenger▼−7Since September 2026: 35% → 28%, −7 points. Inside the 10-point floor: within noise. Read over the models both editions asked.35% → 28%
Coupa26%13%60accepted challenger▼−7Since September 2026: 35% → 28%, −7 points. Inside the 10-point floor: within noise. Read over the models both editions asked.35% → 28%03
Ivalua21%4%53accepted challenger▲+12Since September 2026: 8% → 20%, +12 points. Past the 10-point floor: movement. Read over the models both editions asked.8% → 20%
Ivalua21%4%53accepted challenger▲+12Since September 2026: 8% → 20%, +12 points. Past the 10-point floor: movement. Read over the models both editions asked.8% → 20%04
GEP SMART6%5%37accepted challenger▲+5Since September 2026: 2% → 7%, +5 points. Inside the 10-point floor: within noise. Read over the models both editions asked.2% → 7%
GEP SMART6%5%37accepted challenger▲+5Since September 2026: 2% → 7%, +5 points. Inside the 10-point floor: within noise. Read over the models both editions asked.2% → 7%05
Jaggaer2%2%47accepted challenger▼−6Since September 2026: 8% → 2%, −6 points. Inside the 10-point floor: within noise. Read over the models both editions asked.8% → 2%
Jaggaer2%2%47accepted challenger▼−6Since September 2026: 8% → 2%, −6 points. Inside the 10-point floor: within noise. Read over the models both editions asked.8% → 2%06
Workday Strategic Sourcing2%7%15accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.2% → 2%
Workday Strategic Sourcing2%7%15accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.2% → 2%Show the two products at 0%, ordered by negative rate
07
Zycus0%7%15accepted challenger▼−4Since September 2026: 4% → 0%, −4 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 0%
Zycus0%7%15accepted challenger▼−4Since September 2026: 4% → 0%, −4 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 0%08
Oracle Fusion Cloud Procurement0%0%11accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%
Oracle Fusion Cloud Procurement0%0%11accepted 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.
All twenty-eight head-to-head pages: the top eight products, each against each
oboloo vs Market Dojooboloo vs Ivaluaoboloo vs GEP SMARToboloo vs CoupaPrecoro vs TradogramPrecoro vs ProcurifyPrecoro vs Market DojoPrecoro vs IvaluaPrecoro vs GEP SMARTPrecoro vs CoupaTradogram vs ProcurifyTradogram vs Market DojoTradogram vs IvaluaTradogram vs GEP SMARTTradogram vs CoupaProcurify vs Market DojoProcurify vs IvaluaProcurify vs GEP SMARTProcurify vs CoupaMarket Dojo vs IvaluaMarket Dojo vs GEP SMARTMarket Dojo vs CoupaIvalua vs GEP SMARTIvalua vs CoupaGEP SMART vs Coupa
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 →
0102030405060708Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative50%
Key
01SAP Ariba36%
SAP Ariba36%02Coupa26%
Coupa26%03Ivalua21%
Ivalua21%04GEP SMART6%
GEP SMART6%05Jaggaer2%
Jaggaer2%06Workday Strategic Sourcing2%
Workday Strategic Sourcing2%07Zycus0%
Zycus0%08Oracle Fusion Cloud Procurement0%
Oracle Fusion Cloud Procurement0%What they warned about
Seven of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, GPT-5.4 mini, Mistral Small, Qwen 3.7 Flash, Kimi K2, 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.
SAP Ariba20%
12 of 61 labels negative · 9 of 14 models · 2 hard negative
“**Avoid**: SAP Ariba for this specific use case — while powerful, it has the highest TCO and most complex pricing” Kimi K2, budget prompt
Coupa13%
8 of 60 labels negative · 7 of 14 models
“Coupa — Enterprise implementations routinely cost $400K–$1.5M+, and that's before adding ongoing integration, training, and support costs that often exceed initial projections.” DeepSeek V4 Flash, negative prompt
Precoro100%
5 of 5 labels negative · 4 of 14 models · 2 hard negative
“Non-scalable or SMB-focused tools (e.g., basic procure-to-pay like Precoro or Procurify): Fine for mid-market but lack depth for enterprise complexity” Grok 4.1 Fast, negative prompt
Procurify67%
4 of 6 labels negative · 4 of 14 models · 1 hard negative
“SMB procure-to-pay | Lacks enterprise RFx depth, optimization | Precoro, Procurify” Grok 4.1 Fast, 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. 1215 links across 304 sites, every framing counted. Ranked by the number of answers carrying the site or page. 2 of the 252 answers across every segment cited this index's own page for the category; the method page measures whether that reading tilts an answer.
vendor site · Spendflo40 answers · 48 citations · 12 models
vendor site · G231 answers · 47 citations · 12 models
vendor site · Suplari28 answers · 28 citations · 11 models
vendor site · Guideflow25 answers · 32 citations · 11 models
vendor site · Ivalua21 answers · 26 citations · 11 models
20 answers · 33 citations · 10 models
vendor site · Sourceforge20 answers · 24 citations · 11 models
18 answers · 20 citations · 7 models
vendor site · Zycus17 answers · 23 citations · 10 models
17 answers · 22 citations · 10 models
16 answers · 24 citations · 9 models
16 answers · 18 citations · 7 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.
28 answers · 11 models
24 answers · 11 models
22 answers · 10 models
16 answers · 8 models
15 answers · 10 models
15 answers · 10 models
14 answers · 7 models
12 answers · 9 models
12 answers · 6 models
12 answers · 7 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 strategic sourcing software”, “sourcing tools”, “strategic sourcing 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 |
|---|---|---|---|---|---|---|---|---|
| SAP Ariba sap.com | 36% | 519 | 8,100 | 554 | 2,214,514 | $1,251 | 23 | 6 |
| Coupa coupa.com | 26% | 674 | 60,500 | 1,210 | 41,319 | $339 | 91 | 2 |
| Ivalua ivalua.com | 21% | 258 | 3,600 | 87 | 35,515 | 80 | ||
| GEP gep.com GEP SMART 6%, GEP Quantum Intelligence 2% | 8% | 169 | 880 | 26 | 54,424 company | 51 | ||
| Jaggaer jaggaer.com Jaggaer 2%, JAGGAER Sourcing 0% | 2% | 181 | 5,400 | 218 | 21,919 | $82 | 9 | |
| Workday parent site Workday Strategic Sourcing 2% | 2% | 28 | 1,220,000 | 23,848 | ||||
| Market Dojo marketdojo.com | 2% | 31 | 260 | 8 | 261 | $121 | 3 | |
| SAP Ariba Sourcing Suite | 2% | |||||||
| SAP Ariba Strategic Procurement / SAP Ariba Sourcing | 2% | |||||||
| Zycus zycus.com | 0% | 63 | 2,400 | 49 | 23,901 | 16 | 7 |
Google's top ten for the three searches hold 20 sites; 3 of them are among the sites the models cited here (gartner.com, tropicapp.io, zycus.com). The first result for “best strategic sourcing software” is procurementmag.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 strategic sourcing software for an enterprise B2B company?”Paraphrase“Which e-sourcing and RFP tool would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade sourcing tools and how do they differ?”Budget-constrained“What is the best strategic sourcing 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 strategic sourcing software. What should we look at?”Negative“Which sourcing tools should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5SAP AribaCoupa, SAP AribaChangedno first choiceCoupa, Ivaluano first choicenothing named
Four alternatives
Coupa, GEP SMART, Ivalua, JaggaerTwo alternatives
Ivalua, ZycusTwo alternatives
Keelvar, SAP AribaGPT-5.4 miniIvalua, SAP AribaSAP Ariba Strategic Procurement / SAP Ariba SourcingChangedno first choiceagainst: BravoSolution, Determine, Proactis, SirionIvalua, SAP Ariba Sourcing Suiteno first choicenothing named
Three alternatives
Coupa, Jaggaer, ZipFour alternatives
Coupa, Ivalua, Jaggaer, Oracle Fusion Cloud ProcurementThree alternatives
Coupa, JAGGAER Sourcing, SAP AribaTwo alternatives
Coupa, PowerAdvocateGemini 3.5 FlashCoupaCoupaHeldCoupaWorkday Strategic Sourcingagainst: Coupa, GEP SMART, SAP Aribano first choicenothing named
Five alternatives
GEP SMART, Ivalua, Jaggaer, Keelvar, SAP AribaFive alternatives
Loopio, Responsive, SAP Ariba, Workday Strategic Sourcing, ZipFour alternatives
Jaggaer, Keelvar, SAP Ariba, Workday Strategic SourcingThree alternatives
Ivalua, Tradogram, ZipPerplexity SonarSAP AribaSAP AribaHeldSAP Aribaagainst: OliveSAP Aribano first choicenothing named
Three alternatives
Coupa, GEP Quantum Intelligence, IvaluaOne alternative
CoupaTwo alternatives
Ivalua, ZycusThree alternatives
Coupa, Jaggaer, Workday Strategic SourcingGrok 4.1 FastSAP AribaSAP AribaHeldno first choiceSAP Aribaagainst: Precoro, ProcurePortno first choiceagainst: Coupa, Eightfold AI, Precoro, Procurify, SAP Ariba
Four alternatives
Coupa, GEP SMART, Ivalua, JaggaerThree alternatives
Coupa, Ivalua, JaggaerFive alternatives
Coupa, GEP SMART, Ivalua, Jaggaer, ZycusFour alternatives
Ivalua, Jaggaer, SAP Ariba, Workday Strategic SourcingMistral SmallSAP AribaCoupa, SAP AribaChangedCoupa, SAP AribaIvaluaagainst: Coupano first choiceagainst: Archlet, Coupa, Ivalua, Jaggaer, SAP Ariba, Zycus
Three alternatives
Coupa, GEP SMART, IvaluaFour alternatives
GEP SMART, Ivalua, Jaggaer, Scout RFPOne alternative
JaggaerDeepSeek V4 FlashCoupaCoupaHeldCoupaagainst: Workday Strategic SourcingCoupaagainst: Market Dojo, Prokuria, SAP Aribano first choiceagainst: Coupa, Ivalua, SAP Ariba
Five alternatives
GEP SMART, Ivalua, Jaggaer, Oracle Fusion Cloud Procurement, SAP AribaFour alternatives
GEP SMART, Ivalua, Jaggaer, SAP AribaFive alternatives
GEP SMART, Ivalua, Jaggaer, Oracle Fusion Cloud Procurement, SAP AribaOne alternative
IvaluaLlama 4 Maverickno first choiceno first choiceHeldno first choiceno first choiceno first choicenothing named
Five alternatives
Ivalua, MeRLIN, ProcureKey, SAP Ariba, ZycusQwen 3.7 FlashSAP AribaCoupaChangedSAP AribaGEP SMARTagainst: Oracle Fusion, SAP Aribano first choicenothing named
Five alternatives
Coupa, GEP NEXXE™, Ivalua, Jaggaer, Oracle Fusion Cloud ProcurementTwo alternatives
Jaggaer, SAP AribaFour alternatives
Coupa, GEP SMART, Ivalua, JaggaerOne alternative
CoupaKimi K2SAP AribaCoupa, IvaluaChangedagainst: SAP Aribano first choiceCoupa, Ivaluaagainst: SAP AribaGEP SMART, Ivalua, Jaggaeragainst: Coupa, Ramp Procurement, SAP Ariba, Zipagainst: Precoro, Procurify, Tradogram
Three alternatives
Coupa, GEP SMART, IvaluaTwo alternatives
GEP SMART, JaggaerSix alternatives
Coupa, GEP SMART, Ivalua, Jaggaer, SAP Ariba, ZycusOne alternative
GEP SMARTOne alternative
KeelvarGLM 4.7 FlashXSAP AribaSAP AribaHeldCoupaGEP SMARTagainst: Coupa, SAP Aribano first choiceagainst: Precoro, Procurify, Tradogram
Two alternatives
Coupa, ZycusFive alternatives
Coupa, GEP SMART, Ivalua, Loopio, QvidianThree alternatives
GEP SMART, Ivalua, SAP AribaOne alternative
Market DojoMiniMax M2.5Ivalua, SAP AribaCoupaChangedno first choiceno first choiceCoupa, Ivalua, SAP Aribaagainst: Coupa, GEP SMART, SAP Ariba
Four alternatives
Coupa, GEP SMART, Jaggaer, ServiceNow Source-to-Pay OperationsOne alternative
SAP AribaGPT-6 LunaIvaluaIvaluaHeldno first choiceGEP Quantum Intelligenceagainst: SAP Aribano first choicenothing named
Four alternatives
Coupa, Jaggaer, Oracle Fusion Cloud Procurement, SAP AribaThree alternatives
Coupa, GEP SMART, SAP AribaSeven alternatives
Coupa, GEP Quantum Intelligence, Ivalua, Jaggaer, Keelvar, Oracle Fusion Cloud Procurement, SAP AribaOne alternative
IvaluaMuse Glimmer 30BSAP AribaCoupa, SAP AribaChangedHireEZ, SeekOutagainst: LinkedIn RecruiterMarket Dojono first choiceagainst: Alibaba, Oracle Taleo, Precoro, Procurify, Tradogram
Four alternatives
Coupa, GEP SMART, Ivalua, JaggaerOne alternative
JaggaerThree alternatives
Gem, Juicebox, SAP AribaFive alternatives
Coupa, GEP SMART, Ivalua, Jaggaer, SAP AribaBold 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 10:08 | yes | 17 | 9 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:34 | yes | 5 | 5 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:18 | yes | 14 | 20 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 11:07 | yes | 19 | 5 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:35 | yes | 24 | 8 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:22 | yes | 5 | 4 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:26 | yes | 21 | 36 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:26 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 08:20 | no | 0 | 35 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:30 | yes | 15 | 24 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:18 | yes | 24 | 33 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:22 | yes | 13 | 31 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:34 | yes | 5 | 15 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 07:55 | yes | 23 | 24 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:54 | yes | 16 | 10 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:13 | yes | 5 | 7 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:30 | yes | 22 | 31 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 10:40 | yes | 20 | 2 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:18 | yes | 25 | 9 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:02 | yes | 5 | 4 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:49 | yes | 24 | 27 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:31 | yes | 5 | 4 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:21 | yes | 10 | 47 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:54 | yes | 20 | 20 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:08 | yes | 24 | 27 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:52 | yes | 17 | 54 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:45 | yes | 4 | 23 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:57 | yes | 14 | 21 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:56 | yes | 17 | 9 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:38 | yes | 5 | 10 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:06 | yes | 17 | 22 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 10:08 | yes | 17 | 4 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:48 | yes | 22 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:55 | yes | 19 | 12 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:40 | yes | 25 | 48 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:35 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:32 | yes | 10 | 30 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:27 | yes | 23 | 30 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:49 | yes | 18 | 24 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:07 | yes | 25 | 51 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:33 | yes | 7 | 24 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:59 | yes | 15 | 30 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 07:59 | yes | 15 | 8 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 07:44 | yes | 5 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:18 | yes | 20 | 33 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 08:55 | yes | 17 | 4 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:06 | yes | 24 | 10 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:45 | yes | 20 | 7 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:43 | yes | 24 | 37 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:24 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:03 | yes | 10 | 54 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:00 | yes | 20 | 29 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:25 | yes | 22 | 64 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:59 | yes | 18 | 75 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:01 | yes | 5 | 24 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:23 | yes | 24 | 64 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:51 | yes | 19 | 13 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:52 | no | 0 | 7 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:48 | yes | 9 | 22 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 08:31 | yes | 15 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:11 | yes | 14 | 8 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:15 | no | 0 | 9 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:08 | yes | 24 | 36 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:28 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:33 | no | 0 | 31 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:37 | yes | 19 | 44 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:59 | yes | 14 | 22 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:22 | yes | 5 | 17 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:22 | yes | 3 | 23 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:18 | yes | 23 | 50 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:14 | yes | 9 | 7 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:21 | yes | 4 | 7 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:50 | yes | 15 | 27 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 08:56 | yes | 20 | 3 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:02 | yes | 23 | 11 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:38 | yes | 19 | 9 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:31 | yes | 23 | 43 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:33 | yes | 5 | 3 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:14 | no | 0 | 29 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:40 | yes | 24 | 25 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:54 | yes | 25 | 54 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:08 | yes | 21 | 47 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:28 | no | 0 | 2 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:09 | yes | 22 | 34 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
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Category-scoped readings
GEP read as GEP SMART
Oracle read as Oracle Fusion Cloud Procurement
Oracle Procurement read as Oracle Fusion Cloud Procurement
Oracle Procurement Cloud read as Oracle Fusion Cloud Procurement
Unresolved, counted raw
Eightfold
GEP NEXXE™
JAGGAER Sourcing
Leoforce
Mercell
PRMAI
Percepta
PowerAdvocate
Precura
RFP365
SAP Ariba Sourcing Suite
SAP Ariba Strategic Procurement / SAP Ariba Sourcing
Sirion
Discontinued, still offered
No shut-down product was recommended here.