ML platforms
Asked as “machine learning platform”, and as “MLOps platform for training and deploying models”, on behalf of a mid-market B2B company. 48 first choices recorded across the direct, paraphrase, budget and scale prompts, twelve models each.
Standing · first-choice share
19%
Contested · Azure Machine Learning 17%
19Databricks Mosaic AI17Azure Machine Learning10Amazon SageMaker54others
19% of first choices, contested.
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.
The standing
Share is the count of first choices across the direct, paraphrase, budget and scale prompts, over all twelve models, for a mid-market B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrant
Show the five products at 0%, ordered by negative rate
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 eleven models four times of 44. Lab treatment is defined on the method page; the row is marked, not excluded.
Head to head
All twenty-eight head-to-head pages: the top eight products, each against each
Databricks Mosaic AI vs Google Vertex AIDatabricks Mosaic AI vs DataikuDatabricks Mosaic AI vs TensorFlowDatabricks Mosaic AI vs MLflowAzure Machine Learning vs Amazon SageMakerAzure Machine Learning vs KNIME Analytics PlatformAzure Machine Learning vs Google Vertex AIAzure Machine Learning vs DataikuAzure Machine Learning vs TensorFlowAzure Machine Learning vs MLflowAmazon SageMaker vs KNIME Analytics PlatformAmazon SageMaker vs Google Vertex AIAmazon SageMaker vs DataikuAmazon SageMaker vs TensorFlowAmazon SageMaker vs MLflowKNIME Analytics Platform vs Google Vertex AIKNIME Analytics Platform vs DataikuKNIME Analytics Platform vs TensorFlowKNIME Analytics Platform vs MLflowGoogle Vertex AI vs DataikuGoogle Vertex AI vs TensorFlowGoogle Vertex AI vs MLflowDataiku vs TensorFlowDataiku vs MLflowTensorFlow vs MLflow
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 →
01
02
03
04
05
06
07
08
09
10
11W12
13Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative30%
Key
01Databricks Mosaic AI19%
Databricks Mosaic AI19%02Azure Machine Learning17%
Azure Machine Learning17%03Amazon SageMaker10%
Amazon SageMaker10%04KNIME Analytics Platform10%
KNIME Analytics Platform10%05Google Vertex AI8%
Google Vertex AI8%06Dataiku6%
Dataiku6%07TensorFlow4%
TensorFlow4%08MLflow2%
MLflow2%09DataRobot0%
DataRobot0%10H2O.ai0%
H2O.ai0%11Snowflake Cortex AI0%
Snowflake Cortex AI0%12Weights & Biases0%
13Kubeflow0%
Kubeflow0%What they warned about
Two of twelve 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, Qwen 3.7 Flash, Kimi K2, GLM 4.7 FlashX and MiniMax M2.5 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 SageMaker28%
14 of 50 labels negative · 10 of 12 models · 1 hard negative
“Avoid these platforms if you are a small team, a startup, or just starting out.” GLM 4.7 FlashX, negative prompt
Google Vertex AI20%
9 of 45 labels negative · 8 of 12 models · 1 hard negative
“Avoid these platforms if you are a small team, a startup, or just starting out.” GLM 4.7 FlashX, negative prompt
Azure Machine Learning18%
9 of 49 labels negative · 7 of 12 models · 1 hard negative
“Avoid these platforms if you are a small team, a startup, or just starting out.” GLM 4.7 FlashX, negative prompt
DeepSeek100%
4 of 4 labels negative · 4 of 12 models · 4 hard negative
“leading experts to advise against logging in or using the service for enterprise tasks until stability improves” Qwen 3.7 Flash, negative prompt
What they cite
Twelve of the twelve models returned a source list in this edition: four return the pages they cited and eight the search results they consulted.
Sites the answers cite
64 of 72 answers in this category came back with a source list, from 12 of 12 models: citations where the model returns them, or the search results it consulted. 869 links across 326 sites, every framing counted. Ranked by the number of answers carrying the site or page.
vendor site · G221 answers · 36 citations · 10 models
20 answers · 28 citations · 10 models
vendor site · G219 answers · 25 citations · 11 models
13 answers · 16 citations · 10 models
12 answers · 15 citations · 8 models
12 answers · 13 citations · 7 models
11 answers · 12 citations · 7 models
11 answers · 12 citations · 8 models
vendor site · Dataiku11 answers · 11 citations · 9 models
10 answers · 20 citations · 6 models
vendor site · DagsHub10 answers · 10 citations · 7 models
9 answers · 14 citations · 9 models
Pages the answers cite
The ten pages named in the most answers, by full address. A page here is one the models returned with a recommendation, not one the index endorses.
15 answers · 10 models
12 answers · 7 models
11 answers · 9 models
9 answers · 6 models
9 answers · 7 models
9 answers · 8 models
9 answers · 9 models
9 answers · 9 models
8 answers · 5 models
8 answers · 8 models
Search against answers
Each company's standing in the answers beside its site's footprint in Google search, one row a site: the products the models named on it with their shares, and the share they add up to; monthly searches on Google, and DataForSEO's estimate of AI search demand (modeled from search signals, directional, not a count of queries to any assistant), for the most-searched of the company's and its products' names (the name is in each row's hover text); estimated monthly organic visits to the site; and its best position in Google's top ten for “best 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 19% | 19% | 125 | 135,000 | 8,368 | 689,756 company | $34,664 | 120 |
| Azure parent site Azure Machine Learning 17% | 17% | 148 | 301,000 | 47,904 | |||
| Amazon parent site Amazon SageMaker 10% | 10% | 159 | 151,000,000 | 1,380,939 | |||
| KNIME Analytics Platform knime.com | 10% | 24 | 320 | 3 | 28,171 | 23 | |
| Google Vertex AI cloud.google.com | 8% | 135 | 5,400 | 226 | 7,405,347 | ||
| Dataiku dataiku.com | 6% | 74 | 9,900 | 266 | 12,714 | 93 | |
| TensorFlow tensorflow.org | 4% | 16 | 18,100 | 2,745 | 198,535 | 3 | |
| Kaggle kaggle.com | 4% | 3 | 74,000 | 778 | |||
| Google Colab colab.research.google.com | 4% | 18 | 301,000 | 900 | 240,528 | ||
| ClearML clear.ml | 4% | 9 | 880 | 4 | 588 | 45 |
Google's top ten for the three searches hold 22 sites; 0 of them are among the sites the models cited here. 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 mid-market B2B company?”Paraphrase“Which MLOps platform for training and deploying models would you recommend to a mid-sized B2B company?”Comparative“What are the top machine learning platforms and how do they differ?”Budget-constrained“What is the best machine learning platform for a company with a limited budget?”Scale-constrained“We are a 500 person company evaluating a machine learning platform. What should we look at?”Negative“Which machine learning platforms should I avoid or be cautious about?”
Claude Haiku 4.5no first choiceDatabricks Mosaic AIChangedno first choiceGoogle Cloud AutoML & Vertex AI, TensorFlow, scikit-learnno first choiceagainst: Deep Lake, Lunary, NVIDIA's NeMo, Weights & Biases' Weave toolkit, ZenML
Four alternatives
Azure Machine Learning, DataRobot, Google Vertex AI, TrueFoundryFour alternatives
Amazon SageMaker, Azure Machine Learning, H2O AutoML, PyTorchGPT-5.4 miniDatabricks Mosaic AIDatabricks Mosaic AIHeldagainst: Amazon SageMakerno first choiceAzure Machine Learningagainst: Databricks Mosaic AI, Snowflake Cortex AIno first choicenothing named
Two alternatives
Amazon SageMaker, Azure Machine LearningOne alternative
Google Vertex AIEight alternatives
Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Google Vertex AI, H2O.ai, IBM watsonx.ai, MLflow, Snowflake Cortex AIOne alternative
Amazon SageMakerGemini 3.5 FlashDataikuagainst: Amazon SageMakerClearMLChangedagainst: Kubeflowno first choiceClearMLagainst: Alteryx, Amazon Neptune, DataRobot, Weights & BiasesDatabricks Mosaic AIagainst: Kubeflowagainst: Amazon SageMaker, Azure Machine Learning, DataRobot, Google Vertex AI, H2O Driverless AI, IBM Watson Studio
Five alternatives
Azure Machine Learning, DataRobot, Databricks Mosaic AI, Pecan AI, Snowflake Cortex AIFive alternatives
Amazon SageMaker, Databricks Mosaic AI, Google Vertex AI, MLflow, TrueFoundryNine alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, Databricks Mosaic AI, Dataiku, Google Vertex AI, MLflow, Snowflake Cortex AI, Weights & BiasesSeven alternatives
Amazon SageMaker, Google Vertex AI, Hugging Face, KNIME Analytics Platform, MLflow, Paperspace, Saturn CloudFive alternatives
Amazon SageMaker, Braintrust, Google Vertex AI, LangSmith, Weights & BiasesPerplexity SonarAzure Machine LearningDatabricks Mosaic AIChangedno first choiceGoogle Colab, KNIME Analytics Platformno first choiceagainst: Amazon SageMaker, Azure Machine Learning, DagsHub, Google Vertex AI, H2O.ai
Three alternatives
Databricks Mosaic AI, Dataiku, Snowflake Cortex AIFour alternatives
Amazon SageMaker, BentoML, Google Vertex AI, MLflowSix alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, Databricks Mosaic AI, Google Vertex AI, H2O.aiThree alternatives
BigML, PyCaret, scikit-learnGrok 4.20Azure Machine Learningagainst: H2O.aiAmazon SageMaker, Azure Machine Learning, Google Vertex AIChangedno first choiceGoogle Colab, Kaggleagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AIno first choiceagainst: TensorFlow/PyTorchagainst: Amazon SageMaker, Azure Machine Learning, ChatGPT, ClearML, Copilot, DeepSeek, Google Gemini, Google Vertex AI, Hugging Face, MLflow, Meta AI
Three alternatives
DataRobot, Databricks Mosaic AI, DataikuTwo alternatives
Databricks Mosaic AI, MLflowThree alternatives
Hugging Face, KNIME Analytics Platform, PyTorchMistral SmallAzure Machine LearningAmazon SageMaker, Databricks Mosaic AIChangedno first choiceKNIME Analytics Platform, Kaggleno first choiceagainst: Amazon SageMaker, Azure Machine Learning, DagsHub, DeepSeek, Google Vertex AI
Four alternatives
Amazon SageMaker, Databricks Mosaic AI, Dataiku, Google Vertex AITwo alternatives
Google Vertex AI, MLflowThree alternatives
Azure Machine Learning, BigML, Google Vertex AIDeepSeek V4 FlashAmazon SageMaker, Azure Machine Learning, Google Vertex AIDatabricks Mosaic AIChangedagainst: KubeflowAmazon SageMakerGoogle Vertex AIno first choiceagainst: Amazon SageMaker, Azure Machine Learning, C3 AI, DataRobot, Databricks Mosaic AI, Google Vertex AI, MLflow, MindsDB, Palantir Foundry, TensorFlow Probability, Weights & Biases
Four alternatives
DataRobot, Dataiku, H2O.ai, KNIME Analytics PlatformFour alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AI, MLflowEight alternatives
Azure Machine Learning, DataRobot, Databricks Mosaic AI, Google Vertex AI, PyTorch, RapidMiner, TensorFlow, scikit-learnSix alternatives
Amazon SageMaker, Azure ML Designer, Google Colab, Google Vertex AutoML, MLflow, PyTorchLlama 4 Maverickno first choiceno first choiceHeldno first choiceKNIME Analytics Platform, TensorFlowno first choiceagainst: Amazon SageMaker, DagsHub, Google Vertex AI, Kubeflow
Two alternatives
BigML, Google Vertex AIQwen 3.7 FlashAzure Machine LearningDatabricks Mosaic AIChangedagainst: Amazon SageMakerno first choiceHugging Faceagainst: Amazon SageMaker, Azure Machine Learningno first choiceagainst: Amazon SageMaker, Azure Machine Learning, DagsHub, DeepSeek, Google Colab, Google Vertex AI, Kubeflow
Two alternatives
Amazon SageMaker, Google Vertex AITwo alternatives
Azure Machine Learning, Domino Data LabFour alternatives
Google Colab, Kaggle, MLflow, Weights & BiasesKimi K2DataikuAmazon SageMakerChangedno first choiceMLflowno first choiceagainst: Databricks Mosaic AI, OpenAI, Weights & Biases' Weave toolkit, ZenML
Two alternatives
Azure Machine Learning, Databricks Mosaic AITwo alternatives
Azure Machine Learning, Google Vertex AISeven alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, Google Vertex AI, PyTorch, TensorFlow, scikit-learnFive alternatives
KNIME Analytics Platform, PyTorch, TensorFlow, Weights & Biases, scikit-learnGLM 4.7 FlashXDataikuGoogle Vertex AIChangedno first choiceJupyter Notebook, KNIME Analytics Platform, Orangeagainst: Zoho Analyticsno first choiceagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Hugging Face, MLflow, Weights & Biases
Three alternatives
Azure Machine Learning, DataRobot, Databricks Mosaic AISix alternatives
Amazon SageMaker, Azure Machine Learning, ClearML, Kubeflow, MLflow, Weights & BiasesEight alternatives
Amazon SageMaker, Azure Machine Learning, DataRobot, Databricks Mosaic AI, Google Vertex AI, H2O.ai, Kubeflow, MLflowEight alternatives
Azure Machine Learning, Databricks Mosaic AI, Google Colab, Google Vertex AI, Kaggle, PyTorch, TensorFlow, scikit-learnMiniMax M2.5Azure Machine Learning, Databricks Mosaic AIagainst: Amazon SageMakerAmazon SageMakerChangedno first choiceKNIME Analytics Platformno first choiceagainst: DeepSeek, Google Gemini, Meta AI, Microsoft Copilot
Two alternatives
Google Vertex AI, Snowflake Cortex AIThree alternatives
Databricks Mosaic AI, Kubeflow, MLflowSix alternatives
Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Dataiku, Google Vertex AI, H2O.aiThree alternatives
Azure Machine Learning, TensorFlow, WekaBold 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.
Seventy-two 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 | 2026-09-17 11:40 | no | 0 | 3 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 09:53 | yes | 4 | 6 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 10:13 | yes | 15 | 26 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-09-17 12:59 | yes | 20 | 5 s |
| Direct recommendation | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-17 11:03 | yes | 35 | 21 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 13:23 | yes | 11 | 8 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 10:48 | yes | 19 | 21 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 12:25 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 10:56 | yes | 10 | 56 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 11:04 | yes | 9 | 34 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 10:03 | yes | 21 | 262 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 09:59 | yes | 8 | 26 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 11:44 | yes | 18 | 12 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 12:10 | yes | 5 | 7 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 13:26 | yes | 16 | 24 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-09-17 13:12 | yes | 20 | 8 s |
| Paraphrase | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-17 11:57 | yes | 31 | 20 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 11:19 | yes | 5 | 5 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 09:31 | yes | 15 | 14 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 13:00 | yes | 5 | 4 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 12:40 | no | 0 | 38 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 13:17 | yes | 15 | 49 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 12:06 | yes | 21 | 38 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 09:47 | yes | 10 | 29 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 10:01 | yes | 9 | 9 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 10:58 | yes | 5 | 10 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 11:49 | yes | 13 | 32 s |
| Comparative | Perplexity Sonar | sonar | 2026-09-17 10:37 | yes | 20 | 7 s |
| Comparative | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-17 13:42 | yes | 28 | 14 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 10:16 | yes | 5 | 6 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 11:13 | yes | 20 | 19 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 13:47 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 09:56 | yes | 5 | 31 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 11:54 | yes | 10 | 29 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 12:11 | yes | 35 | 74 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 11:00 | yes | 5 | 16 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 12:04 | no | 0 | 6 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 11:28 | yes | 5 | 7 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 10:51 | yes | 9 | 21 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-09-17 10:00 | yes | 20 | 5 s |
| Budget constrained | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-17 14:00 | yes | 14 | 9 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 11:03 | yes | 5 | 4 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 12:55 | yes | 19 | 20 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 12:00 | yes | 5 | 3 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 13:46 | no | 0 | 34 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 11:21 | yes | 10 | 26 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 12:13 | yes | 10 | 71 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 11:30 | yes | 5 | 25 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 10:07 | no | 0 | 6 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 12:07 | no | 0 | 8 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 13:10 | yes | 12 | 30 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-09-17 12:24 | yes | 20 | 7 s |
| Scale constrained | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-17 09:52 | yes | 12 | 8 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 11:16 | yes | 5 | 8 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 12:07 | yes | 18 | 19 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 13:54 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 13:41 | no | 0 | 36 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 11:19 | yes | 13 | 23 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 09:29 | yes | 12 | 74 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 14:01 | yes | 5 | 20 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 12:58 | yes | 18 | 8 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 10:08 | no | 0 | 5 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 13:36 | yes | 19 | 25 s |
| Negative framing | Perplexity Sonar | sonar | 2026-09-17 11:38 | yes | 20 | 7 s |
| Negative framing | Grok 4.20 | spacexai/grok-4.1-fast-non-reasoning via vertex (asked for grok-4.20-non-reasoning; the API answered as this version) | 2026-09-17 10:44 | yes | 42 | 16 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 09:23 | yes | 5 | 6 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 11:43 | yes | 20 | 20 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 14:07 | yes | 5 | 4 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 10:25 | yes | 5 | 40 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 13:22 | yes | 15 | 24 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 11:26 | yes | 33 | 77 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 12:46 | yes | 5 | 23 s |
Normalization in this category
Every judgment call made between the raw labels and the numbers above, listed so it is visible and reversible.
ShowHide
Category-scoped readings
AWS SageMaker Studio (Free Tier) read as Amazon SageMaker
Apache Spark (standalone/local) read as Apache Spark MLlib
Azure Databricks read as Databricks Mosaic AI
Databricks read as Databricks Mosaic AI
Databricks (Managed MLflow) read as Databricks Mosaic AI
Databricks (Mosaic AI / MLflow) read as Databricks Mosaic AI
Databricks (Mosaic AI/MLflow) read as Databricks Mosaic AI
Databricks (w/ MLflow) read as Databricks Mosaic AI
Databricks (with MLflow) read as Databricks Mosaic AI
Databricks Community Edition read as Databricks Mosaic AI
Databricks Data Intelligence Platform read as Databricks Mosaic AI
Databricks Machine Learning 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
KNIME Cloud read as KNIME Analytics Platform
Palantir read as Palantir Foundry
Snowflake read as Snowflake Cortex AI
Snowflake (Cortex & Snowpark) read as Snowflake Cortex AI
Snowflake (Snowpark / Cortex) read as Snowflake Cortex AI
Snowflake Cortex read as Snowflake Cortex AI
Snowflake ML read as Snowflake Cortex AI
Unresolved, counted raw
Amplemarket
Azure ML Designer
Google Cloud AI/ML
Google Vertex AutoML
Le Chat
Lunary
NVIDIA's NeMo
RStudio (Open Source)
TensorFlow Probability
Discontinued, still offered
No shut-down product was recommended here.