ML platforms for enterprise buyers
Asked as “machine learning platform”, and as “MLOps platform for training and deploying models”, 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
49%
Clear leader
49Databricks Mosaic AI29Azure Machine Learning08Amazon SageMaker14others
49% of first choices, clear leader.
Since October 2026▲+5Since October 2026: 44% → 49%, +5 points. Inside the 11-point floor: within noise.Databricks Mosaic AI held the lead, +5 points on 44%, 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
Google Vertex AI20%Contested▲+1Since October 2026: 19% → 20%, +1 point. Inside the 11-point floor: within noise.Standing →Mid-market
Databricks Mosaic AI24%Contested↗new leaderNew leader since October 2026: Databricks Mosaic AI (24%) replaces Azure Machine Learning (21% then, 19% now), 5 points clear, inside the 11-point floor.Standing →EnterpriseDatabricks Mosaic AI49%Clear leader▲+5Since October 2026: 44% → 49%, +5 points. Inside the 11-point floor: within noise.This page
Google Vertex AI20%Contested▲+1Since October 2026: 19% → 20%, +1 point. Inside the 11-point floor: within noise.Standing →Mid-marketDatabricks Mosaic AI24%Contested↗new leaderNew leader since October 2026: Databricks Mosaic AI (24%) replaces Azure Machine Learning (21% then, 19% now), 5 points clear, inside the 11-point floor.Standing →EnterpriseDatabricks Mosaic AI49%Clear leader▲+5Since October 2026: 44% → 49%, +5 points. Inside the 11-point floor: within noise.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
01Databricks Mosaic AI49%5%61endorsed leader▲+5Since October 2026: 44% → 49%, +5 points. Inside the 11-point floor: within noise.44% → 49%
Databricks Mosaic AI49%5%61endorsed leader▲+5Since October 2026: 44% → 49%, +5 points. Inside the 11-point floor: within noise.44% → 49%02
Azure Machine Learning29%17%66accepted challenger▲+18Since October 2026: 11% → 29%, +18 points. Past the 11-point floor: movement.11% → 29%
Azure Machine Learning29%17%66accepted challenger▲+18Since October 2026: 11% → 29%, +18 points. Past the 11-point floor: movement.11% → 29%03
Amazon SageMaker8%25%64criticized challenger▼−5Since October 2026: 13% → 8%, −5 points. Inside the 11-point floor: within noise.13% → 8%
Amazon SageMaker8%25%64criticized challenger▼−5Since October 2026: 13% → 8%, −5 points. Inside the 11-point floor: within noise.13% → 8%04
Dataiku6%3%32accepted challenger▼−1Since October 2026: 7% → 6%, −1 point. Inside the 11-point floor: within noise.7% → 6%
Dataiku6%3%32accepted challenger▼−1Since October 2026: 7% → 6%, −1 point. Inside the 11-point floor: within noise.7% → 6%05Google Vertex AI Lab in the set4%29%51criticized challenger=heldSince October 2026: 4% → 4%, ±0 points. Inside the 11-point floor: within noise.4% → 4%
Google Vertex AI Lab in the set4%29%51criticized challenger=heldSince October 2026: 4% → 4%, ±0 points. Inside the 11-point floor: within noise.4% → 4%06
Domino Data Lab4%6%16accepted challenger▼−5Since October 2026: 9% → 4%, −5 points. Inside the 11-point floor: within noise.9% → 4%
Domino Data Lab4%6%16accepted challenger▼−5Since October 2026: 9% → 4%, −5 points. Inside the 11-point floor: within noise.9% → 4%Show the five products at 0%, ordered by negative rate
11
Kubeflow0%50%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Kubeflow0%50%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%10
MLflow0%50%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
MLflow0%50%12criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%09
Snowflake Cortex AI0%23%13accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Snowflake Cortex AI0%23%13accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%07
DataRobot0%6%33accepted challenger▼−7Since October 2026: 7% → 0%, −7 points. Inside the 11-point floor: within noise.7% → 0%
DataRobot0%6%33accepted challenger▼−7Since October 2026: 7% → 0%, −7 points. Inside the 11-point floor: within noise.7% → 0%08IBM watsonx.ai0%0%10accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.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 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.
Google Vertex AI is made by Google, whose model Gemini 3.5 Flash is in the set. On the four share prompts that model made it the first choice zero times of 4; the other thirteen models two times of 52. Lab treatment is defined on the method page; the row is marked, not excluded.
For buyers
Head to head
Databricks Mosaic AI vs Azure Machine LearningDatabricks Mosaic AI vs DataikuDatabricks Mosaic AI vs Amazon SageMaker
Head-to-head pages are published for mid-market buyers, so these open on mid-market figures, not enterprise.All twenty-eight head-to-head pages: the top eight products, each against each
Databricks Mosaic AI vs MLflowDatabricks Mosaic AI vs Snowflake Cortex AIDatabricks Mosaic AI vs PyTorchDatabricks Mosaic AI vs TensorFlowAzure Machine Learning vs DataikuAzure Machine Learning vs Amazon SageMakerAzure Machine Learning vs MLflowAzure Machine Learning vs Snowflake Cortex AIAzure Machine Learning vs PyTorchAzure Machine Learning vs TensorFlowDataiku vs Amazon SageMakerDataiku vs MLflowDataiku vs Snowflake Cortex AIDataiku vs PyTorchDataiku vs TensorFlowAmazon SageMaker vs MLflowAmazon SageMaker vs Snowflake Cortex AIAmazon SageMaker vs PyTorchAmazon SageMaker vs TensorFlowMLflow vs Snowflake Cortex AIMLflow vs PyTorchMLflow vs TensorFlowSnowflake Cortex AI vs PyTorchSnowflake Cortex AI vs TensorFlowPyTorch vs TensorFlow
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 →
01020304050607I08
091011Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative60%
Key
01Databricks Mosaic AI49%
Databricks Mosaic AI49%02Azure Machine Learning29%
Azure Machine Learning29%03Amazon SageMaker8%
Amazon SageMaker8%04Dataiku6%
Dataiku6%05Google Vertex AI4%
Google Vertex AI4%06Domino Data Lab4%
Domino Data Lab4%07DataRobot0%
DataRobot0%08IBM watsonx.ai0%
09Snowflake Cortex AI0%
Snowflake Cortex AI0%10MLflow0%
MLflow0%11Kubeflow0%
Kubeflow0%What they warned about
Seven of fourteen models held their first choice under the paraphrase. GPT-5.4 mini, Grok 4.20, Qwen 3.7 Flash, Kimi K2, GLM 4.7 FlashX, MiniMax M2.5 and GPT-6 Luna 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.
Amazon SageMaker25%
16 of 64 labels negative · 11 of 14 models · 2 hard negative
“What to Avoid for Cost Predictability | Amazon SageMaker | Usage-based ... High” DeepSeek V4 Flash, budget prompt
Google Vertex AI29%
15 of 51 labels negative · 10 of 14 models · 3 hard negative
“What I'd Avoid or Delay: Google Vertex AI: While clean and user-friendly, it lags in enterprise governance features” Kimi K2, paraphrase prompt
Azure Machine Learning17%
11 of 66 labels negative · 8 of 14 models
“While AWS SageMaker, Azure ML, and Google Vertex AI are excellent, becoming entirely dependent on one means that if your pricing changes or you need to migrate workloads to a competitor, you face massive technical debt.” Qwen 3.7 Flash, negative prompt
Kubeflow50%
6 of 12 labels negative · 5 of 14 models · 2 hard negative
“Pure open-source (Kubeflow/MLflow self-hosted): At "thousands of employees" scale, the operational overhead of self-managing these becomes prohibitive” Kimi K2, paraphrase 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
72 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. 858 links across 330 sites, every framing counted. Ranked by the number of answers carrying the site or page. 54 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.
33 answers · 38 citations · 10 models
vendor site · G225 answers · 36 citations · 10 models
vendor site · Dataiku19 answers · 22 citations · 10 models
publisher (Gane)15 answers · 17 citations · 7 models
vendor site · Prompts.ai14 answers · 17 citations · 10 models
14 answers · 14 citations · 7 models
vendor site · Microsoft13 answers · 24 citations · 10 models
vendor site · LinkedIn13 answers · 18 citations · 6 models
vendor site · Microsoft13 answers · 17 citations · 7 models
vendor site · IBM11 answers · 11 citations · 8 models
vendor site · Amazon10 answers · 17 citations · 7 models
10 answers · 11 citations · 7 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.
24 answers · 10 models
15 answers · 7 models
13 answers · 10 models
11 answers · 9 models
11 answers · 8 models
9 answers · 7 models
8 answers · 5 models
8 answers · 5 models
8 answers · 6 models
8 answers · 5 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 machine learning platform”, “machine learning platform”, “machine learning 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 |
|---|---|---|---|---|---|---|---|
| Databricks databricks.com Databricks Mosaic AI 49% | 49% | 125 | 135,000 | 8,368 | 689,756 company | $34,664 | 120 |
| Azure parent site Azure Machine Learning 29% | 29% | 148 | 301,000 | 47,904 | |||
| Amazon parent site Amazon SageMaker 8% | 8% | 159 | 151,000,000 | 1,380,939 | |||
| Dataiku dataiku.com | 6% | 74 | 9,900 | 266 | 12,714 | 93 | |
| Google Vertex AI cloud.google.com | 4% | 135 | 5,400 | 226 | 7,405,347 | ||
| Domino domino.ai Domino Data Lab 4% | 4% | 28 | 1,900 | 57 | 18,579 company | 36 | |
| DataRobot datarobot.com | 0% | 79 | 5,400 | 169 | 9,791 | 25 | |
| IBM parent site IBM watsonx.ai 0%, IBM Watson Studio 0% | 0% | 16 | 201,000 | 34,098 | |||
| SAS Viya sas.com | 0% | 27 | 2,400 | 89 | 431,607 | 42 | |
| H2O.ai h2o.ai | 0% | 28 | 880 | 78 | 59,586 |
Google's top ten for the three searches hold 22 sites; 1 of them are among the sites the models cited here (aws.amazon.com). The first result for “best machine learning platform” is anaconda.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 machine learning platform for an enterprise B2B company?”Paraphrase“Which MLOps platform for training and deploying models would you recommend to a large B2B company with thousands of employees?”Comparative“What are the top enterprise-grade machine learning platforms and how do they differ?”Budget-constrained“What is the best machine learning 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 machine learning platform. What should we look at?”Negative“Which machine learning platforms should a large enterprise avoid or be cautious about?”
Claude Haiku 4.5Databricks Mosaic AIDatabricks Mosaic AIHeldDatabricks Mosaic AIAzure Machine Learningno first choiceagainst: Amazon SageMaker, Azure Machine Learning, Google Cloud, Google Vertex AI, OpenAI
Five alternatives
Amazon SageMaker, Azure Machine Learning, Cloudera, DataRobot, Google Vertex AIThree alternatives
Amazon SageMaker, Azure Machine Learning, Domino Data LabThree alternatives
DataRobot, Google Vertex AI, Microsoft Azure ML StudioGPT-5.4 miniDatabricks Mosaic AIAzure Machine LearningChangedno first choiceAzure Machine Learningagainst: Amazon SageMaker, Google Cloud, Google Vertex AIno first choicenothing named
Three alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AITwo alternatives
Amazon SageMaker, Databricks Mosaic AITwo alternatives
Cake Platform, Karini AIGemini 3.5 FlashDatabricks Mosaic AIagainst: Snowflake Cortex AIDatabricks Mosaic AIHeldAmazon SageMakerDomino Data Labagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AIno first choiceagainst: Amazon SageMaker, Azure Machine Learning, GCP Vertex AI, IBM Watson, SAS Enterprise Miner / SAS 9
Five alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, Dataiku, Google Vertex AIFour alternatives
Amazon SageMaker, Azure Machine Learning, Dataiku, Domino Data LabFive alternatives
Azure Machine Learning, DataRobot, Databricks Mosaic AI, Dataiku, Google Vertex AIFour alternatives
Dataiku, Kubeflow, Ray, Run:aiPerplexity SonarDatabricks Mosaic AIDatabricks Mosaic AIHeldagainst: MLflowAmazon SageMaker, Azure Machine Learning, Google Vertex AIDataikuagainst: Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Google Vertex AIno first choiceagainst: Amazon Bedrock, Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Kubernetes, PyTorch, Snowflake Cortex AI, TensorFlow
Four alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, Google Vertex AIFour alternatives
Amazon SageMaker, Azure Machine Learning, Domino Data Lab, Google Vertex AIFour alternatives
DataRobot, Databricks Mosaic AI, Dataiku, IBM watsonx.aiGrok 4.20Databricks Mosaic AIagainst: MLflowAmazon SageMakerChangedagainst: Comet, DataRobot, Databricks Mosaic AI, Dataiku, Domino Data Lab, Kubeflow, MLflow, Weights & Biasesno first choiceagainst: Weights & BiasesAzure Machine Learningagainst: Amazon SageMaker, Databricks Mosaic AI, Google Vertex AIno first choiceagainst: Amazon SageMaker, Anthropic's Claude, Azure Machine Learning, Azure OpenAI Service, Google Vertex AI, Google's Gemini, Hugging Face, Kubeflow, MLflow, OpenAI, OpenAI's ChatGPT, Perplexity Enterprise Pro
Three alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AITwo alternatives
Azure Machine Learning, Google Vertex AIOne alternative
DataikuFour alternatives
Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Google Vertex AIMistral SmallDatabricks Mosaic AIDatabricks Mosaic AIHeldAmazon SageMaker, Azure Machine Learning, Google Vertex AIAzure Machine Learning, Google Vertex AIagainst: Kubeflow, MLflowno first choicenothing named
Two alternatives
Amazon SageMaker, Azure Machine LearningFive alternatives
Amazon SageMaker, Azure Machine Learning, Dataiku, Domino Data Lab, Google Vertex AIFour alternatives
DataRobot, Databricks Mosaic AI, Dataiku, IBM Watson StudioTwo alternatives
Amazon SageMaker, Databricks Mosaic AIDeepSeek V4 FlashDatabricks Mosaic AIDatabricks Mosaic AIHeldAmazon SageMakerDataikuagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AIno first choiceagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Kubeflow
Four alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, DataikuFour alternatives
Amazon SageMaker, Azure Machine Learning, Dataiku, Domino Data LabSix alternatives
Azure Machine Learning, DataRobot, Databricks Mosaic AI, Dataiku, Google Vertex AI, Snowflake Cortex AITwo alternatives
DataRobot, Databricks Mosaic AILlama 4 MaverickDatabricks Mosaic AIDatabricks Mosaic AIHeldDatabricks Mosaic AIAmazon SageMaker, Azure Machine Learning, Databricks Mosaic AIno first choiceagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AI
Two alternatives
Amazon SageMaker, Azure Machine LearningTwo alternatives
Amazon SageMaker, Azure Machine LearningFour alternatives
Amazon SageMaker, Azure Machine Learning, IBM watsonx.ai, SAS ViyaQwen 3.7 FlashDatabricks Mosaic AIagainst: Snowflake Cortex AIAzure Machine Learning, Databricks Mosaic AIChangedagainst: KubeflowAmazon SageMaker, Databricks Mosaic AIAzure Machine Learningno first choiceagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AI
Four alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, Google Vertex AIOne alternative
Amazon SageMakerFour alternatives
Azure Machine Learning, DataRobot, Google Vertex AI, IBM watsonx.aiThree alternatives
DataRobot, Databricks Mosaic AI, Domino Data LabKimi K2Databricks Mosaic AIAzure Machine LearningChangedagainst: Google Vertex AI, KubeflowAmazon SageMaker, Azure Machine Learning, Google Vertex AIDataikuagainst: Amazon SageMaker, Google Vertex AIno first choiceagainst: Amazon Bedrock, Azure AI Foundry, DataRobot
Three alternatives
Amazon Bedrock, Amazon SageMaker, DataikuTwo alternatives
Amazon SageMaker, Databricks Mosaic AIThree alternatives
DataRobot, Databricks Mosaic AI, DataikuThree alternatives
Azure Machine Learning, DataRobot, Databricks Mosaic AIGLM 4.7 FlashXAmazon SageMaker, Azure Machine Learning, Google Vertex AIDatabricks Mosaic AIChangedno first choiceAzure Machine Learningno first choiceagainst: ChatGPT, Microsoft Copilot
Three alternatives
DataRobot, Databricks Mosaic AI, DataikuThree alternatives
Amazon SageMaker, Azure Machine Learning, Domino Data LabTwo alternatives
Amazon SageMaker, Google Vertex AIMiniMax M2.5Azure Machine Learning, Databricks Mosaic AIAmazon SageMakerChangedno first choiceAzure Machine Learningagainst: Amazon SageMakerno first choiceagainst: Amazon SageMaker Canvas, Google Vertex AI AutoML, MLflow
Three alternatives
Alteryx Machine Learning, Dataiku, SAS ViyaThree alternatives
Azure Machine Learning, Databricks Mosaic AI, Google Vertex AIThree alternatives
DataRobot, Databricks Mosaic AI, DataikuGPT-6 LunaDatabricks Mosaic AIAzure Machine LearningChangedno first choiceDomino Data Labno first choiceagainst: GitHub Models, Humanloop, Neptune's hosted service
Three alternatives
Amazon SageMaker, Azure Machine Learning, Google Cloud's Gemini Enterprise Agent PlatformThree alternatives
Amazon SageMaker, Databricks Mosaic AI, Google's Agent PlatformThree alternatives
Azure Machine Learning, Databricks Mosaic AI, SageMaker AIMuse Glimmer 30BDatabricks Mosaic AIDatabricks Mosaic AIHeldAzure Machine Learning, Microsoft FoundryDatabricks Mosaic AIagainst: Amazon SageMaker, Google Vertex AIno first choiceagainst: Amazon SageMaker, Azure Machine Learning, ChatGPT, ChatGPT free version, Claude, Databricks proprietary services, DeepSeek consumer app, Google Gemini, Google Vertex AI
Six alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, Dataiku, Google Vertex AI, IBMFive alternatives
Amazon SageMaker, Azure AI Foundry, Azure Machine Learning, Google Vertex AI, MLflowNine alternatives
Amazon SageMaker, DataRobot, Databricks Mosaic AI, Dataiku, Domino Data Lab, Gemini Enterprise Agent Platform, Google Vertex AI, SAS Viya, Snowflake Cortex AIThree alternatives
Azure Machine Learning, DataRobot, Domino Data LabBold 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 14:27 | no | 0 | 5 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 17:04 | yes | 3 | 8 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 14:14 | no | 0 | 14 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-11-01 11:37 | yes | 10 | 4 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:55 | yes | 5 | 12 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 11:55 | yes | 5 | 10 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 08:57 | yes | 24 | 31 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 15:08 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 14:58 | yes | 10 | 22 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 08:56 | yes | 15 | 26 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 15:57 | yes | 15 | 27 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 19:09 | yes | 5 | 19 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-11-01 18:11 | yes | 2 | 19 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 14:00 | yes | 14 | 20 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 12:24 | yes | 10 | 8 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 17:54 | yes | 3 | 6 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 16:00 | yes | 4 | 22 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-11-01 13:05 | yes | 10 | 5 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 15:34 | yes | 5 | 9 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 15:28 | yes | 5 | 6 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 19:15 | yes | 21 | 42 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 12:38 | yes | 5 | 2 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 11:33 | no | 0 | 27 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 12:19 | yes | 10 | 35 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 10:46 | yes | 17 | 30 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 14:15 | yes | 5 | 16 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-11-01 15:03 | yes | 4 | 14 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 14:38 | yes | 15 | 22 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 17:57 | yes | 19 | 9 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 11:00 | yes | 6 | 17 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 18:51 | no | 0 | 16 s |
| Comparative | Perplexity Sonar | sonar | 2026-11-01 11:50 | yes | 10 | 6 s |
| Comparative | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:37 | yes | 5 | 13 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 15:23 | yes | 5 | 7 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 17:04 | yes | 22 | 52 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 13:26 | yes | 5 | 4 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 11:54 | yes | 5 | 33 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 12:10 | yes | 19 | 26 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 18:16 | yes | 19 | 44 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 18:34 | yes | 10 | 20 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-11-01 14:11 | yes | 7 | 18 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 18:02 | yes | 15 | 29 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 13:06 | yes | 19 | 8 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 14:18 | yes | 5 | 7 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 15:37 | no | 0 | 17 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-11-01 15:23 | yes | 10 | 3 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 18:33 | yes | 14 | 15 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 16:43 | yes | 5 | 6 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 10:25 | yes | 22 | 23 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 11:29 | yes | 6 | 4 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 15:47 | yes | 18 | 72 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 10:32 | yes | 25 | 62 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 13:04 | yes | 24 | 33 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 18:59 | yes | 24 | 76 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 19:32 | yes | 3 | 13 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 14:24 | yes | 15 | 24 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 12:23 | no | 0 | 6 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 14:16 | yes | 0 | 7 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 13:40 | no | 0 | 21 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-11-01 15:14 | yes | 10 | 8 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 14:52 | yes | 10 | 17 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 18:30 | no | 0 | 7 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 15:06 | yes | 25 | 45 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 11:48 | yes | 5 | 2 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 19:14 | yes | 5 | 35 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 10:21 | yes | 24 | 33 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 09:43 | yes | 15 | 33 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 12:52 | yes | 20 | 48 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 09:55 | yes | 3 | 17 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 09:15 | yes | 15 | 17 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 13:55 | yes | 19 | 11 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:51 | yes | 6 | 6 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 16:29 | no | 0 | 21 s |
| Negative framing | Perplexity Sonar | sonar | 2026-11-01 14:59 | yes | 10 | 5 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 18:37 | yes | 5 | 11 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 13:13 | yes | 15 | 12 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 12:17 | yes | 24 | 42 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 14:17 | yes | 5 | 3 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 14:20 | no | 0 | 28 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 16:41 | yes | 25 | 30 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 18:18 | yes | 25 | 30 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 18:30 | no | 0 | 29 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-11-01 17:16 | yes | 4 | 17 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 16:18 | yes | 24 | 42 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
Azure OpenAI read as Azure OpenAI Service
Databricks read as Databricks Mosaic AI
Databricks (MLflow / Mosaic AI Platform) read as Databricks Mosaic AI
Databricks (Mosaic AI / Data Intelligence Platform) read as Databricks Mosaic AI
Databricks (Mosaic AI / MLflow) read as Databricks Mosaic AI
Databricks (Mosaic AI) read as Databricks Mosaic AI
Databricks (Unity Platform) read as Databricks Mosaic AI
Databricks (with Mosaic AI & MLflow) read as Databricks Mosaic AI
Databricks (with Mosaic AI) read as Databricks Mosaic AI
Databricks Data Intelligence Platform read as Databricks Mosaic AI
Databricks Machine Learning read as Databricks Mosaic AI
Google Cloud AI/Vertex AI read as Google Vertex AI
IBM Watsonx read as IBM watsonx.ai
IBM watsonx read as IBM watsonx.ai
Palantir read as Palantir Foundry
Snowflake read as Snowflake Cortex AI
Snowflake (Cortex & Snowpark Container Services) read as Snowflake Cortex AI
Snowflake Cortex read as Snowflake Cortex AI
Snowflake ML read as Snowflake Cortex AI
Unresolved, counted raw
Altair
Anthropic's Claude
Azure AI
Cake Platform
ChatGPT free version
Databricks proprietary services
DeepSeek consumer app
Firework AI
Gemini platform
GitHub Models
Google Cloud's Vertex AI lineage
Google Vertex AI AutoML
Google's Agent Platform (formerly Vertex AI)
Google's Gemini
Humanloop
Karini AI
Neptune's hosted service
Neptune.ai
OpenAI's ChatGPT
Run:ai
SAS Enterprise Miner / SAS 9
SAS Institute
Discontinued, still offered
No shut-down product was recommended here.