ML platforms for small business buyers
Asked as “machine learning platform”, and as “MLOps platform for training and deploying models”, on behalf of a small B2B company. 56 first choices recorded across the direct, paraphrase, budget and scale prompts, fourteen models each.
Standing · first-choice share
20%
Contested · Azure Machine Learning 11%
20Google Vertex AI11Azure Machine Learning09Amazon SageMaker61others
20% of first choices, contested.
Since October 2026▲+1Since October 2026: 19% → 20%, +1 point. Inside the 11-point floor: within noise.Google Vertex AI held the lead, +1 point on 19%, 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.This pageMid-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.Standing →
Google Vertex AI20%Contested▲+1Since October 2026: 19% → 20%, +1 point. Inside the 11-point floor: within noise.This pageMid-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.Standing →The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all fourteen models, for a small B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrantSince October 2026
01Google Vertex AI Lab in the set20%20%49accepted challenger▲+1Since October 2026: 19% → 20%, +1 point. Inside the 11-point floor: within noise.19% → 20%
Google Vertex AI Lab in the set20%20%49accepted challenger▲+1Since October 2026: 19% → 20%, +1 point. Inside the 11-point floor: within noise.19% → 20%02
Azure Machine Learning11%23%57accepted challenger▲+6Since October 2026: 5% → 11%, +6 points. Inside the 11-point floor: within noise.5% → 11%
Azure Machine Learning11%23%57accepted challenger▲+6Since October 2026: 5% → 11%, +6 points. Inside the 11-point floor: within noise.5% → 11%03
MLflow9%10%31accepted challenger▲+3Since October 2026: 6% → 9%, +3 points. Inside the 11-point floor: within noise.6% → 9%
MLflow9%10%31accepted challenger▲+3Since October 2026: 6% → 9%, +3 points. Inside the 11-point floor: within noise.6% → 9%04
Google Colab Lab in the set9%6%18accepted challenger=heldSince October 2026: 9% → 9%, ±0 points. Inside the 11-point floor: within noise.9% → 9%
Google Colab Lab in the set9%6%18accepted challenger=heldSince October 2026: 9% → 9%, ±0 points. Inside the 11-point floor: within noise.9% → 9%05
Amazon SageMaker9%37%59criticized challenger▲+1Since October 2026: 8% → 9%, +1 point. Inside the 11-point floor: within noise.8% → 9%
Amazon SageMaker9%37%59criticized challenger▲+1Since October 2026: 8% → 9%, +1 point. Inside the 11-point floor: within noise.8% → 9%06
Hugging Face5%6%17accepted challenger=heldSince October 2026: 5% → 5%, ±0 points. Inside the 11-point floor: within noise.5% → 5%
Hugging Face5%6%17accepted challenger=heldSince October 2026: 5% → 5%, ±0 points. Inside the 11-point floor: within noise.5% → 5%07
DataRobot5%50%26criticized challenger▲+3Since October 2026: 2% → 5%, +3 points. Inside the 11-point floor: within noise.2% → 5%
DataRobot5%50%26criticized challenger▲+3Since October 2026: 2% → 5%, +3 points. Inside the 11-point floor: within noise.2% → 5%08
KNIME Analytics Platform4%6%18accepted challenger▼−4Since October 2026: 8% → 4%, −4 points. Inside the 11-point floor: within noise.8% → 4%
KNIME Analytics Platform4%6%18accepted challenger▼−4Since October 2026: 8% → 4%, −4 points. Inside the 11-point floor: within noise.8% → 4%09
scikit-learn4%0%12accepted challenger▲+2Since October 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise.2% → 4%
scikit-learn4%0%12accepted challenger▲+2Since October 2026: 2% → 4%, +2 points. Inside the 11-point floor: within noise.2% → 4%10Weights & Biases2%12%17accepted challenger=heldSince October 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise.2% → 2%
11
Dataiku2%32%19criticized challenger=heldSince October 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise.2% → 2%
Dataiku2%32%19criticized challenger=heldSince October 2026: 2% → 2%, ±0 points. Inside the 11-point floor: within noise.2% → 2%Show the four products at 0%, ordered by negative rate
15
Kubeflow0%85%13criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
Kubeflow0%85%13criticized challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%14Databricks Mosaic AI0%46%37criticized challenger▼−3Since October 2026: 3% → 0%, −3 points. Inside the 11-point floor: within noise.3% → 0%
Databricks Mosaic AI0%46%37criticized challenger▼−3Since October 2026: 3% → 0%, −3 points. Inside the 11-point floor: within noise.3% → 0%13
H2O.ai0%15%13accepted challenger▼−2Since October 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise.2% → 0%
H2O.ai0%15%13accepted challenger▼−2Since October 2026: 2% → 0%, −2 points. Inside the 11-point floor: within noise.2% → 0%12
RapidMiner0%0%10accepted challenger=heldSince October 2026: 0% → 0%, ±0 points. Inside the 11-point floor: within noise.0% → 0%
RapidMiner0%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 eleven times of 52. Google Colab 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 five 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 small business.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 →
010203040506070809W10
1112131415Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative30%
Key
01Google Vertex AI20%
Google Vertex AI20%02Azure Machine Learning11%
Azure Machine Learning11%03MLflow9%
MLflow9%04Google Colab9%
Google Colab9%05Amazon SageMaker9%
Amazon SageMaker9%06Hugging Face5%
Hugging Face5%07DataRobot5%
DataRobot5%08KNIME Analytics Platform4%
KNIME Analytics Platform4%09scikit-learn4%
scikit-learn4%10Weights & Biases2%
11Dataiku2%
Dataiku2%12RapidMiner0%
RapidMiner0%13H2O.ai0%
H2O.ai0%14Databricks Mosaic AI0%
Databricks Mosaic AI0%15Kubeflow0%
Kubeflow0%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 4.20, Mistral Small, DeepSeek V4 Flash, Llama 4 Maverick, Qwen 3.7 Flash, 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.
Databricks Mosaic AI46%
17 of 37 labels negative · 12 of 14 models · 4 hard negative
“Why to avoid: This platform is excellent for massive data lakes but is frequently criticized for being prohibitively expensive for small businesses.” GLM 4.7 FlashX, negative prompt
Amazon SageMaker37%
22 of 59 labels negative · 11 of 14 models · 8 hard negative
“Avoid or be very cautious with enterprise-focused, full-featured cloud ML services (SageMaker, Azure ML, Google Cloud AI Platform, IBM Watson)” Muse Glimmer 30B, negative prompt
Azure Machine Learning23%
13 of 57 labels negative · 10 of 14 models · 5 hard negative
“proprietary elements make migration painful. SMBs risk over-reliance on Microsoft partnerships that limit flexibility.” Grok 4.20, negative prompt
Google Vertex AI20%
10 of 49 labels negative · 9 of 14 models · 4 hard negative
“incredibly powerful but often disastrous for small teams due to complexity and cost” Qwen 3.7 Flash, negative 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
64 of 84 answers in this category came back with a source list, from 13 of 14 models: citations where the model returns them, or the search results it consulted. 703 links across 237 sites, every framing counted. Ranked by the number of answers carrying the site or page. The other 1 model searched through a gateway that returned no source list on this edition. 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.
vendor site · G244 answers · 89 citations · 11 models
27 answers · 44 citations · 10 models
publisher (Gane)24 answers · 24 citations · 10 models
13 answers · 14 citations · 6 models
11 answers · 12 citations · 8 models
vendor site · Amazon10 answers · 17 citations · 5 models
vendor site · GitHub10 answers · 15 citations · 6 models
vendor site · Qovery10 answers · 10 citations · 5 models
vendor site · G29 answers · 10 citations · 5 models
9 answers · 9 citations · 7 models
8 answers · 8 citations · 6 models
vendor site · Microsoft7 answers · 11 citations · 2 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
21 answers · 9 models
19 answers · 8 models
18 answers · 8 models
11 answers · 9 models
10 answers · 5 models
9 answers · 5 models
8 answers · 6 models
8 answers · 4 models
7 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 | Google ads, last 30 days |
|---|---|---|---|---|---|---|
| Google Vertex AI cloud.google.com | 20% | 135 | 5,400 | 226 | 7,405,347 | |
| Azure parent site Azure Machine Learning 11% | 11% | 148 | 301,000 | 47,904 | ||
| MLflow mlflow.org | 9% | 58 | 9,900 | 438 | 6,498 | 1 |
| Google Colab colab.research.google.com | 9% | 18 | 301,000 | 900 | 240,528 | |
| Amazon parent site Amazon SageMaker 9% | 9% | 159 | 151,000,000 | 1,380,939 | ||
| Hugging Face huggingface.co | 5% | 26 | 135,000 | 1,844 | 1,133,354 | 2 |
| DataRobot datarobot.com | 5% | 79 | 5,400 | 169 | 9,791 | 25 |
| KNIME Analytics Platform knime.com | 4% | 24 | 320 | 3 | 28,171 | 23 |
| scikit-learn scikit-learn.org | 4% | 6 | 12,100 | 555 | 312,623 | |
| Modal modal.com | 4% | 2 |
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 a small B2B company?”Paraphrase“Which MLOps platform for training and deploying models would you recommend to a small business that sells to other businesses?”Comparative“What are the top machine learning platforms for a small team and how do they differ?”Budget-constrained“What is the best machine learning platform for a small company with a tight budget?”Scale-constrained“We are a 30 person company evaluating a machine learning platform. What should we look at?”Negative“Which machine learning platforms should a small business avoid or be cautious about?”
Claude Haiku 4.5no first choiceagainst: Amazon SageMakerClearML, MLflowChangedagainst: DataikuAnyscale, Hugging Faceagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AIscikit-learnno first choiceagainst: AWS, Amazon SageMaker, Azure Machine Learning, DataRobot, Databricks Mosaic AI, Domino Data Lab, Google Vertex AI
Three alternatives
Arize Phoenix, Evidently, ReplicateSeven alternatives
DataRobot, H2O ai, KNIME Analytics Platform, MLflow, RapidMiner, Snowflake Cortex AI, scikit-learnFive alternatives
DataRobot, Google Colab, H2O.ai, PyTorch, TensorFlowGPT-5.4 miniAmazon SageMaker, Azure Machine LearningAzure Machine LearningChangedDatabricks Mosaic AIagainst: Kubeflow, MLflowGoogle Colabagainst: Databricks Mosaic AIno first choicenothing named
One alternative
Databricks Mosaic AIOne alternative
Databricks Mosaic AIFour alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Snowflake Cortex AISix alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AI, PyTorch, XGBoost, scikit-learnGemini 3.5 FlashObviously AIagainst: DataRobot, DataikuBaseten, ModalChangedagainst: Amazon SageMaker, Kubeflow, RayGoogle Vertex AIHugging Face, Modal, PyCaretagainst: Amazon SageMaker, DataRobot, GCP Vertex AIno first choiceagainst: Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, GCP Vertex AI, Kubeflow, Snowflake Cortex AIagainst: Amazon SageMaker, Apache Airflow, Azure Machine Learning, C3 AI, DataRobot, Google Vertex AI, Kubeflow, MLflow, Palantir Foundry, SAS Enterprise Miner
Five alternatives
AWS SageMaker Canvas, BigML, Google Vertex AI, Microsoft Azure Automated ML, OpenAI APIFive alternatives
AWS ECS, GCP Vertex AI, MLflow, Railway, RenderSeven alternatives
Amazon SageMaker, Azure Machine Learning, Baseten, Databricks Mosaic AI, Hugging Face, Modal, Weights & BiasesNine alternatives
FLAML, GCP Cloud Run, Google Colab, Local Jupyter Notebooks, MLflow, Replicate, RunPod, Vast.ai, Weights & BiasesSix alternatives
Anyscale, Baseten, MLflow, Modal, Replicate, Weights & BiasesPerplexity SonarGoogle Vertex AIagainst: Akkio, DataRobot, Databricks Mosaic AIMLflowChangedagainst: Databricks Mosaic AI, Weights & BiasesGoogle Vertex AIagainst: Databricks Mosaic AITensorFlow, XGBoost, scikit-learnno first choiceagainst: Amazon Personalize, Amazon SageMaker, Anyscale, Azure Machine Learning, DataRobot, Databricks Lakehouse Platform, Google Vertex AI, H2O Driverless AI, IBM Watson, Kubeflow
Three alternatives
Amazon SageMaker, Azure Machine Learning, H2O.aiThree alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AIEight alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, H2O.ai, MLflow, Modal, Replicate, Together AIFive alternatives
Amazon SageMaker, Deepnote, Google Vertex AI, Paperspace, SageMaker CanvasGrok 4.20Google Vertex AIagainst: TensorFlowAmazon SageMaker, Azure Machine LearningChangedagainst: Databricks Mosaic AIGoogle Vertex AIGoogle Colabagainst: Amazon SageMaker, DataRobot, DataikuAzure Machine Learning, Google Vertex AIagainst: Hugging Face, Kubeflowagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AI, IBM Watson
Four alternatives
Amazon SageMaker, Azure Machine Learning, BigML, DataRobotThree alternatives
MLflow, Roboflow, Weights & BiasesSix alternatives
Alteryx, Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Dataiku, Hugging FaceFive alternatives
Azure Machine Learning, Google Vertex AI, Hugging Face, KNIME Analytics Platform, MLflowFive alternatives
Amazon SageMaker, DataRobot, Databricks Mosaic AI, H2O.ai, MLflowMistral SmallGoogle Vertex AI, OpenAI PlatformMLflowChangedno first choiceagainst: Amazon SageMakerGoogle Vertex AI, KNIME Analytics Platformno first choiceagainst: Amazon SageMaker, Azure Machine Learning, DagsHub, Databricks Mosaic AI, Dataiku, Kubeflow
Three alternatives
Akkio, Amazon SageMaker, KNIME Analytics PlatformThree alternatives
Amazon SageMaker, DataRobot, Google Vertex AIFour alternatives
Fiddler AI, Picsellia, Superwise AI, TensorFlowTwo alternatives
Azure Machine Learning, MLflowDeepSeek V4 FlashGoogle Vertex AIagainst: DataRobot, SAS ViyaMLflowChangedagainst: DataRobot, Databricks Mosaic AI, Kubeflow, Weights & BiasesGoogle Vertex AIagainst: Databricks Mosaic AI, Dataiku, KubeflowGoogle Colabagainst: Amazon SageMakerno first choiceagainst: Apache Airflow, Kubeflow, MLflowagainst: Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Dataiku, Google Vertex AI, H2O.ai, IBM Watson, Kubeflow, SAS Viya
Three alternatives
Azure Machine Learning, BigML, LevityThree alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AIFive alternatives
Amazon SageMaker, Azure Machine Learning, KNIME Analytics Platform, MLflow, RapidMinerFour alternatives
Anaconda, Azure Machine Learning, DigitalOcean, KNIME Analytics PlatformLlama 4 MaverickGoogle Vertex AIno first choiceChangedno first choiceno first choiceno first choiceagainst: Amazon SageMaker, Azure Machine Learning, Google Cloud AutoML, IBM watsonx.ai
Eight alternatives
Amazon SageMaker, Azure Machine Learning, Fiddler AI, Hugging Face, KNIME Analytics Platform, MLflow, Picsellia, Superwise AIQwen 3.7 FlashDataRobotagainst: Amazon SageMakerAmazon SageMaker, Azure Machine LearningChangedGoogle Vertex AIagainst: Databricks Mosaic AIKNIME Analytics Platformagainst: DataRobot, Domino Data Labno first choiceagainst: Alteryx, Amazon SageMaker, Azure Machine Learning, Caffe, DataRobot, Google Vertex AI, KNIME Analytics Platform
Three alternatives
Alteryx, Databricks Mosaic AI, RapidMinerFour alternatives
BentoML, KServe, MLflow, Weights & BiasesTwo alternatives
Amazon SageMaker, Weights & BiasesThree alternatives
BigML, EasyDeploy AI, Google Vertex AIKimi K2Google Vertex AIGoogle Vertex AIHeldagainst: DataRobot, Databricks Mosaic AI, H2O.aiGoogle Vertex AIGoogle Colabagainst: Azure Machine Learning, Google Cloud AutoMLAmazon SageMaker, Azure Machine Learningagainst: Alteryx Designer, Amazon SageMaker, Azure Machine Learning, DataRobot, Google Vertex AI
Six alternatives
Amazon SageMaker Autopilot / SageMaker Canvas, Azure AutoML, BigML, Dataiku, KNIME Analytics Platform, RapidMinerThree alternatives
Amazon SageMaker, Azure Machine Learning, MLflowFive alternatives
Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Dataiku, MLflowFive alternatives
H2O.ai, KNIME Analytics Platform, PyTorch, TensorFlow, scikit-learnTwo alternatives
Databricks Mosaic AI, Google Vertex AIGLM 4.7 FlashXGoogle Cloud AutoMLDataRobotChangedno first choiceDataikuagainst: Amazon SageMaker, Google Vertex AIno first choiceagainst: Amazon SageMaker, Databricks Mosaic AI, Google Cloud AutoML & Vertex AI
Four alternatives
Amazon SageMaker, Azure Machine Learning, BigML, DataRobotFour alternatives
Databricks Mosaic AI, Dataiku, MLflow, Weights & BiasesFifteen alternatives
Alteryx Machine Learning, Amazon SageMaker, Azure Machine Learning, DataRobot, Databricks Mosaic AI, Dataiku, Google Colab, Google Vertex AI, H2O.ai, IBM Watson Machine Learning Accelerator, KNIME Analytics Platform, MLflow, Palo Alto Networks Cortex Cloud, Peltarion, RapidMinerFive alternatives
Google Colab, Hugging Face Spaces, KNIME Analytics Platform, Kaggle, Obviously AIMiniMax M2.5DataRobot, Google Cloud AutoMLMLflow, Weights & BiasesChangedno first choiceHugging Faceno first choiceagainst: IBM, Oracle, SAP
Two alternatives
Amazon SageMaker, Azure Machine LearningTwo alternatives
ClearML, Google Vertex AINine alternatives
Akkio, Amazon SageMaker, Azure Machine Learning, ClearML, Databricks Mosaic AI, Dataiku, Google Colab, Google Vertex AI, H2O-3Five alternatives
Amazon SageMaker, Azure Machine Learning, Google Cloud, Google Colab, KaggleGPT-6 LunaGoogle Cloud's Gemini Enterprise Agent PlatformAmazon SageMakerChangedagainst: Databricks Mosaic AIno first choiceagainst: Databricks Mosaic AIHugging Faceagainst: Google Colabno first choiceagainst: OpenAI
Three alternatives
Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AITwo alternatives
Azure Machine Learning, Google Vertex AIThree alternatives
Hugging Face, MLflow, ModalOne alternative
SageMaker StudioMuse Glimmer 30BGoogle Vertex AIGoogle Vertex AIHeldagainst: Amazon SageMakerGoogle Vertex AIGoogle Colabno first choiceagainst: Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Gemini Enterprise Agent Platform, Google Vertex AI, IBM Watson, IBM watsonx.ai
Ten alternatives
Akkio, Alteryx, Amazon SageMaker, Azure Machine Learning, BigML, Fiddler AI, Google Colab, KNIME Analytics Platform, Picsellia, Superwise AIThree alternatives
KServe, Kubeflow, MLflowSix alternatives
Amazon SageMaker, Azure Machine Learning, Databricks Data Intelligence / Mosaic AI, Dataiku, Deepnote, KNIME Analytics PlatformFour alternatives
Google Vertex AI, Hugging Face, Kaggle, RapidMinerBold 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 17:31 | no | 0 | 5 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 11:41 | yes | 3 | 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 19:20 | no | 0 | 16 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-11-01 13:21 | yes | 10 | 4 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 19:43 | yes | 5 | 11 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 10:10 | yes | 5 | 5 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 12:16 | yes | 22 | 22 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 09:26 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 17:11 | no | 0 | 28 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 19:32 | yes | 10 | 55 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 09:28 | yes | 15 | 42 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 14:27 | no | 0 | 11 s |
| Direct recommendation | GPT-6 Luna | gpt-6-luna | 2026-11-01 14:02 | yes | 5 | 16 s |
| Direct recommendation | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 18:14 | yes | 14 | 22 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 10:07 | yes | 9 | 7 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 15:13 | yes | 2 | 4 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 12:35 | no | 0 | 17 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-11-01 09:49 | yes | 10 | 4 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 17:27 | yes | 10 | 10 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 17:51 | yes | 5 | 5 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 19:03 | yes | 23 | 28 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 09:00 | yes | 5 | 3 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 19:16 | yes | 8 | 50 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 10:30 | yes | 24 | 26 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 17:14 | yes | 18 | 23 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 09:06 | yes | 5 | 30 s |
| Paraphrase | GPT-6 Luna | gpt-6-luna | 2026-11-01 19:06 | yes | 6 | 19 s |
| Paraphrase | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 18:36 | yes | 14 | 21 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 11:12 | yes | 9 | 9 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:59 | yes | 4 | 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 10:12 | no | 0 | 17 s |
| Comparative | Perplexity Sonar | sonar | 2026-11-01 10:48 | yes | 10 | 6 s |
| Comparative | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 18:15 | yes | 9 | 16 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 15:39 | yes | 5 | 6 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 13:44 | yes | 24 | 50 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 12:29 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 09:56 | no | 0 | 31 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 15:36 | yes | 15 | 41 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 16:22 | yes | 19 | 43 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 14:39 | yes | 25 | 59 s |
| Comparative | GPT-6 Luna | gpt-6-luna | 2026-11-01 12:08 | yes | 8 | 18 s |
| Comparative | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 19:12 | yes | 12 | 29 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 13:49 | no | 0 | 5 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 08:53 | no | 0 | 4 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 11:33 | no | 0 | 13 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-11-01 15:14 | yes | 10 | 3 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 15:09 | yes | 5 | 7 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 19:28 | yes | 5 | 7 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 19:44 | yes | 22 | 32 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 19:23 | yes | 5 | 3 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 18:24 | yes | 10 | 42 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 18:26 | yes | 10 | 23 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 09:12 | yes | 20 | 92 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 09:49 | no | 0 | 13 s |
| Budget constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 13:50 | yes | 3 | 18 s |
| Budget constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 12:28 | yes | 14 | 21 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 17:27 | no | 0 | 6 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 16:57 | no | 0 | 5 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 17:04 | no | 0 | 17 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-11-01 17:38 | yes | 10 | 7 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 18:54 | yes | 5 | 12 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 09:46 | no | 0 | 7 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 09:22 | yes | 23 | 31 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 10:59 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 11:18 | no | 0 | 29 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 12:27 | yes | 20 | 28 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 09:29 | yes | 15 | 25 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 19:13 | no | 0 | 12 s |
| Scale constrained | GPT-6 Luna | gpt-6-luna | 2026-11-01 15:08 | yes | 2 | 14 s |
| Scale constrained | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 17:32 | yes | 15 | 17 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-11-01 19:04 | yes | 17 | 9 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-11-01 12:41 | yes | 6 | 5 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 08:58 | no | 0 | 15 s |
| Negative framing | Perplexity Sonar | sonar | 2026-11-01 16:56 | yes | 10 | 4 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.20-non-reasoning via xai | 2026-11-01 19:43 | yes | 5 | 11 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-11-01 15:53 | yes | 5 | 5 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via deepinfra | 2026-11-01 18:09 | yes | 23 | 35 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-11-01 09:36 | yes | 5 | 3 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-11-01 09:45 | no | 0 | 28 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-11-01 11:44 | yes | 15 | 60 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-11-01 09:27 | yes | 25 | 80 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-11-01 14:42 | no | 0 | 28 s |
| Negative framing | GPT-6 Luna | gpt-6-luna | 2026-11-01 16:34 | yes | 4 | 13 s |
| Negative framing | Muse Glimmer 30B | meta/muse-glimmer-30b via togetherai | 2026-11-01 09:26 | yes | 11 | 20 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 (Mosaic AI) read as Databricks Mosaic AI
Databricks (Unity Catalog + MLflow) read as Databricks Mosaic AI
Databricks (with Managed MLflow) read as Databricks Mosaic AI
Databricks Data Intelligence Platform read as Databricks Mosaic AI
Domino read as Domino Data Lab
Google Cloud AI Platform / Vertex AI read as Google Vertex AI
KNIME read as KNIME Analytics Platform
Snowflake read as Snowflake Cortex AI
Snowflake Cortex read as Snowflake Cortex AI
Snowflake ML read as Snowflake Cortex AI
Unresolved, counted raw
AWS SageMaker Canvas
Amazon SageMaker Autopilot / SageMaker Canvas
Azure AutoML
Azure Text Analytics
Caffe
Canonical's open source MLOps platform
Databricks Data Intelligence / Mosaic AI
Databricks Lakehouse Platform
Determined AI
Gemini platform
Google AI APIs
Google Cloud Gemini Enterprise Agent Platform
Google Cloud TPU
Google Cloud's Gemini Platform
Google Gemini API
Google Vertex AutoML
Google Vision
H2O ai
Hopsworks
Intelligence Center X AI Studio
Lightning AI Studios
Local Jupyter Notebooks
Microsoft Azure Automated ML
Microsoft Power BI DAX functions
OpenAI Platform
Orange3
Peltarion
Rapidminer SLC
SAP Predictive Analytics
SAS Enterprise Miner
SageMaker Studio
Spell
TIBCO Data Science
Discontinued, still offered
No shut-down product was recommended here.