Rebate management for enterprise buyers
Asked as “rebate management platform”, and as “trade rebate and incentive tracking software”, on behalf of an enterprise B2B company. 51 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
57%
Clear leader
57Enable18Vistex16Vendavo10others
57% 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 four 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 ten head-to-head pages: the top five products, each against each
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 →
01
02
03
04
05
06
07Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative70%
Key
01Enable57%
Enable57%02Vistex18%
Vistex18%03Vendavo16%
Vendavo16%04Pricefx0%
Pricefx0%05Model N0%
Model N0%06IMA3600%
IMA3600%07360insights0%
360insights0%What they warned about
Four of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, Perplexity Sonar, Grok 4.1 Fast, Mistral Small, Llama 4 Maverick, Qwen 3.7 Flash, Kimi K2, 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.
Vistex24%
14 of 59 labels negative · 9 of 14 models
“Vistex (Cautious) ... large enterprises should approach with caution, particularly if they are looking for modern cloud-native agility.” GLM 4.7 FlashX, negative prompt
Enable13%
8 of 63 labels negative · 7 of 14 models · 4 hard negative
“Platforms & Solutions to Approach with Caution ... **Enable** - **Data duplication issues** reported by users” MiniMax M2.5, negative prompt
Channelscaler33%
3 of 9 labels negative · 3 of 14 models · 2 hard negative
“Users frequently cite **poor user interface (UI)** and **outdated features** as major barriers to adoption.” Qwen 3.7 Flash, negative prompt
Oracle Channel Revenue Management33%
3 of 9 labels negative · 3 of 14 models · 2 hard negative
“Most ERPs (e.g., SAP S/4HANA, Oracle) have native rebate capabilities, but they are typically designed for simple, linear rebate programs.” Qwen 3.7 Flash, 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
81 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. 1149 links across 149 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 · G269 answers · 153 citations · 14 models
vendor site · Guideflow47 answers · 47 citations · 11 models
vendor site · Worldmetrics45 answers · 108 citations · 11 models
vendor site · Level 643 answers · 45 citations · 11 models
39 answers · 49 citations · 10 models
vendor site · Enable37 answers · 64 citations · 13 models
vendor site · OnCentive31 answers · 31 citations · 12 models
vendor site · Vistaar28 answers · 39 citations · 12 models
26 answers · 33 citations · 10 models
24 answers · 32 citations · 8 models
vendor site · Sourceforge22 answers · 29 citations · 10 models
vendor site · Vistex20 answers · 42 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.
47 answers · 11 models
42 answers · 12 models
38 answers · 11 models
31 answers · 12 models
26 answers · 10 models
24 answers · 12 models
24 answers · 10 models
22 answers · 10 models
22 answers · 11 models
20 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 rebate management platform”, “rebate management platform”, “rebate management 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 |
|---|---|---|---|---|---|---|---|---|
| Enable enable.com | 57% | 175 | 49,500 | 180,327 | 13,670 | $106 | 9 | |
| Vistex vistex.com | 18% | 139 | 1,900 | 96 | 2,312 | 70 | ||
| Vendavo vendavo.com | 16% | 96 | 1,000 | 30 | 72,496 | 1 | 1 | |
| Salesforce salesforce.com Salesforce Rebate Management 6%, Salesforce Revenue Cloud 0%, Salesforce Agentforce Revenue Management 0% | 6% | 35 | 550,000 | 60,632 | 7,941,323 company | $8,259 | 115 | 7 |
| Rebates-On rebates-on.com | 2% | 11 | 20 | 50,534 | 33 | |||
| e-bate e-bate.io | 2% | 65 | 20 | 45 | 944 | 2 | ||
| Pricefx pricefx.com | 0% | 83 | 1,000 | 18 | 11,062 | 0 | ||
| Model N modeln.com | 0% | 65 | 2,400 | 619 | 9,762 | 4 | ||
| IMA360 ima360.com | 0% | 32 | 110 | 0 | 58 | $61 | 6 | |
| incentX incentx.com | 0% | 51 | 30 | 0 | 854 | 3 |
Google's top ten for the three searches hold 22 sites; 2 of them are among the sites the models cited here (sourceforge.net, vistaar.com). The first result for “best rebate management platform” is vendavo.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 rebate management platform for an enterprise B2B company?”Paraphrase“Which trade rebate and incentive tracking software would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade rebate management platforms and how do they differ?”Budget-constrained“What is the best rebate management platform 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 rebate management platform. What should we look at?”Negative“Which rebate management platforms should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5Enable, VendavoEnableChangedEnableSalesforce Rebate Managementno first choiceagainst: SAP, Vistex
Two alternatives
Vistex, incentXThree alternatives
Pricefx, Vendavo, VistexFive alternatives
IMA360, Model N, Pricefx, Vendavo, VistexTwo alternatives
Enable, VistexGPT-5.4 miniEnableEnableHeldEnableEnableno first choicenothing named
One alternative
VistexFive alternatives
IMA360, TELUS Trade Promotion Management, Vendavo, Vistaar, VistexTwo alternatives
Oracle Supplier Rebate Management / Channel Revenue Management, SAP Vendor Program Management by Vistex / SAP rebate toolingOne alternative
VistexGemini 3.5 FlashEnableEnableHeldEnableEnable, VendavoEnableagainst: Vistexagainst: Microsoft Dynamics 365, Oracle NetSuite, SAP, Vistex
Five alternatives
Model N, Pricefx, Salesforce Agentforce Revenue Management, Vendavo, VistexFour alternatives
360insights, Model N, SAP Incentive Administration, VendavoSix alternatives
360insights, Model N, Pricefx, Salesforce Agentforce Revenue Management, Vendavo, VistexTwo alternatives
Pricefx, VistexTwo alternatives
Pricefx, VendavoPerplexity SonarVendavoEnable, VistexChangedEnable, VendavoEnableno first choiceagainst: Avidxchange Rebate Management, Microsoft Dynamics 365, Odoo
Two alternatives
Enable, VistexThree alternatives
Vendavo, Wiser Promotions, ZilliantSix alternatives
Aptitude Software, Infor Rebate Management, Pricefx, Visualfabriq, Zilliant, e-bateFour alternatives
Aptitude Software, Oracle Channel Revenue Management, Pricefx, SAP Incentive AdministrationGrok 4.1 FastEnableVistexChangedEnableEnableagainst: Optymyze, PricefxVendavoagainst: Channelscaler, Enable, SAP Condition Contract Settlement modules, Vistex
Three alternatives
Model N, Vendavo, VistexOne alternative
EnableThree alternatives
Model N, Pricefx, VistexTwo alternatives
Vendavo, VistexTwo alternatives
Vistaar, incentXMistral SmallEnableVistexChangedVistexEnable, Vendavono first choiceagainst: Channelscaler, E2open, Enable, Pricefx, Vendavo
Two alternatives
Aptitude Software, VendavoTwo alternatives
Enable, VendavoThree alternatives
Enable, SAP Rebate Management, incentXOne alternative
VistaarDeepSeek V4 FlashEnableEnableHeldEnableagainst: Rebate.ai, RebateCloud, e-bateEnableEnableagainst: Salesforce Rebate Management, Vistexagainst: Enable, IMA360, Oracle Channel Revenue Management, Rebately, Revport, SAP Rebate Processing, Vistex
Two alternatives
Model N, VistexTwo alternatives
Model N, VistexThree alternatives
Model N, Vendavo, VistexThree alternatives
Model N, Pricefx, VistexTwo alternatives
IMA360, PricefxLlama 4 MaverickVendavono first choiceChangedno first choiceno first choiceno first choicenothing named
One alternative
Aptitude SoftwareQwen 3.7 FlashEnableVistexChangedVistexVistexno first choiceagainst: Channelscaler, Enable, Oracle Channel Revenue Management, SAP S/4HANA
Two alternatives
360insights, incentXTwo alternatives
Model N, SAP Trade Promotion ManagementFour alternatives
Coupa, E2open Channel Revenue Management, Enable Software, Model NTwo alternatives
Model N, VendavoKimi K2EnableEnable, VistexChangedEnableSalesforce Rebate Management, e-bateagainst: Enable, Model N, Vendavo, Vistexno first choiceagainst: SAP Rebate Management, Vistexagainst: Enable, Model N, Oracle Channel Revenue Management, SAP, Vistex
Four alternatives
Conga, Pricefx, Vendavo, incentXTwo alternatives
360insights, VendavoFive alternatives
Flintfox, Model N, Pricefx, Vistex, incentXOne alternative
Rebates-OnGLM 4.7 FlashXEnableEnableHeldEnableEnableno first choiceagainst: SAP Condition Contract Settlement, Vistex
Three alternatives
Pricefx, Salesforce Revenue Cloud, VistexSix alternatives
E2open Supply Chain, Oracle Enterprise Applications, Phocas Software, Pricefx, Vistex, ZilliantThree alternatives
Model N, Oracle Channel Revenue Management, VistexTwo alternatives
Pricefx, VistexMiniMax M2.5no first choiceEnable, VistexChangedSAP Rebate Management, Vistex Rebate ManagementVendavono first choiceagainst: Enable, Vistex
One alternative
VendavoSeven alternatives
E2open Demand & Supply Chain, Enable, Model N Revenue Management, Pricefx, Salesforce Revenue Cloud, Vendavo Revenue Management, VisualfabriqThree alternatives
Model N, Pricefx, VistexGPT-6 LunaEnableVistexChangedEnable, Vendavo, VistexEnableagainst: Salesforce Channel Revenue Managementno first choiceagainst: 360insights, Enable, Vistex, e-bate
Two alternatives
Vendavo, VistexThree alternatives
Enable, Oracle Channel Revenue Management, Salesforce Rebate ManagementFour alternatives
Conga, IMA360, Model N, SAP S/4HANA Condition Contract ManagementOne alternative
VistexMuse Glimmer 30BEnable, VistexVendavoChangedEnableRebates-On, Salesforce Rebate Managementagainst: Model N, Vendavo, Vistexno first choiceagainst: Flintfox, Vistex
Three alternatives
HighRadius, IMA360, ZilliantTwo alternatives
Enable, VistexSix alternatives
IMA360, Model N, Oracle Channel Revenue Management, SAP Incentive Administration, Vendavo, VistexBold 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 | 2026-10-04 23:23 | yes | 9 | 9 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 22:25 | yes | 3 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 23:10 | yes | 21 | 22 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-04 23:10 | yes | 13 | 3 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 22:58 | yes | 21 | 12 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 22:21 | yes | 5 | 3 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 22:52 | yes | 21 | 27 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 23:14 | yes | 5 | 2 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:13 | yes | 5 | 18 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 22:21 | yes | 24 | 29 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 22:53 | yes | 22 | 48 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 22:42 | yes | 17 | 23 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-04 22:26 | yes | 4 | 13 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:17 | yes | 21 | 34 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 22:45 | yes | 14 | 9 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 22:52 | yes | 4 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 23:04 | yes | 21 | 29 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-04 22:39 | yes | 15 | 3 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 22:15 | yes | 19 | 9 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 22:40 | yes | 5 | 4 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 23:22 | yes | 20 | 70 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 22:59 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:33 | yes | 15 | 34 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 22:47 | yes | 19 | 22 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 22:33 | yes | 13 | 26 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:22 | yes | 9 | 30 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-04 22:17 | yes | 4 | 15 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:55 | yes | 23 | 23 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 22:18 | yes | 9 | 11 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 23:24 | yes | 8 | 10 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 23:22 | yes | 19 | 27 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-04 22:13 | yes | 16 | 4 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 22:30 | yes | 20 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 22:16 | yes | 24 | 11 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 23:26 | yes | 20 | 51 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 23:10 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:19 | yes | 20 | 42 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 23:18 | yes | 23 | 45 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 22:48 | yes | 24 | 88 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:16 | yes | 8 | 59 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-04 22:29 | yes | 9 | 42 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:14 | yes | 14 | 18 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 22:30 | yes | 17 | 8 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 22:16 | yes | 4 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 22:14 | yes | 19 | 33 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-04 22:48 | yes | 17 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 22:21 | yes | 18 | 9 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 23:07 | yes | 21 | 12 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 23:24 | yes | 21 | 35 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 23:13 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:46 | yes | 5 | 22 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 23:07 | yes | 22 | 30 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 22:43 | yes | 21 | 52 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:16 | yes | 11 | 26 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-04 22:13 | yes | 4 | 15 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:46 | yes | 14 | 27 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 22:42 | yes | 18 | 12 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 22:53 | yes | 3 | 7 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 23:04 | yes | 18 | 30 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-04 22:26 | yes | 16 | 6 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 23:13 | yes | 15 | 8 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 22:50 | no | 0 | 7 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 22:33 | yes | 21 | 37 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 22:33 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:58 | no | 0 | 24 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 22:14 | yes | 21 | 31 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 22:52 | yes | 13 | 55 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 22:20 | yes | 10 | 17 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-04 22:28 | yes | 3 | 19 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 22:56 | yes | 18 | 26 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-04 22:43 | yes | 16 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-04 22:15 | yes | 0 | 6 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-04 22:14 | yes | 17 | 31 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-04 22:43 | yes | 15 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-04 23:23 | yes | 23 | 11 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-04 23:05 | yes | 11 | 7 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-04 22:25 | yes | 20 | 46 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-04 22:59 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-04 22:52 | yes | 10 | 26 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-04 23:16 | yes | 18 | 18 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-04 22:39 | yes | 18 | 48 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-04 23:23 | yes | 19 | 30 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-04 23:14 | yes | 4 | 20 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-04 23:08 | yes | 17 | 26 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
Oracle read as Oracle Channel Revenue Management
Unresolved, counted raw
CaptivateIQ
E2open Demand & Supply Chain (Rebate Management)
E2open Supply Chain
Enable Software
Everstage
Incentit
Infor Rebate Management
Model N Revenue Management
Oracle Enterprise Applications
Oracle Supplier Rebate Management / Channel Revenue Management
Oracle Trade Management
Profectus Group
Rebate management software by Guideflow
Rebate.ai
Revport
SAP Condition Contract Settlement modules
SAP Rebate Processing
SAP S/4HANA Condition Contract Management
SAP Settlement Management
SAP Trade Promotion Management (TPM)
SAP Vendor Program Management by Vistex / SAP rebate tooling
SalesRabbit
SmartRebates
TELUS Trade Promotion Management
Varicent
Vendavo AI
Vendavo Revenue Management (Rebate & Pricing)
Vendortell
Vistex Commercial agreement management
Vistex Rebate Management
Vitrina
Xactly Incent
Discontinued, still offered
No shut-down product was recommended here.