Index › HR › Onboarding and employee experience › Recognition and rewards › Enterprise · November 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. 58 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
29%
Contested · Workhuman 22%
29Awardco22Workhuman21Achievers28others
29% of first choices, contested.
Since October 2026↗new leaderNew leader since October 2026: Awardco (29%) replaces Achievers (39% then, 21% now), 8 points clear, inside the 13-point floor.Awardco leads at 29%, replacing Achievers, which led at 39% and stands at 21% now: 8 points clear, inside the floor, so the swap reads as unsettled.
By buyer segment
The same question asked on behalf of a different buyer. Each standing is computed within its segment; they sit side by side and are never added together.
Small business
Bonusly61%Clear leader▲+1Since October 2026: 60% → 61%, +1 point. Inside the 13-point floor: within noise.Standing →Mid-marketBonusly58%Clear leader▲+29Since October 2026: 29% → 58%, +29 points. Past the 13-point floor: movement.Standing →Enterprise
Awardco29%Contested↗new leaderNew leader since October 2026: Awardco (29%) replaces Achievers (39% then, 21% now), 8 points clear, inside the 13-point floor.This page
Bonusly61%Clear leader▲+1Since October 2026: 60% → 61%, +1 point. Inside the 13-point floor: within noise.Standing →Mid-marketBonusly58%Clear leader▲+29Since October 2026: 29% → 58%, +29 points. Past the 13-point floor: movement.Standing →EnterpriseAwardco29%Contested↗new leaderNew leader since October 2026: Awardco (29%) replaces Achievers (39% then, 21% now), 8 points clear, inside the 13-point floor.This pageThe standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for an enterprise B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince October 2026
01Awardco29%3%63accepted challenger▲+9Since October 2026: 20% → 29%, +9 points. Inside the 13-point floor: within noise.20% → 29%
Awardco29%3%63accepted challenger▲+9Since October 2026: 20% → 29%, +9 points. Inside the 13-point floor: within noise.20% → 29%02
Workhuman22%9%57accepted challenger▲+4Since October 2026: 18% → 22%, +4 points. Inside the 13-point floor: within noise.18% → 22%
Workhuman22%9%57accepted challenger▲+4Since October 2026: 18% → 22%, +4 points. Inside the 13-point floor: within noise.18% → 22%03
Achievers21%8%61accepted challenger▼−18Since October 2026: 39% → 21%, −18 points. Past the 13-point floor: movement.39% → 21%
Achievers21%8%61accepted challenger▼−18Since October 2026: 39% → 21%, −18 points. Past the 13-point floor: movement.39% → 21%04Bonusly5%22%45accepted challenger▼−3Since October 2026: 8% → 5%, −3 points. Inside the 13-point floor: within noise.8% → 5%
Bonusly5%22%45accepted challenger▼−3Since October 2026: 8% → 5%, −3 points. Inside the 13-point floor: within noise.8% → 5%05
O.C. Tanner Culture Cloud2%3%30accepted challenger▲+2Since October 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise.0% → 2%
O.C. Tanner Culture Cloud2%3%30accepted challenger▲+2Since October 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise.0% → 2%06
Kudos2%8%13accepted challenger▼−2Since October 2026: 4% → 2%, −2 points. Inside the 13-point floor: within noise.4% → 2%
Kudos2%8%13accepted challenger▼−2Since October 2026: 4% → 2%, −2 points. Inside the 13-point floor: within noise.4% → 2%07
Assembly2%21%14accepted challenger▲+2Since October 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise.0% → 2%
Assembly2%21%14accepted challenger▲+2Since October 2026: 0% → 2%, +2 points. Inside the 13-point floor: within noise.0% → 2%08
Motivosity2%28%18criticized challenger=heldSince October 2026: 2% → 2%, ±0 points. Inside the 13-point floor: within noise.2% → 2%
Motivosity2%28%18criticized challenger=heldSince October 2026: 2% → 2%, ±0 points. Inside the 13-point floor: within noise.2% → 2%Show the two products at 0%, ordered by negative rate
10
Nectar0%25%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise.0% → 0%
Nectar0%25%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise.0% → 0%09
WorkTango0%20%10accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise.0% → 0%
WorkTango0%20%10accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 13-point floor: within noise.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 can't be told apart from repeat variation, and both are shown. Each index measures its own floor from its own repeat, over its own categories, so the floor differs from one index to the next. Both editions asked the same fourteen models. 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.
Head to headHead-to-head pages are published for mid-market buyers, so these open on mid-market figures, not enterprise.
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% negative40%
Key
01Awardco29%
Awardco29%02Workhuman22%
Workhuman22%03Achievers21%
Achievers21%04Bonusly5%
Bonusly5%05O.C. Tanner Culture Cloud2%
O.C. Tanner Culture Cloud2%06Kudos2%
Kudos2%07Assembly2%
Assembly2%08Motivosity2%
Motivosity2%09WorkTango0%
WorkTango0%10Nectar0%
Nectar0%What they warned about
One of fourteen models held their first choice under the paraphrase. Claude Haiku 4.5, Gemini 3.5 Flash, Perplexity Sonar, Grok 4.20, Mistral Small, DeepSeek V4 Flash, Llama 4 Maverick, 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.
Bonusly22%
10 of 45 labels negative · 8 of 14 models · 3 hard negative
“Platforms that are routinely described as SMB / mid-market first and that enterprises are cautioned to outgrow ... Bonusly” Muse Glimmer 30B, negative prompt
Achievers8%
5 of 61 labels negative · 4 of 14 models · 1 hard negative
“reviewers note the cost scales significantly with workforce size and reward volume” DeepSeek V4 Flash, budget prompt
Motivosity28%
5 of 18 labels negative · 4 of 14 models · 1 hard negative
“pricing (starting around $3,000/year) and limited values mapping may not scale well for very large organizations” Mistral Small, negative prompt
Workhuman9%
5 of 57 labels negative · 4 of 14 models · 1 hard negative
“known to be expensive/complex for large enterprises. Budget predictability is difficult” DeepSeek V4 Flash, budget prompt
What they cite
Fourteen of the fourteen models returned a source list in this edition: five return the pages they cited and nine the search results they consulted.
Sites the answers cite
74 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. 888 links across 190 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 · Awardco47 answers · 75 citations · 14 models
vendor site · G232 answers · 54 citations · 12 models
vendor site · Lead Change Group30 answers · 48 citations · 9 models
vendor site · Xoxoday26 answers · 35 citations · 12 models
25 answers · 35 citations · 8 models
vendor site · Achievers25 answers · 32 citations · 11 models
vendor site · Workhuman19 answers · 37 citations · 9 models
vendor site · Bucketlist Rewards16 answers · 20 citations · 8 models
vendor site · Bonusly16 answers · 19 citations · 10 models
vendor site · Tremendous16 answers · 16 citations · 8 models
vendor site · O.C. Tanner15 answers · 23 citations · 9 models
15 answers · 20 citations · 11 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.
26 answers · 9 models
24 answers · 8 models
22 answers · 11 models
16 answers · 8 models
14 answers · 8 models
12 answers · 9 models
11 answers · 9 models
10 answers · 6 models
10 answers · 8 models
10 answers · 6 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 |
|---|---|---|---|---|---|---|---|---|
| Awardco awardco.com | 29% | 152 | 27,100 | 303 | 32,927 | 14 | ||
| Workhuman workhuman.com | 22% | 95 | 4,400 | 158 | 373,538 | $160,162 | 72 | |
| Achievers achievers.com | 21% | 107 | 6,600 | 69,832 | 295,924 | 5 | 4 | |
| Bonusly bonusly.com | 5% | 200 | 14,800 | 75 | 44,595 | 21 | 2 | |
| Tremendous tremendous.com | 5% | 8 | 5 | |||||
| Recognize recognizeapp.com | 3% | 12 | 74,000 | 110,244 | 35,069 | 8 | 6 | |
| O.C. Tanner octanner.com O.C. Tanner Culture Cloud 2% | 2% | 51 | 30 | 1 | 60,022 company | 23 | 7 | |
| Kudos kudos.com | 2% | 46 | 60,500 | 3,826 | 26,553 | 10 | 4 | |
| Empuls | 2% | |||||||
| Assembly joinassembly.com | 2% | 97 | 90,500 | 76,788 | 10,398 | 7 |
Google's top ten for the three searches hold 18 sites; 5 of them are among the sites the models cited here (achievers.com, bonusly.com, octanner.com, selectsoftwarereviews.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 4.5WorkhumanAchievers, AwardcoChangedAchievers, WorkhumanAchievers, Empulsno first choicenothing named
Three alternatives
Achievers, Awardco, O.C. Tanner Culture CloudOne alternative
WorkhumanThree alternatives
Awardco, Motivosity, O.C. Tanner Culture CloudTwo alternatives
Assembly, MotivosityGPT-5.4 miniWorkhumanWorkhumanHeldAchievers, WorkhumanAwardcoagainst: Bonuslyno first choicenothing named
Three alternatives
Achievers, Awardco, O.C. Tanner Culture CloudTwo alternatives
Achievers, AwardcoSix alternatives
Assembly, Awardco, Bonusly, Bucketlist Rewards, Reward Gateway, Vantage CircleOne alternative
GuustoGemini 3.5 FlashAwardcoWorkhumanChangedWorkhumanAwardcono first choiceagainst: Assembly, Bonusly, Cooleaf, Motivosity, Nectar
Four alternatives
Achievers, O.C. Tanner Culture Cloud, WorkTango, WorkhumanFive alternatives
Achievers, Bonusly, Empuls, Reward Gateway, Vantage CircleFour alternatives
Achievers, Awardco, Kudos, O.C. Tanner Culture CloudThree alternatives
Empuls, Nectar, WorkTangoPerplexity SonarWorkhumanagainst: BonuslyAwardcoChangedWorkhumanagainst: BonuslyAwardcoagainst: Achievers, Workhumanno first choicenothing named
Two alternatives
Achievers, AwardcoThree alternatives
Achievers, Workhuman, Xoxoday PlumFive alternatives
Achievers, Awardco, Motivosity, O.C. Tanner Culture Cloud, WorkTangoOne alternative
AssemblyGrok 4.20Workhumanagainst: Motivosity, NectarAchieversChangedagainst: Motivosity, Tremendous, WorkTangoDeepgram, Speechmaticsagainst: Amazon Transcribe, OpenAI WhisperWorkhumanno first choiceagainst: Amazon Rekognition, Clearview AI, IBM Watson Visual Recognition, Microsoft Azure Face API
Three alternatives
Achievers, Awardco, BonuslyTwo alternatives
Awardco, WorkhumanFour alternatives
AssemblyAI, Azure AI Speech, Google Cloud Speech-to-Text, IBM Watson Speech to TextThree alternatives
Achievers, Bonusly, O.C. Tanner Culture CloudMistral SmallAwardco, BonuslyAwardco, TremendousChangedBonuslyAchievers, Awardcono first choiceagainst: 15Five, Culture Amp, Engagedly, Lattice, Motivosity, Vantage Circle
Two alternatives
Achievers, WorkhumanTwo alternatives
Achievers, O.C. Tanner Culture CloudFour alternatives
Awardco, O.C. Tanner Culture Cloud, Recognize, WorkTangoDeepSeek V4 FlashAchievers, WorkhumanAwardcoChangedagainst: BonuslyBonuslyAwardcoagainst: Achievers, Guusto, O.C. Tanner Culture Cloud, WorkhumanBonuslyagainst: Assembly, Workhumanagainst: Achievers, Bonusly, Kudos, Motivosity, Recognition One, WorkTango
One alternative
AwardcoTwo alternatives
Achievers, WorkhumanSeven alternatives
Achievers, Amazon Rekognition, Awardco, Google Cloud Vision AI, Microsoft Azure AI Vision, O.C. Tanner Culture Cloud, WorkhumanTwo alternatives
Bonusly, RecognizeThree alternatives
Achievers, Awardco, O.C. Tanner Culture CloudLlama 4 Maverickno first choiceAchievers, Awardco, TremendousChangedno first choiceAwardcono first choicenothing named
One alternative
EmpulsQwen 3.7 FlashRecognizeTremendousChangedWorkhumanMotivosityno first choiceagainst: Bonusly
Three alternatives
Achievers, Bonusly, WorkhumanThree alternatives
Achievers, Awardco, O.C. Tanner Culture CloudFour alternatives
Achievers, Awardco, Bonusly, O.C. Tanner Culture CloudTwo alternatives
RewardGateway, WorkhumanKimi K2Achievers, Workhumanagainst: BonuslyWorkhumanChangedAchievers, WorkhumanAwardcoagainst: Achievers, Empuls, Workhumanno first choicenothing named
One alternative
AwardcoTwo alternatives
Achievers, AwardcoFour alternatives
Awardco, Bonusly, Kudos, O.C. Tanner Culture CloudOne alternative
BonuslyGLM 4.7 FlashXWorkhumanAwardcoChangedno first choiceAchievers, Awardcono first choiceagainst: Assembly, Awardco, Bonusly
Three alternatives
Achievers, Awardco, BonuslyThree alternatives
Achievers, Bonusly, WorkhumanFive alternatives
Assembly, Bonusly, Empuls, Matter, WorkhumanMiniMax M2.5Awardco, Kudos, RecognizeAchieversChangedAchievers, WorkhumanAssembly, Bonuslyno first choicenothing named
Two alternatives
Achievers, O.C. Tanner Culture CloudTwo alternatives
Bucketlist Rewards, WorkhumanOne alternative
BonuslyTwo alternatives
Awardco, HeyTacoGPT-6 LunaWorkhumanAchieversChangedno first choiceWorkstarsno first choicenothing named
Two alternatives
Achievers, AwardcoTwo alternatives
Awardco, WorkhumanSeven alternatives
Achievers, Awardco, Kudos, O.C. Tanner Culture Cloud, Reward Gateway \| Edenred, WorkTango, WorkhumanTwo alternatives
Awardco, MotivosityMuse Glimmer 30BAchievers, O.C. Tanner Culture Cloud, WorkhumanAchieversChangedBonuslyAccess Perks Ascend, Matteragainst: Achievers, Awardco, Workhumanno first choiceagainst: Bonusly, Flaree, Matter, Nectar
Two alternatives
Awardco, BonuslyTwo alternatives
Awardco, O.C. Tanner Culture CloudSeven alternatives
Achievers, Assembly, Awardco, Kudos, Motivosity, O.C. Tanner Culture Cloud, WorkhumanOne alternative
HeyTacoBold 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.
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 | 2026-11-01 10:19 | yes | 10 | 8 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:08 | yes | 4 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 10:56 | yes | 8 | 17 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-11-01 11:12 | yes | 10 | 3 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:30 | yes | 10 | 31 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 11:53 | yes | 5 | 5 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 09:21 | yes | 24 | 27 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 09:28 | yes | 5 | 4 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 12:41 | yes | 5 | 20 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 12:18 | yes | 15 | 23 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 11:47 | yes | 15 | 21 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 10:11 | yes | 5 | 31 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-11-01 11:59 | yes | 3 | 13 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 09:57 | yes | 11 | 18 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 10:23 | yes | 17 | 9 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:29 | yes | 3 | 5 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 08:57 | no | 0 | 18 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-11-01 10:46 | yes | 10 | 4 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:27 | yes | 5 | 27 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 12:13 | yes | 5 | 5 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 12:19 | yes | 25 | 31 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 10:07 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 09:12 | yes | 5 | 26 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 10:05 | yes | 15 | 33 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 10:56 | yes | 22 | 52 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 11:35 | yes | 5 | 28 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-11-01 10:04 | yes | 3 | 12 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 12:30 | yes | 15 | 21 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 10:04 | yes | 16 | 11 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 09:12 | yes | 5 | 8 s |
| Comparative | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 10:23 | yes | 12 | 26 s |
| Comparative | Perplexity Sonar | sonar | 2026-11-01 10:12 | yes | 10 | 5 s |
| Comparative | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:24 | yes | 5 | 31 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 12:48 | yes | 10 | 11 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 11:34 | yes | 24 | 35 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 12:05 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 11:27 | yes | 8 | 22 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 09:21 | yes | 20 | 51 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 10:03 | yes | 25 | 65 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 10:11 | yes | 15 | 41 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-11-01 09:02 | yes | 7 | 25 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 12:53 | yes | 14 | 27 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 11:04 | yes | 9 | 9 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:10 | yes | 3 | 5 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 09:03 | yes | 12 | 17 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-11-01 11:40 | yes | 10 | 3 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:16 | yes | 23 | 33 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 09:13 | yes | 5 | 4 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 10:08 | yes | 24 | 23 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 10:51 | yes | 5 | 3 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 12:36 | no | 0 | 30 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 10:15 | yes | 23 | 30 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 08:47 | yes | 14 | 37 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 09:50 | yes | 9 | 43 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 11:12 | yes | 3 | 14 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 12:37 | yes | 21 | 40 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 11:42 | no | 0 | 8 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 10:46 | no | 0 | 6 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 12:36 | no | 0 | 20 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-11-01 08:50 | yes | 10 | 11 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:03 | yes | 15 | 40 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 10:53 | no | 0 | 8 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 12:22 | yes | 17 | 39 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 10:10 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 11:37 | no | 0 | 30 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 10:51 | yes | 15 | 24 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 10:55 | yes | 15 | 23 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 10:07 | no | 0 | 21 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 08:42 | yes | 2 | 18 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 10:07 | yes | 13 | 21 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 12:25 | yes | 19 | 8 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:38 | no | 0 | 3 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.6-flash (asked for gemini-3.5-flash; the API answered as this version) | 2026-11-01 10:39 | yes | 7 | 24 s |
| Negative framing | Perplexity Sonar | sonar | 2026-11-01 12:32 | yes | 10 | 5 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 13:16 | yes | 14 | 27 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 12:10 | yes | 14 | 10 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 08:52 | yes | 25 | 36 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 11:09 | yes | 5 | 2 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 10:59 | yes | 10 | 20 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 09:29 | yes | 25 | 32 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 10:23 | yes | 25 | 59 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 09:48 | yes | 15 | 62 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-11-01 10:40 | no | 0 | 3 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 11:44 | yes | 25 | 40 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
O.C. Tanner read as O.C. Tanner Culture Cloud
O.C. Tanner (Culture Cloud) read as O.C. Tanner Culture Cloud
Unresolved, counted raw
AI Monk
Access Perks Ascend
Amazon Transcribe
AssemblyAI
Ayonix
Azure AI Speech
Deepgram
Google Cloud Vision AI
IBM Watson Speech to Text
Innovatrics
Krisp
Mozo
Nuance Dragon
OpenAI Whisper
Paravision
Popupmaker
Recognition One (Recognize)
Reward Gateway \| Edenred
RewardGateway
Speechmatics
WorkProud
Discontinued, still offered
No shut-down product was recommended here.