Index › Onboarding and employee experience › Recognition and rewards › Enterprise › October 2026 Edition
Recognition and rewards for enterprise buyers
Asked as “employee recognition platform”, and as “employee rewards program software”, on behalf of an enterprise B2B company. 49 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
39%
Contested · Awardco 20%
39Achievers20Awardco18Workhuman22others
39% of first choices, contested.
Since September 2026=heldSince September 2026: 38% → 38%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.Achievers held the lead, ±0 points on 38%, inside the 13-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
Bonusly60%Clear leader▼−1Since September 2026: 60% → 59%, −1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketBonusly29%Contested↗new leaderNew leader since September 2026: Nectar (26%) replaces Bonusly (22% then, 23% now), 2 points clear, inside the 13-point floor.Standing →Enterprise
Achievers39%Contested=heldSince September 2026: 38% → 38%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.This page
Bonusly60%Clear leader▼−1Since September 2026: 60% → 59%, −1 point. Inside the 13-point floor: within noise. Read over the models both editions asked.Standing →Mid-marketBonusly29%Contested↗new leaderNew leader since September 2026: Nectar (26%) replaces Bonusly (22% then, 23% now), 2 points clear, inside the 13-point floor.Standing →EnterpriseAchievers39%Contested=heldSince September 2026: 38% → 38%, ±0 points. Inside the 13-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
01Achievers39%7%60endorsed leader=heldSince September 2026: 38% → 38%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.38% → 38%
Achievers39%7%60endorsed leader=heldSince September 2026: 38% → 38%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.38% → 38%02
Awardco20%9%54accepted challenger▲+7Since September 2026: 17% → 24%, +7 points. Inside the 13-point floor: within noise. Read over the models both editions asked.17% → 24%
Awardco20%9%54accepted challenger▲+7Since September 2026: 17% → 24%, +7 points. Inside the 13-point floor: within noise. Read over the models both editions asked.17% → 24%03
Workhuman18%11%53accepted challenger▼−15Since September 2026: 34% → 19%, −15 points. Past the 13-point floor: movement. Read over the models both editions asked.34% → 19%
Workhuman18%11%53accepted challenger▼−15Since September 2026: 34% → 19%, −15 points. Past the 13-point floor: movement. Read over the models both editions asked.34% → 19%04Bonusly8%41%32criticized challenger▲+5Since September 2026: 2% → 7%, +5 points. Inside the 13-point floor: within noise. Read over the models both editions asked.2% → 7%
Bonusly8%41%32criticized challenger▲+5Since September 2026: 2% → 7%, +5 points. Inside the 13-point floor: within noise. Read over the models both editions asked.2% → 7%05
Kudos4%14%22accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 2%
Kudos4%14%22accepted challenger▲+2Since September 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 2%06
Motivosity2%20%15accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.2% → 2%
Motivosity2%20%15accepted challenger=heldSince September 2026: 2% → 2%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.2% → 2%Show the four products at 0%, ordered by negative rate
10
Nectar0%36%14criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Nectar0%36%14criticized challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%07
O.C. Tanner Culture Cloud0%17%18accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
O.C. Tanner Culture Cloud0%17%18accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%08
Guusto0%14%14accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Guusto0%14%14accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%09
Vantage Circle0%0%10accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%
Vantage Circle0%0%10accepted challenger=heldSince September 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise. Read over the models both editions asked.0% → 0%The floor is 13 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 fifteen head-to-head pages: the top six 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 →
01020304050607080910Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative50%
Key
01Achievers39%
Achievers39%02Awardco20%
Awardco20%03Workhuman18%
Workhuman18%04Bonusly8%
Bonusly8%05Kudos4%
Kudos4%06Motivosity2%
Motivosity2%07O.C. Tanner Culture Cloud0%
O.C. Tanner Culture Cloud0%08Guusto0%
Guusto0%09Vantage Circle0%
Vantage Circle0%10Nectar0%
Nectar0%What they warned about
Two 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, 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.
Bonusly41%
13 of 32 labels negative · 9 of 14 models · 3 hard negative
“Lightweight versions of platforms like Bonusly or generic Slack/Teams integrations are not recommended for large enterprises.” Mistral Small, negative prompt
Workhuman11%
6 of 53 labels negative · 5 of 14 models · 1 hard negative
“Avoid for predictability: ... Workhuman” Grok 4.1 Fast, budget prompt
Awardco9%
5 of 54 labels negative · 4 of 14 models · 3 hard negative
“Large enterprises should avoid or be cautious about SMB-focused tools, Awardco, and Achievers due to scalability issues, limited flexibility, delivery delays, opaque pricing” Mistral Small, negative prompt
Achievers7%
4 of 60 labels negative · 4 of 14 models · 2 hard negative
“Avoid for predictability: Enterprise-heavy like Achievers” Grok 4.1 Fast, 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
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. 1083 links across 168 sites, every framing counted. Ranked by the number of answers carrying the site or page. 18 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 · Achievers60 answers · 112 citations · 13 models
vendor site · Workhuman42 answers · 65 citations · 14 models
vendor site · Awardco38 answers · 64 citations · 12 models
vendor site · G234 answers · 54 citations · 12 models
vendor site · Tremendous31 answers · 32 citations · 11 models
vendor site · Engagedly31 answers · 31 citations · 12 models
30 answers · 34 citations · 12 models
30 answers · 30 citations · 10 models
vendor site · Kudoboard25 answers · 29 citations · 11 models
vendor site · Kudos24 answers · 24 citations · 9 models
21 answers · 22 citations · 11 models
vendor site · ThriveSparrow21 answers · 22 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 · 11 models
31 answers · 11 models
30 answers · 10 models
30 answers · 12 models
30 answers · 12 models
26 answers · 10 models
25 answers · 11 models
24 answers · 9 models
22 answers · 10 models
22 answers · 11 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 employee recognition platform”, “employee recognition platform”, “recognition 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 |
|---|---|---|---|---|---|---|---|---|
| Achievers achievers.com | 39% | 107 | 6,600 | 69,832 | 295,924 | 5 | 4 | |
| Awardco awardco.com | 20% | 124 | 27,100 | 303 | 32,927 | 14 | ||
| Workhuman workhuman.com | 18% | 138 | 4,400 | 158 | 373,538 | $160,162 | 72 | |
| Bonusly bonusly.com | 8% | 176 | 14,800 | 75 | 44,595 | 21 | 2 | |
| Kudos kudos.com | 4% | 70 | 60,500 | 3,826 | 26,553 | 10 | 4 | |
| Empuls | 4% | |||||||
| Motivosity motivosity.com | 2% | 87 | 8,100 | 58 | 12,155 | $27 | 30 | |
| HeyTaco heytaco.com | 2% | 13 | 590 | 26 | 19,686 | |||
| Workstars workstars.com | 2% | 1 | ||||||
| O.C. Tanner octanner.com O.C. Tanner Culture Cloud 0% | 0% | 29 | 30 | 1 | 60,022 company | 23 | 7 |
Google's top ten for the three searches hold 18 sites; 6 of them are among the sites the models cited here (achievers.com, kudos.com, peoplemanagingpeople.com, selectsoftwarereviews.com, thrivesparrow.com, tremendous.com). The first result for “best employee recognition platform” is selectsoftwarereviews.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 employee recognition platform for an enterprise B2B company?”Paraphrase“Which employee rewards program software would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade recognition platforms and how do they differ?”Budget-constrained“What is the best employee recognition 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 an employee recognition platform. What should we look at?”Negative“Which recognition platforms should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5WorkhumanAwardcoChangedAchievers, Awardco, WorkhumanAwardcono first choiceagainst: Bonusly, Motivosity
Three alternatives
Achievers, Awardco, O.C. Tanner Culture CloudThree alternatives
Achievers, OC Tanner Culture Cloud, TerryberryThree alternatives
O.C. Tanner Culture Cloud, Vantage Circle, WorkTangoThree alternatives
Bonusly, Empuls, NectarGPT-5.4 miniWorkhumanAchieversChangedWorkhumanMotivosityagainst: Workhumanno first choicenothing named
Four alternatives
Achievers, Awardco, Guusto, O.C. Tanner Culture CloudTwo alternatives
Awardco, WorkhumanFive alternatives
Assembly, Awardco, Culture Amp, O.C. Tanner Culture Cloud, WorkvivoOne alternative
BonuslyGemini 3.5 FlashAchieversAwardcoChangedAchievers, WorkhumanAwardcoAwardcoagainst: Bonusly, Kudos, Motivosity, Nectar, O.C. Tanner Culture Cloud, Terryberry
Three alternatives
Awardco, Teamflect, WorkhumanFour alternatives
Achievers, Recognize, Reward Gateway, WorkhumanThree alternatives
Awardco, O.C. Tanner Culture Cloud, Reward GatewayTwo alternatives
Nectar, TremendousFive alternatives
Achievers, Bonusly, Guusto, Motivosity, WorkhumanPerplexity SonarWorkhumanAchieversChangedAchievers, WorkhumanAwardcono first choicenothing named
Two alternatives
Achievers, AwardcoFour alternatives
Awardco, Empuls, Tremendous, WorkhumanSix alternatives
Awardco, Guusto, Kudos, O.C. Tanner Culture Cloud, Vantage Circle, WorkvivoTwo alternatives
Achievers, WorkhumanGrok 4.1 FastAchievers, WorkhumanAchieversChangedagainst: Bonusly, NectarWorkhumanagainst: BonuslyBonuslyagainst: Achievers, Awardco, Bucketlist Rewards, WorkhumanAwardcoagainst: Awardco, Bonusly, Kudos, Nectar
Two alternatives
Awardco, O.C. Tanner Culture CloudTwo alternatives
Awardco, WorkhumanThree alternatives
Achievers, Awardco, NectarThree alternatives
Assembly, Kudos, NectarTwo alternatives
Reward Gateway, Vantage CircleMistral SmallAchieversAchievers, AwardcoChangedWorkhumanagainst: Culture AmpAchievers, Workhumanno first choiceagainst: Achievers, Awardco, Bonusly
Four alternatives
Guusto, Kudos, Reward Gateway, Tanner’s Culture Cloud™Two alternatives
Bonusly, Vantage CircleTwo alternatives
Achievers, O.C. Tanner Culture CloudOne alternative
AssemblyDeepSeek V4 FlashAchieversagainst: Bonusly, Guusto, Motivosity, NectarAchieversHeldagainst: WorkhumanWorkhumanagainst: GuustoAchieversagainst: Bonusly, O.C. Tanner Culture Cloud, Workhumanno first choiceagainst: Cooleaf
Two alternatives
Awardco, WorkhumanTwo alternatives
Awardco, EmpulsEight alternatives
Achievers, Awardco, Bonusly, Kudos, Motivosity, Nectar, O.C. Tanner Culture Cloud, WorkTangoOne alternative
AwardcoLlama 4 Maverickno first choiceEmpulsChangedWorkhumanno first choiceno first choiceagainst: Awardco, Bonusly
Two alternatives
Achievers, Semos CloudTwo alternatives
Achievers, GuustoThree alternatives
Achievers, Engagedly, WorkhumanQwen 3.7 FlashAwardcoAchieversChangedAchievers, WorkhumanBonusly, Kudosagainst: Achievers, Workhumanno first choicenothing named
Three alternatives
Kudos, Tanner, TremendousTwo alternatives
Awardco, KudosSix alternatives
Awardco, Guusto, Kudos, Motivosity, Nectar, Reward GatewayOne alternative
AwardcoKimi K2Achieversagainst: BonuslyWorkhumanChangedagainst: O.C. Tanner Culture CloudWorkhumanWorkhumanagainst: Achievers, Bonusly, Kudos, Nectarno first choicenothing named
Three alternatives
Awardco, Guusto, WorkhumanTwo alternatives
Achievers, AwardcoSix alternatives
Achievers, Awardco, Bonusly, Guusto, Kudos, MotivosityTwo alternatives
Awardco, MotivosityGLM 4.7 FlashXAchievers, WorkhumanAchievers, AwardcoChangedWorkhumanBonuslyno first choiceagainst: Microsoft Viva Employee Experience Manager, Slack
Four alternatives
Awardco, Bonusly, Kudos, MotivosityTwo alternatives
O.C. Tanner Culture Cloud, WorkhumanFour alternatives
Achievers, Bonusly, Kudos, Reward GatewayThree alternatives
Awardco, Recognize, WorkhumanMiniMax M2.5AchieversEmpulsChangedAchievers, XoxodayHeyTacono first choicenothing named
Two alternatives
Reward Gateway, StadiumTwo alternatives
Achievers, FondSeven alternatives
Assembly, Bonusly, Culture Amp, Kudos, Lattice, ThriveSparrow Kudos, WorkTangoFour alternatives
Achievers, Engagedly, HubEngage, WorkhumanGPT-6 LunaAchieversAchieversHeldAchievers, Awardco, O.C. Tanner Culture Cloud, WorkhumanWorkstarsno first choiceagainst: Bonusly, Workhuman
Three alternatives
Awardco, O.C. Tanner Culture Cloud, WorkhumanTwo alternatives
Awardco, WorkhumanTwo alternatives
Nectar, TerryberryOne alternative
BonuslyMuse Glimmer 30BWorkhumanAchieversChangedWorkhumanBonusly, Kudosno first choiceagainst: Awardco, Bonusly, Matter
Two alternatives
Achievers, KudosTwo alternatives
Awardco, Reward Gateway | EdenredFour alternatives
Achievers, Kudos, Reward Gateway, TerryberryBold 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 07:36 | yes | 9 | 6 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:05 | yes | 3 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:28 | yes | 22 | 25 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-10-01 11:43 | yes | 18 | 4 s |
| Direct recommendation | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:15 | yes | 21 | 10 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:59 | yes | 13 | 7 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:44 | yes | 17 | 32 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:37 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:53 | yes | 8 | 29 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:04 | yes | 15 | 21 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 11:43 | yes | 25 | 56 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:43 | yes | 8 | 15 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-10-01 11:37 | yes | 4 | 16 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:32 | yes | 14 | 38 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 07:52 | yes | 9 | 9 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 10:11 | yes | 2 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 07:29 | yes | 18 | 23 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-10-01 09:52 | yes | 20 | 5 s |
| Paraphrase | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 07:47 | yes | 21 | 7 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:08 | yes | 5 | 6 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:42 | yes | 22 | 22 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 10:47 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 09:07 | yes | 9 | 26 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 12:00 | yes | 17 | 31 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:13 | yes | 13 | 32 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:21 | yes | 5 | 10 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:31 | yes | 3 | 14 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 11:32 | yes | 23 | 27 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:26 | yes | 10 | 8 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:21 | yes | 4 | 11 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:26 | yes | 19 | 25 s |
| Comparative | Perplexity Sonar | sonar | 2026-10-01 09:42 | yes | 19 | 7 s |
| Comparative | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:41 | yes | 20 | 12 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:48 | yes | 12 | 9 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 08:15 | yes | 25 | 74 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:15 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:26 | yes | 16 | 42 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:29 | yes | 13 | 27 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 08:16 | yes | 23 | 97 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:20 | yes | 8 | 16 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-10-01 09:44 | yes | 6 | 22 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:27 | yes | 14 | 37 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:11 | yes | 17 | 10 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 08:33 | yes | 4 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 10:46 | yes | 16 | 23 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-10-01 11:18 | yes | 19 | 5 s |
| Budget constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 11:02 | yes | 21 | 12 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 09:47 | yes | 8 | 6 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 10:23 | yes | 24 | 23 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:53 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 10:57 | yes | 9 | 17 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 09:24 | yes | 23 | 26 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:20 | yes | 21 | 35 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 09:51 | yes | 15 | 26 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 08:26 | yes | 2 | 23 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 07:29 | yes | 18 | 23 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 10:36 | yes | 18 | 12 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 09:49 | no | 0 | 8 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:21 | no | 0 | 17 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-10-01 11:19 | yes | 20 | 8 s |
| Scale constrained | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 08:46 | yes | 14 | 8 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 10:58 | no | 0 | 6 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:21 | yes | 23 | 44 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 11:30 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 11:55 | no | 0 | 36 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 08:13 | yes | 21 | 30 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 09:05 | yes | 15 | 24 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 08:10 | yes | 5 | 20 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-10-01 10:46 | yes | 2 | 20 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 09:05 | yes | 15 | 40 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-10-01 11:21 | yes | 18 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-10-01 07:36 | yes | 2 | 6 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-10-01 11:03 | yes | 17 | 29 s |
| Negative framing | Perplexity Sonar | sonar | 2026-10-01 11:54 | yes | 18 | 4 s |
| Negative framing | Grok 4.1 Fast | spacexai/grok-4.1-fast-non-reasoning via vertex | 2026-10-01 10:54 | yes | 22 | 12 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-10-01 11:32 | yes | 5 | 9 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-10-01 11:23 | yes | 19 | 50 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-10-01 09:49 | yes | 5 | 3 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-10-01 12:05 | no | 0 | 47 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-10-01 11:51 | yes | 24 | 31 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-10-01 07:29 | yes | 19 | 35 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-10-01 10:13 | yes | 21 | 32 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-10-01 12:03 | yes | 3 | 18 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-10-01 08:31 | yes | 22 | 46 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
Bucketlist read as Bucketlist Rewards
O.C. Tanner read as O.C. Tanner Culture Cloud
Unresolved, counted raw
Compright
Microsoft Viva Employee Experience Manager
OC Tanner Culture Cloud
Reward Gateway | Edenred
Rewordin
Tanner (Culture Cloud)
Tanner’s Culture Cloud™
Workstars
Discontinued, still offered
No shut-down product was recommended here.