Strategic sourcing
Asked as “strategic sourcing software”, and as “e-sourcing and RFP tool”, on behalf of a mid-market B2B company. 52 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
15%
Contested · Precoro 13%
15oboloo13Precoro13Procurify58others
15% of first choices, contested.
Since September 2026▲+3Since September 2026: 11% → 14%, +3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.oboloo held the lead, +3 points on 11%, inside the 10-point 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
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.This pageEnterprise
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.Standing →
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.This pageEnterpriseSAP 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.Standing →The standing
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. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince September 2026
01oboloo15%9%11accepted challenger▲+3Since September 2026: 11% → 14%, +3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.11% → 14%
oboloo15%9%11accepted challenger▲+3Since September 2026: 11% → 14%, +3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.11% → 14%02
Precoro13%0%23accepted challenger▼−3Since September 2026: 17% → 14%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.17% → 14%
Precoro13%0%23accepted challenger▼−3Since September 2026: 17% → 14%, −3 points. Inside the 10-point floor: within noise. Read over the models both editions asked.17% → 14%03Tradogram13%7%14accepted challenger▼−1Since September 2026: 15% → 14%, −1 point. Inside the 10-point floor: within noise. Read over the models both editions asked.15% → 14%
Tradogram13%7%14accepted challenger▼−1Since September 2026: 15% → 14%, −1 point. Inside the 10-point floor: within noise. Read over the models both editions asked.15% → 14%04
Procurify13%0%11accepted challenger▲+9Since September 2026: 4% → 14%, +9 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 14%
Procurify13%0%11accepted challenger▲+9Since September 2026: 4% → 14%, +9 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 14%05
Market Dojo6%0%16accepted challenger=heldSince September 2026: 4% → 5%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 5%
Market Dojo6%0%16accepted challenger=heldSince September 2026: 4% → 5%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 5%06
Ivalua4%19%16accepted challenger=heldSince September 2026: 4% → 5%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 5%
Ivalua4%19%16accepted challenger=heldSince September 2026: 4% → 5%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.4% → 5%07
GEP SMART4%21%14accepted challenger▼−6Since September 2026: 11% → 5%, −6 points. Inside the 10-point floor: within noise. Read over the models both editions asked.11% → 5%
GEP SMART4%21%14accepted challenger▼−6Since September 2026: 11% → 5%, −6 points. Inside the 10-point floor: within noise. Read over the models both editions asked.11% → 5%08
Coupa4%47%30criticized challenger▼−2Since September 2026: 6% → 5%, −2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.6% → 5%
Coupa4%47%30criticized challenger▼−2Since September 2026: 6% → 5%, −2 points. Inside the 10-point floor: within noise. Read over the models both editions asked.6% → 5%09
Jaggaer2%15%13accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.2% → 2%
Jaggaer2%15%13accepted 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 five products at 0%, ordered by negative rate
14SAP Ariba0%69%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%
SAP Ariba0%69%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%13
LinkedIn Recruiter0%21%14accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%
LinkedIn Recruiter0%21%14accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 10-point floor: within noise. Read over the models both editions asked.0% → 0%12
Gem0%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%
Gem0%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%10
HireEZ0%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%
HireEZ0%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%11
SeekOut0%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%
SeekOut0%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.
For buyers
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 →
0102030405060708091011121314Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative30%
Key
01oboloo15%
oboloo15%02Precoro13%
Precoro13%03Tradogram13%
Tradogram13%04Procurify13%
Procurify13%05Market Dojo6%
Market Dojo6%06Ivalua4%
Ivalua4%07GEP SMART4%
GEP SMART4%08Coupa4%
Coupa4%09Jaggaer2%
Jaggaer2%10HireEZ0%
HireEZ0%11SeekOut0%
SeekOut0%12Gem0%
Gem0%13LinkedIn Recruiter0%
LinkedIn Recruiter0%14SAP Ariba0%
SAP Ariba0%What they warned about
One 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, 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 Ariba69%
22 of 32 labels negative · 9 of 14 models · 5 hard negative
“Mid-sized companies should avoid heavyweight enterprise legacy platforms (like SAP Ariba or Oracle) because they are highly expensive, complex” Gemini 3.5 Flash, paraphrase prompt
Coupa47%
14 of 30 labels negative · 8 of 14 models · 2 hard negative
“**SAP Ariba & Coupa** — Powerful but typically overkill and overpriced for mid-sized companies” Kimi K2, paraphrase prompt
Alibaba100%
4 of 4 labels negative · 4 of 14 models
“Even on massive platforms like Alibaba, "Verified" badges can sometimes be paid advertisements. Always verify ISO certifications independently.” Qwen 3.7 Flash, negative prompt
GEP SMART21%
3 of 14 labels negative · 3 of 14 models · 1 hard negative
“NOT Recommended for Limited Budgets” DeepSeek V4 Flash, budget 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
75 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. 1030 links across 272 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 · Spendflo33 answers · 37 citations · 12 models
32 answers · 36 citations · 12 models
vendor site · G230 answers · 61 citations · 12 models
vendor site · Sourceforge30 answers · 50 citations · 12 models
25 answers · 26 citations · 11 models
vendor site · Guideflow17 answers · 18 citations · 9 models
16 answers · 17 citations · 9 models
14 answers · 16 citations · 9 models
vendor site · Pin13 answers · 17 citations · 10 models
13 answers · 13 citations · 7 models
vendor site · Juicebox12 answers · 12 citations · 8 models
12 answers · 12 citations · 9 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
23 answers · 11 models
20 answers · 10 models
18 answers · 10 models
14 answers · 9 models
14 answers · 9 models
12 answers · 9 models
11 answers · 6 models
10 answers · 7 models
10 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 |
|---|---|---|---|---|---|---|---|
| oboloo oboloo.com | 15% | 37 | 20 | 0 | 11,787 | ||
| Precoro precoro.com | 13% | 283 | 1,000 | 3 | 82,966 | 86 | |
| Tradogram tradogram.com | 13% | 151 | 880 | 4 | 208,129 | 1 | |
| Procurify procurify.com | 13% | 220 | 4,400 | 43 | 62,225 | $282 | 14 |
| Market Dojo marketdojo.com | 6% | 31 | 260 | 8 | 261 | $121 | 3 |
| Vendorful vendorful.com | 6% | 13 | |||||
| Workday parent site Workday Strategic Sourcing 6% | 6% | 28 | 1,220,000 | 23,848 | |||
| Ivalua ivalua.com | 4% | 258 | 3,600 | 87 | 35,515 | 80 | |
| GEP gep.com GEP SMART 4% | 4% | 169 | 880 | 26 | 54,424 company | 51 | |
| Loopio loopio.com | 4% | 15 | 3,600 | 80 | 4,640 | 26 |
Google's top ten for the three searches hold 20 sites; 2 of them are among the sites the models cited here (pin.com, tropicapp.io). 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 a mid-market B2B company?”Paraphrase“Which e-sourcing and RFP tool would you recommend to a mid-sized B2B company?”Comparative“What are the top sourcing tools and how do they differ?”Budget-constrained“What is the best strategic sourcing software for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a strategic sourcing software. What should we look at?”Negative“Which sourcing tools should I avoid or be cautious about?”
Claude Haiku 4.5PrecoroVendorfulChangedPinagainst: LinkedIn RecruiterTradogramno first choicenothing named
Four alternatives
Coupa, ProcurePort, SAP Ariba, ZycusFive alternatives
Arphie, AutoRFP.ai, Market Dojo, Precoro, SteerlabFour alternatives
Coupa, Gem, SAP Ariba, SeekOutFive alternatives
Precoro, SourceRFX, TYASuite Procurement, eBuyerAssist, obolooGPT-5.4 miniProcurifyagainst: Coupa, Ivalua, Jaggaer, SAP AribaIvaluaChangedno first choicePrecoro, Tradogramagainst: Coupa, SAP Aribano first choicenothing named
Two alternatives
Archlet, Bid ManagementTwo alternatives
Responsive, SAP AribaOne alternative
ProcurifyGemini 3.5 FlashWorkday Strategic Sourcingagainst: Coupa, SAP AribaMarket DojoChangedagainst: Oracle Fusion Cloud Procurement, SAP AribaJaggaeragainst: SAP AribaTradogramagainst: Coupa, SAP Ariba, ZycusTradogram, Workday Strategic Sourcingagainst: Coupa, SAP Aribanothing named
Four alternatives
Archlet, Market Dojo, Tradogram, ZipSix alternatives
Arphie, AutoRFP.ai, Cotiss, DeepStream, Loopio, ResponsiveThree alternatives
Coupa, Ivalua, ZipThree alternatives
Market Dojo, ProcurePort, obolooFour alternatives
Cotiss, GEP SMART, Precoro, ZycusPerplexity SonarGEP SMARTVendorfulChangedagainst: obolooCoupa, SAP AribaMarket Dojono first choiceagainst: Capital IQ, PitchBook, SourceScrub, ZoomInfo
Three alternatives
Precoro, Procol, SAP Ariba Strategic Sourcing SuiteThree alternatives
BusinessBid, Precoro, Sourcing ForceThree alternatives
Archlet, Market Dojo, ScanmarketOne alternative
ProcolGrok 4.1 FastProcurifyagainst: SAP AribaTradogramChangedLinkedIn Recruiteragainst: Entelo, Manatalobolooagainst: Coupa, Tradogramno first choiceagainst: SAP Aribaagainst: Alibaba, Dux-Soup, Global Sources, Grata, PhantomBuster, PitchBook, Waalaxy
One alternative
PrecoroTwo alternatives
Precoro, VendorfulThree alternatives
HireEZ, Pin, SeekOutOne alternative
e-ProcureMistral SmallProcurifyLoopio, Scout RFPChangedno first choiceoboloono first choicenothing named
Four alternatives
Ivalua, MeRLIN, SAP Ariba, ScanmarketThree alternatives
Market Dojo, Proactis, ZycusThree alternatives
Entelo, HeroHunt.ai, SquarePegDeepSeek V4 FlashProcurifyagainst: IvaluaTradogramChangedagainst: Sourcing Acumen, Workday Strategic Sourcingno first choiceobolooagainst: Coupa, GEP SMART, Keelvar, SAP Aribano first choiceagainst: Coupa, SAP Aribaagainst: KASPR, LinkedIn Recruiter
Four alternatives
Fairmarkit, GEP SMART, Market Dojo, PrecoroThree alternatives
Loopio, Precoro, ProposifyTwo alternatives
AuraVMS, PrecoroSix alternatives
GEP SMART, Ivalua, Jaggaer, Market Dojo, Tradogram, Workday Strategic SourcingLlama 4 Maverickno first choiceno first choiceHeldno first choiceno first choiceno first choicenothing named
Qwen 3.7 FlashCoupaagainst: SAP AribaFairmarkitChangedagainst: SAP Aribano first choiceBastionagainst: Coupa, SAP AribaIvalua, Jaggaer, Proactisagainst: Coupa, SAP Aribaagainst: Alibaba
Three alternatives
Jaggaer, Precoro, ZycusThree alternatives
Coupa, Market Dojo, PowerRFPFive alternatives
Coupa, Jaggaer, Keelvar, Körber, SAP AribaFive alternatives
Airtable, Kissflow, Monday.com, Scoutbee, XoraOne alternative
SpendwiseKimi K2Precoro, Procurifyagainst: Coupa, GEP SMART, SAP AribaPrecoroChangedagainst: Asana, Coupa, Monday.com, SAP AribaHireEZagainst: LinkedIn Recruiterobolooagainst: Kissflowno first choiceagainst: 1688.com, Alibaba, DHgate, Metaview
Two alternatives
Ivalua, ZipThree alternatives
Bonfire, Procurify, ScoutbeeThree alternatives
Fetcher, Gem, SeekOutThree alternatives
OpenProcurement, Tradogram, Zoho ProcurementsGLM 4.7 FlashXCoupa, GEP SMARTPrecoroChangedGem, HireEZobolooagainst: Coupa, SAP Aribano first choiceagainst: Alibaba, CJdropshipping, Global Sources, Jaggaer, SAP Ariba
Seven alternatives
Ivalua, Precoro, ProcureWare, SAP Ariba, Scanmarket, ServiceNow Source-to-Pay Operations, TradogramSix alternatives
DeepStream, GEP SMART, Market Dojo, Procurify, Scanmarket, ZycusFive alternatives
AmazingHiring, Juicebox, LinkedIn Recruiter, Loxo, SeekOutThree alternatives
Market Dojo, Precoro, ProquraMiniMax M2.5Procurify, Scanmarketagainst: SAP AribaLoopio, PrecoroChangedno first choiceoboloono first choicenothing named
Two alternatives
ProcureKey, ScanmarketOne alternative
TradogramTwo alternatives
Spendflo, VendorfulGPT-6 LunaWorkday Strategic SourcingMarket DojoChangedLinkedIn Recruiteroboloono first choicenothing named
Two alternatives
Coupa, GEP SMARTTwo alternatives
Fairmarkit, ResponsiveThree alternatives
Gem, HireEZ, SeekOutOne alternative
AcquirellMuse Glimmer 30BProcurifyagainst: SAP AribaPrecoro, VendorfulChangedHireEZ, SeekOutTradogram, oboloono first choiceagainst: Coupa, GEP SMART, Ivalua, SAP Aribanothing named
Four alternatives
Basware, GEP SMART, Precoro, ZycusTwo alternatives
Loopio, Workday Strategic SourcingFour alternatives
Eightfold AI, Fetcher, Gem, JuiceboxThree alternatives
Market Dojo, Prokuria, TYASuite ProcurementThree alternatives
Fairmarkit, Keelvar, Market DojoBold 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 11:27 | yes | 9 | 7 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:35 | yes | 3 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:04 | yes | 21 | 22 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 08:48 | yes | 17 | 3 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:09 | yes | 19 | 8 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:51 | yes | 14 | 6 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:44 | yes | 23 | 29 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:41 | yes | 5 | 1 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:04 | yes | 10 | 46 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:26 | yes | 11 | 23 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:36 | yes | 15 | 73 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:44 | yes | 12 | 19 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:04 | yes | 3 | 16 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 07:33 | yes | 24 | 30 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:15 | yes | 17 | 10 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:07 | yes | 3 | 8 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:10 | yes | 15 | 25 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 09:33 | yes | 18 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:04 | yes | 21 | 6 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:28 | yes | 10 | 7 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:54 | yes | 21 | 38 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:36 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:51 | yes | 10 | 66 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:56 | yes | 19 | 21 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:48 | yes | 15 | 22 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:58 | yes | 12 | 26 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:43 | yes | 3 | 18 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:38 | yes | 12 | 22 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:17 | yes | 9 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:46 | yes | 5 | 6 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:47 | yes | 11 | 23 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 08:08 | yes | 20 | 5 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 07:30 | yes | 24 | 7 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:59 | yes | 12 | 7 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:01 | yes | 24 | 67 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:36 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:44 | yes | 15 | 49 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:21 | yes | 15 | 25 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:16 | yes | 24 | 142 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:16 | yes | 13 | 21 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:13 | yes | 4 | 14 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:09 | yes | 13 | 28 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:38 | yes | 9 | 7 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:29 | yes | 4 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:26 | yes | 22 | 25 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 10:43 | yes | 16 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:15 | yes | 23 | 16 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:30 | yes | 11 | 5 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:35 | yes | 24 | 24 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:53 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:03 | no | 0 | 34 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:46 | yes | 23 | 24 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:28 | yes | 24 | 90 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:43 | yes | 8 | 23 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:46 | yes | 3 | 11 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:03 | yes | 11 | 19 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 08:36 | no | 0 | 7 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:18 | no | 0 | 6 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 08:47 | yes | 9 | 26 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 08:49 | yes | 19 | 5 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:11 | yes | 15 | 15 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:41 | no | 0 | 7 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:46 | yes | 16 | 40 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:51 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:20 | no | 0 | 35 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:44 | yes | 20 | 30 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:12 | yes | 12 | 155 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:18 | yes | 8 | 16 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:48 | yes | 2 | 16 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 10:40 | yes | 11 | 17 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:22 | no | 0 | 2 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 07:53 | no | 0 | 3 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 09:59 | yes | 22 | 18 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 09:51 | yes | 20 | 5 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:21 | yes | 19 | 5 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:41 | yes | 5 | 5 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:50 | yes | 22 | 39 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:47 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:52 | no | 0 | 29 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:01 | yes | 23 | 28 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:26 | yes | 24 | 75 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:09 | yes | 14 | 31 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:20 | no | 0 | 2 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 07:30 | yes | 15 | 20 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
Unresolved, counted raw
Acquirell
Aestiva Sourcing RFQ
Bid Management
CJdropshipping
Dux-Soup
Field Materials
FlexRFP
GitHub/Stack Overflow
Grata
HeroHunt.ai
Jobin.cloud
KASPR
Körber (formerly Zycus)
LightSource
MeRLIN Sourcing
Nvelop
OpenProcurement
PRM360
Pactum
PhantomBuster
ProcureWare
Procure杖
Proqura
SAP Ariba Strategic Sourcing Suite
Sage Supply Chain Intelligence
SourceScrub
SourceWhale
SquarePeg
Waalaxy
Wellfound
Xora
e-Procure
jaggaer.com
Discontinued, still offered
No shut-down product was recommended here.
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