Experimentation and personalization for enterprise buyers
Asked as “website experimentation and personalization platform”, and as “A/B testing and personalization tool”, on behalf of an enterprise B2B company. 61 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
46%
Clear leader
46Optimizely CMS16Adobe Target10Mutiny28others
46% of first choices, clear leader.
Since September 2026▲+7Since September 2026: 45% → 52%, +7 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Optimizely CMS held the lead, +7 points on 45%, inside the 11-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
VWO36%Contested▼−2Since September 2026: 38% → 37%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketVWO27%Contested▼−8Since September 2026: 34% → 26%, −8 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Enterprise
Optimizely CMS46%Clear leader▲+7Since September 2026: 45% → 52%, +7 points. Inside the 11-point floor: within noise. Read over the models both editions asked.This page
VWO36%Contested▼−2Since September 2026: 38% → 37%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketVWO27%Contested▼−8Since September 2026: 34% → 26%, −8 points. Inside the 11-point floor: within noise. Read over the models both editions asked.Standing →EnterpriseOptimizely CMS46%Clear leader▲+7Since September 2026: 45% → 52%, +7 points. Inside the 11-point floor: within noise. Read over the models both editions asked.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
01Optimizely CMS46%24%66endorsed leader▲+7Since September 2026: 45% → 52%, +7 points. Inside the 11-point floor: within noise. Read over the models both editions asked.45% → 52%
Optimizely CMS46%24%66endorsed leader▲+7Since September 2026: 45% → 52%, +7 points. Inside the 11-point floor: within noise. Read over the models both editions asked.45% → 52%02
Adobe Target16%28%67criticized challenger▲+2Since September 2026: 12% → 14%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.12% → 14%
Adobe Target16%28%67criticized challenger▲+2Since September 2026: 12% → 14%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.12% → 14%03
Mutiny10%29%14criticized challenger▲+4Since September 2026: 6% → 10%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 10%
Mutiny10%29%14criticized challenger▲+4Since September 2026: 6% → 10%, +4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 10%04VWO7%28%47criticized challenger▼−6Since September 2026: 12% → 6%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.12% → 6%
VWO7%28%47criticized challenger▼−6Since September 2026: 12% → 6%, −6 points. Inside the 11-point floor: within noise. Read over the models both editions asked.12% → 6%05
GrowthBook5%0%11accepted challenger▼−2Since September 2026: 8% → 6%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.8% → 6%
GrowthBook5%0%11accepted challenger▼−2Since September 2026: 8% → 6%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.8% → 6%06
Kameleoon3%0%34accepted challenger▼−4Since September 2026: 6% → 2%, −4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 2%
Kameleoon3%0%34accepted challenger▼−4Since September 2026: 6% → 2%, −4 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 2%07
Convert Experiences3%25%12criticized challenger▼−2Since September 2026: 6% → 4%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 4%
Convert Experiences3%25%12criticized challenger▼−2Since September 2026: 6% → 4%, −2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.6% → 4%08
AB Tasty2%15%34accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%
AB Tasty2%15%34accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 2%09
Statsig2%10%21accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 2%
Statsig2%10%21accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.2% → 2%Show the two products at 0%, ordered by negative rate
11
LaunchDarkly0%50%12criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
LaunchDarkly0%50%12criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%10
Dynamic Yield0%19%21accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%
Dynamic Yield0%19%21accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise. Read over the models both editions asked.0% → 0%The floor is 11 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-one head-to-head pages: the top seven products, each against each
VWO vs Optimizely CMSVWO vs KameleoonVWO vs PostHogConvert Experiences vs GrowthBookConvert Experiences vs MutinyConvert Experiences vs Optimizely CMSConvert Experiences vs KameleoonConvert Experiences vs PostHogGrowthBook vs MutinyGrowthBook vs Optimizely CMSGrowthBook vs KameleoonGrowthBook vs PostHogMutiny vs Optimizely CMSMutiny vs KameleoonMutiny vs PostHogOptimizely CMS vs KameleoonOptimizely CMS vs PostHogKameleoon vs PostHog
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% negative60%
Key
01Optimizely CMS46%
Optimizely CMS46%02Adobe Target16%
Adobe Target16%03Mutiny10%
Mutiny10%04VWO7%
VWO7%05GrowthBook5%
GrowthBook5%06Kameleoon3%
Kameleoon3%07Convert Experiences3%
Convert Experiences3%08AB Tasty2%
AB Tasty2%09Statsig2%
Statsig2%10Dynamic Yield0%
Dynamic Yield0%11LaunchDarkly0%
LaunchDarkly0%What they warned about
Six of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, Mistral Small, Llama 4 Maverick, Qwen 3.7 Flash, Kimi K2, GLM 4.7 FlashX, MiniMax M2.5 and Muse Glimmer 30B changed. A high negative share on a product with few labels is a warning. A low share on a product with many labels is salience, not sentiment.
Adobe Target28%
19 of 67 labels negative · 12 of 14 models · 5 hard negative
“Deep-ecosystem tools like Adobe Target when the goal is experimentation/personalization without broader Adobe Experience Cloud commitment.” Muse Glimmer 30B, negative prompt
Optimizely CMS24%
16 of 66 labels negative · 10 of 14 models · 4 hard negative
“Heavyweight enterprise suites like Optimizely for teams without dedicated developers and EU compliance resources” Muse Glimmer 30B, negative prompt
VWO28%
13 of 47 labels negative · 10 of 14 models · 3 hard negative
“**The killer issue**: VWO charges per MTU — if your tests succeed and drive more traffic, your bill increases. That's the opposite of predictable.” DeepSeek V4 Flash, budget prompt
LaunchDarkly50%
6 of 12 labels negative · 6 of 14 models
“Be cautious if you are buying a feature-flagging tool expecting it to serve as your primary, company-wide experimentation and personalization hub.” Gemini 3.5 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
79 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. 1239 links across 320 sites, every framing counted. Ranked by the number of answers carrying the site or page. 13 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 · Mida37 answers · 48 citations · 10 models
vendor site · Guideflow36 answers · 47 citations · 12 models
vendor site · Kameleoon31 answers · 39 citations · 12 models
vendor site · Personizely31 answers · 34 citations · 9 models
vendor site · Optimizely29 answers · 38 citations · 14 models
vendor site · Convert28 answers · 42 citations · 12 models
21 answers · 31 citations · 11 models
vendor site · Personyze21 answers · 21 citations · 11 models
vendor site · Statsig20 answers · 56 citations · 10 models
vendor site · GrowthBook20 answers · 35 citations · 11 models
vendor site · Webflow19 answers · 19 citations · 11 models
vendor site · Croct17 answers · 21 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.
27 answers · 11 models
24 answers · 10 models
23 answers · 9 models
22 answers · 7 models
18 answers · 10 models
18 answers · 11 models
17 answers · 9 models
17 answers · 10 models
17 answers · 9 models
16 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 website experimentation and personalization platform”, “website experimentation and personalization platform”. 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 |
|---|---|---|---|---|---|---|---|---|
| Optimizely optimizely.com Optimizely CMS 46%, Optimizely Web Experimentation 5% | 51% | 237 | 60,500 | 36,211 | 200,757 company | $2 | 120 | 3 |
| Adobe parent site Adobe Target 16% | 16% | 113 | 1,220,000 | 117,563 | ||||
| Mutiny mutinyhq.com | 10% | 71 | 110,000 | 3,032 | 680 | 0 | ||
| VWO vwo.com | 7% | 156 | 22,200 | 449 | 25,874 | 14 | 5 | |
| GrowthBook growthbook.io | 5% | 71 | 2,900 | 14 | 26,646 | 26 | ||
| Kameleoon kameleoon.com | 3% | 82 | 590 | 3 | 28,601 | 3 | ||
| Convert Experiences convert.com | 3% | 80 | 50 | 22 | 20,882 | 1 | ||
| AB Tasty abtasty.com | 2% | 79 | 1,000 | 27 | 23,529 | 3 | ||
| Statsig statsig.com Statsig 2%, Statsig Warehouse Native 0% | 2% | 74 | 12,100 | 182 | 353,837 | $176 | 6 | |
| Harness Feature Management & Experimentation harness.io | 2% | 2 | 86,302 | 6 |
Google's top ten for the two searches hold 17 sites; 4 of them are among the sites the models cited here (blog.croct.com, guideflow.com, mida.so, optimizely.com). The first result for “best website experimentation and personalization 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 website experimentation and personalization platform for an enterprise B2B company?”Paraphrase“Which A/B testing and personalization tool would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade experimentation and personalization platforms and how do they differ?”Budget-constrained“What is the best website experimentation and personalization 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 website experimentation and personalization platform. What should we look at?”Negative“Which experimentation and personalization platforms should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5Mutiny, Optimizely CMSOptimizely CMSChangedOptimizely CMSOptimizely CMSno first choiceagainst: Adobe Target, Optimizely CMS, Sitecore, VWO Personalize
Two alternatives
Dynamic Yield, KameleoonThree alternatives
Adobe Target, Kameleoon, VWOThree alternatives
Adobe Target, Dynamic Yield, Salesforce Marketing Cloud PersonalizationTwo alternatives
Kameleoon, VWOGPT-5.4 miniAdobe TargetAdobe TargetHeldagainst: VWOno first choiceGrowthBookagainst: Adobe Target, Convert Experiences, Optimizely CMSno first choicenothing named
One alternative
Optimizely CMSOne alternative
Optimizely CMSSix alternatives
AB Tasty, Adobe Target, LaunchDarkly, Optimizely CMS, Statsig, VWOOne alternative
AB TastyGemini 3.5 FlashOptimizely CMSagainst: Intellimize, Mutiny, NinetailedOptimizely CMSHeldagainst: Adobe TargetOptimizely CMSGrowthBookagainst: Adobe Target, Optimizely CMSno first choiceagainst: Adobe Target, Convert Experiences, LaunchDarkly, Optimizely CMS, Split, VWO
Five alternatives
Abmatic AI, Adobe Target, Croct, Kameleoon, VWOThree alternatives
Kameleoon, Mutiny, WingifySeven alternatives
AB Tasty, Adobe Target, Dynamic Yield, GrowthBook, Kameleoon, Statsig, VWOTwo alternatives
Kameleoon, StatsigPerplexity SonarOptimizely CMSagainst: VWOOptimizely CMSHeldAdobe Target, Optimizely CMS, StatsigStatsigno first choiceagainst: PostHog
One alternative
Adobe TargetThree alternatives
AB Tasty, Adobe Target, VWOFour alternatives
AB Tasty, Amplitude Experiment, Kameleoon, VWOOne alternative
Optimizely CMSGrok 4.1 FastOptimizely CMSOptimizely CMSHeldno first choiceConvert Experiencesagainst: AB Tasty, Adobe Target, Optimizely CMSAdobe Target, Optimizely CMS, VWOagainst: AB Tasty, Adobe Target, Optimizely CMS, VWO
Three alternatives
Adobe Target, Dynamic Yield, MutinyThree alternatives
AB Tasty, Adobe Target, Dynamic YieldThree alternatives
Kameleoon, VWO, Varify.ioMistral SmallMutiny, Optimizely CMSOptimizely CMSChangedagainst: VWOAdobe Target, Optimizely CMSAdobe Targetagainst: Google Optimize, Optimizely CMSno first choiceagainst: Adobe Target, Mutiny, Ninetailed, Optimizely CMS
Two alternatives
Adobe Target, InsiderOne alternative
AB TastyFive alternatives
Eppo, GrowthBook, Kameleoon, Statsig, VWOTwo alternatives
Mida, VWODeepSeek V4 FlashOptimizely CMSagainst: Adobe Target, MutinyOptimizely CMSHeldagainst: VWOOptimizely CMSConvert Experiencesagainst: Adobe Target, Optimizely CMS, VWOAdobe Target, Kameleoon, Optimizely CMS, VWOagainst: Convert Experiences, LaunchDarklyagainst: Adobe Target, Dynamic Yield, Optimizely CMS, VWO
Three alternatives
AB Tasty, Kameleoon, VWOTwo alternatives
AB Tasty, Adobe TargetFive alternatives
AB Tasty, Adobe Target, Kameleoon, Mastercard Dynamic Yield, VWOOne alternative
KameleoonLlama 4 MaverickMutiny, Optimizely CMSAB TastyChangedno first choiceOptimizely CMSOptimizely CMSnothing named
Two alternatives
Optimizely CMS, VWOFour alternatives
AB Tasty, Adobe Target, Kameleoon, VWOQwen 3.7 FlashOptimizely CMSAdobe TargetChangedno first choiceOptimizely CMSno first choiceagainst: Adobe Target, Amazon Personalize, LaunchDarkly, Sitecore Experience Platform, Split
Two alternatives
Adobe Target, Convert ExperiencesThree alternatives
AB Tasty, Kameleoon, Optimizely CMSFive alternatives
Adobe Target, Bloomreach, Dynamic Yield, Kameleoon, Optimizely CMSThree alternatives
Adobe Target, Statsig, Visual Website OptimizerKimi K2Mutiny, Optimizely CMSagainst: IntellimizeOptimizely CMSChangedOptimizely CMSGrowthBookagainst: AB Tasty, Adobe Target, Dynamic Yield, Optimizely CMS, Statsig, VWOOptimizely CMSagainst: AB Tasty, Adobe Target, Dynamic Yield, Google Optimize, Optimizely CMS, Sitecore
Two alternatives
Adobe Target, VWOThree alternatives
Adobe Target, Kameleoon, MutinyFour alternatives
Adobe Target, Dynamic Yield, Kameleoon, VWOOne alternative
KameleoonFour alternatives
Adobe Target, Eppo, Statsig, VWOGLM 4.7 FlashXOptimizely CMSAdobe TargetChangedno first choiceVWOagainst: Adobe Target, Optimizely CMSno first choiceagainst: HubSpot Breeze Intelligence, Intellimize, LaunchDarkly, Mutiny, Ninetailed, VWO, Webflow Optimize
Four alternatives
Adobe Target, Convert Experiences, Mutiny, VWOOne alternative
KameleoonOne alternative
StatsigMiniMax M2.5Mutiny, Optimizely CMSOptimizely CMSChangedAdobe Target, Optimizely CMSHarness Feature Management & Experimentationagainst: LaunchDarkly, Optimizely CMS, Statsigno first choiceagainst: Adobe Target
Two alternatives
Adobe Target, Dynamic YieldTwo alternatives
AB Tasty, Adobe TargetFour alternatives
GrowthBook, Monetate, Statsig, VWOTwo alternatives
GrowthBook, VWOGPT-6 LunaOptimizely Web ExperimentationOptimizely Web ExperimentationHeldno first choiceVWOno first choiceagainst: AB Tasty, Adobe Target, Eppo, Google Optimize, VWO
Three alternatives
AB Tasty, Adobe Target, VWOTwo alternatives
Adobe Target, StatsigEight alternatives
AB Tasty, Adobe Target, Amplitude Experiment, Dynamic Yield, LaunchDarkly, Optimizely CMS, Statsig, VWOOne alternative
Adobe TargetMuse Glimmer 30BAdobe Target, Mutiny, Optimizely CMSAdobe Target, Optimizely Web ExperimentationChangedOptimizely CMS, Statsigagainst: LaunchDarklyKameleoonagainst: Adobe Target, Optimizely CMS, VWOAdobe Target, Optimizely CMSagainst: Adobe Target, Dynamic Yield, Monetate, Optimizely CMS, VWO
Two alternatives
Dynamic Yield, MonetateFour alternatives
Adobe Target, Dynamic Yield – Mastercard, Monetate, SplitThree alternatives
Mida, RightMessage, graph8One alternative
VWOBold 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 10:32 | yes | 9 | 6 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:39 | yes | 2 | 7 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:06 | yes | 19 | 34 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 11:03 | yes | 18 | 4 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:43 | yes | 24 | 8 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 08:21 | yes | 9 | 6 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:30 | yes | 25 | 32 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 13:07 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:45 | yes | 10 | 42 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:57 | yes | 19 | 24 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 10:59 | yes | 22 | 30 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:33 | yes | 5 | 30 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 07:26 | yes | 3 | 17 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:12 | yes | 22 | 34 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 12:51 | yes | 9 | 8 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 11:06 | yes | 3 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:13 | yes | 22 | 33 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 08:59 | yes | 24 | 4 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:16 | yes | 25 | 7 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:29 | yes | 9 | 6 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 09:41 | yes | 23 | 29 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:05 | yes | 5 | 1 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 13:30 | yes | 5 | 19 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:38 | yes | 13 | 19 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:41 | yes | 24 | 83 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:33 | yes | 8 | 39 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:46 | yes | 3 | 14 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:39 | yes | 14 | 20 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:41 | yes | 18 | 12 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:28 | yes | 8 | 10 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 14:12 | yes | 23 | 30 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 13:01 | yes | 19 | 6 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 09:20 | yes | 24 | 9 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 12:11 | yes | 25 | 15 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 13:43 | yes | 21 | 37 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 07:31 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:17 | yes | 5 | 32 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 10:53 | yes | 18 | 24 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:30 | yes | 23 | 138 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:19 | yes | 20 | 36 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:55 | yes | 8 | 23 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 12:54 | yes | 19 | 44 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 09:41 | yes | 18 | 10 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:33 | yes | 4 | 4 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 13:08 | yes | 23 | 39 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 08:45 | yes | 19 | 3 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 12:27 | yes | 23 | 8 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:46 | yes | 20 | 6 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:31 | yes | 25 | 31 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 12:45 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 07:52 | no | 0 | 44 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:23 | yes | 23 | 26 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:28 | yes | 25 | 41 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 07:46 | yes | 22 | 37 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:34 | yes | 3 | 22 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 12:59 | yes | 19 | 41 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:36 | yes | 18 | 13 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:22 | yes | 0 | 9 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:24 | yes | 5 | 35 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 07:47 | yes | 19 | 6 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:39 | yes | 14 | 12 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:18 | no | 0 | 8 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:30 | yes | 24 | 62 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 13:18 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:41 | no | 0 | 29 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 07:56 | yes | 25 | 29 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:28 | yes | 25 | 30 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 13:38 | yes | 10 | 42 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 13:48 | yes | 4 | 29 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:08 | yes | 15 | 29 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 07:56 | yes | 26 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 12:33 | yes | 4 | 8 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 12:38 | yes | 21 | 35 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 11:27 | yes | 20 | 5 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 07:50 | yes | 24 | 9 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 07:41 | yes | 5 | 3 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 12:25 | yes | 25 | 53 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:56 | yes | 5 | 1 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:26 | no | 0 | 36 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:24 | yes | 25 | 35 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 13:28 | yes | 25 | 21 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 11:15 | yes | 23 | 32 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:44 | yes | 4 | 25 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 14:10 | yes | 24 | 41 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
Adobe read as Adobe Target
Convert read as Convert Experiences
Convert.com read as Convert Experiences
Unresolved, counted raw
Algonomy
Amazon Personalize
Dynamic Yield – Mastercard
Mastercard Dynamic Yield (Experience OS)
Microsoft Azure Personalizer
Salesforce
Statsig Warehouse Native
Wingify (The newly unified VWO + AB Tasty Platform)
Discontinued, still offered
No shut-down product was recommended here.