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. 53 first choices recorded across the direct, paraphrase, budget and scale prompts, twelve models each.
Standing · first-choice share
17%
Contested · Google Colab 13%
17Google Vertex AI13Google Colab09Azure Machine Learning60others
17% 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 small B2B company. Ordered by share.
ProductFirst-choice shareNegative rateLabelsQuadrant
Show the four 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 nine times of 44. 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 eleven models seven times of 44. Lab treatment is defined on the method page; the row is marked, not excluded.
Head to head
Databricks Mosaic AI vs Azure Machine LearningDatabricks Mosaic AI vs Amazon SageMakerDatabricks Mosaic AI vs KNIME Analytics Platform
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 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
11
12
13
14Accepted challengerEndorsed leader
0%First-choice share → · lines at 30% share and 25% negative30%
Key
01Google Vertex AI17%
Google Vertex AI17%02Google Colab13%
Google Colab13%03Azure Machine Learning9%
Azure Machine Learning9%04MLflow9%
MLflow9%05KNIME Analytics Platform8%
KNIME Analytics Platform8%06Databricks Mosaic AI4%
Databricks Mosaic AI4%07H2O.ai2%
H2O.ai2%08BigML2%
BigML2%09Dataiku2%
Dataiku2%10Amazon SageMaker2%
Amazon SageMaker2%11Hugging Face0%
Hugging Face0%12RapidMiner0%
RapidMiner0%13DataRobot0%
DataRobot0%14Kubeflow0%
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 SageMaker44%
21 of 48 labels negative · 9 of 12 models · 4 hard negative
“Avoid or be very cautious with enterprise‑focused, full‑featured cloud ML services (SageMaker, Azure ML, Google Cloud AI Platform, IBM Watson)” MiniMax M2.5, negative prompt
Azure Machine Learning29%
12 of 42 labels negative · 9 of 12 models · 4 hard negative
“Avoid or be very cautious with enterprise‑focused, full‑featured cloud ML services (SageMaker, Azure ML, Google Cloud AI Platform, IBM Watson)” MiniMax M2.5, negative prompt
Databricks Mosaic AI50%
11 of 22 labels negative · 8 of 12 models · 2 hard negative
“Premium pricing and steep learning curve; overkill for simple analytics or small data sets.” GLM 4.7 FlashX, negative prompt
Google Vertex AI20%
10 of 50 labels negative · 8 of 12 models · 1 hard negative
“Avoid or be very cautious with enterprise‑focused, full‑featured cloud ML services (SageMaker, Azure ML, Google Cloud AI Platform, IBM Watson)” MiniMax M2.5, 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
63 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. 880 links across 306 sites, every framing counted. Ranked by the number of answers carrying the site or page.
vendor site · G242 answers · 98 citations · 11 models
19 answers · 19 citations · 10 models
17 answers · 18 citations · 9 models
16 answers · 20 citations · 8 models
15 answers · 15 citations · 11 models
vendor site · FitGap15 answers · 15 citations · 8 models
14 answers · 14 citations · 8 models
13 answers · 14 citations · 7 models
13 answers · 13 citations · 9 models
vendor site · TrueFoundry12 answers · 17 citations · 8 models
12 answers · 12 citations · 8 models
11 answers · 12 citations · 8 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 · 9 models
19 answers · 10 models
17 answers · 10 models
16 answers · 9 models
15 answers · 10 models
15 answers · 11 models
15 answers · 8 models
14 answers · 8 models
13 answers · 9 models
12 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 |
|---|---|---|---|---|---|---|---|
| Google Vertex AI cloud.google.com | 17% | 135 | 5,400 | 226 | 7,405,347 | ||
| Google Colab colab.research.google.com | 13% | 18 | 301,000 | 900 | 240,528 | ||
| Azure parent site Azure Machine Learning 9% | 9% | 148 | 301,000 | 47,904 | |||
| MLflow mlflow.org | 9% | 58 | 9,900 | 438 | 6,498 | 1 | |
| KNIME Analytics Platform knime.com | 8% | 24 | 320 | 3 | 28,171 | 23 | |
| Kaggle kaggle.com | 4% | 3 | 74,000 | 778 | |||
| ClearML clear.ml | 4% | 9 | 880 | 4 | 588 | 45 | |
| Modal modal.com | 4% | 2 | |||||
| Akkio akkio.com | 4% | 6 | 1,000 | 10 | 2,874 | ||
| Databricks databricks.com Databricks Mosaic AI 4% | 4% | 125 | 135,000 | 8,368 | 689,756 company | $34,664 | 120 |
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 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 choiceClearMLChangedGoogle Vertex AIagainst: Databricks Mosaic AIGoogle Colab, Python, scikit-learnagainst: Google Cloud AutoMLno first choiceagainst: Azure Machine Learning, Google Vertex AI, SAS
One alternative
DVCFive alternatives
Amazon SageMaker, Anyscale, Azure Machine Learning, Dataiku, Hugging Face Inference EndpointsFour alternatives
Amazon Web Services, Hugging Face, Microsoft Azure Free Trial, TensorFlow/PyTorchGPT-5.4 miniDatabricks Mosaic AIDatabricks Mosaic AIHeldDatabricks Mosaic AIGoogle Vertex AIno first choicenothing named
Three alternatives
Amazon SageMaker, Google Vertex AI, Microsoft FabricOne alternative
Amazon SageMakerThree alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AITwo alternatives
Amazon SageMaker, Azure Machine LearningGemini 3.5 FlashAkkio, Obviously AITrueFoundryChangedClearML, Lightning AI, Modal, ReplicateKNIME Analytics Platformagainst: AWS, Amazon SageMaker, Azure, Databricks Mosaic AIBaseten, Modalagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AI, Kubeflowagainst: Amazon SageMaker, Apache Spark MLlib, Azure Machine Learning, Google Vertex AI, Kubeflow, MLflow
Four alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AI, KNIME Analytics PlatformTwo alternatives
Modal, QwakTwo alternatives
Baseten, Weights & BiasesEleven alternatives
Anthropic, DVC, Google Colab, Google Gemini Flash, Google Vertex AI, Hugging Face, MLflow, OpenAI, Paperspace, RunPod, n8nEight alternatives
Amazon Bedrock, Anyscale, DataRobot, LangSmith, OpenAI, Replicate, Vertex AI AutoML, Weights & BiasesPerplexity SonarGoogle Vertex AIMLflowChangedagainst: KubeflowAmazon SageMaker, Google Vertex AIMLflowno first choiceagainst: Azure Machine Learning, Google AI / Vertex AI, IBM Watson, Oracle AI, SAP AI
Three alternatives
BigML, Deepnote, KNIME Analytics PlatformFour alternatives
Amazon SageMaker, Azure Machine Learning, BentoML, Google Vertex AIEight alternatives
Azure Machine Learning, DataRobot, Databricks Mosaic AI, Dataiku, Deepnote, Feast, H2O.ai, MLflowThree alternatives
Deepnote, Google Cloud AI / Vertex AI, KNIME Analytics PlatformGrok 4.20Google Vertex AIagainst: Amazon SageMaker, DataRobot, Databricks Mosaic AIMLflowChangedagainst: Amazon SageMaker, Google Vertex AI, Weights & BiasesGoogle Colabagainst: Amazon SageMakerGoogle Colab, Kaggleagainst: Amazon SageMakerno first choiceagainst: Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, Google Vertex AI
Three alternatives
Azure Machine Learning, H2O.ai, RapidMinerTwo alternatives
BentoML, ClearMLThree alternatives
Hugging Face, MLflow, Weights & BiasesFour alternatives
Hugging Face Spaces, KNIME Analytics Platform, PyCaret, TensorFlowMistral SmallAzure Machine Learning, Google Vertex AIAmazon SageMakerChangedAzure Machine Learning, Google Vertex AIAzure Machine Learning, Google Colabno first choiceagainst: Amazon SageMaker, Azure Machine Learning, DagsHub, Kubeflow
One alternative
IBM WatsonThree alternatives
DataRobot, Google Vertex AI, MLflowThree alternatives
Amazon SageMaker, BigML, DataRobotTwo alternatives
Google Vertex AI, H2O.aiDeepSeek V4 FlashAkkio, BigMLagainst: DataRobotMLflowChangedno first choiceagainst: DataRobot, Databricks Mosaic AIGoogle ColabClearML, MLflowagainst: DataRobot, Domino Data Labagainst: Amazon SageMaker, Azure Machine Learning, Databricks Mosaic AI, DeepSeek, Google Vertex AI, IBM Watson, Kubeflow, Oracle AI, SAP AI
Four alternatives
Amazon SageMaker, Azure Machine Learning, Google Vertex AI, H2O.aiFour alternatives
Amazon SageMaker, Azure Machine Learning, Dataiku, Google Vertex AISix alternatives
Amazon SageMaker, Azure Machine Learning, Dataiku, Google Vertex AI, H2O.ai, KNIME Analytics PlatformThree alternatives
Azure Machine Learning, Google Cloud AutoML & Vertex AI, KaggleFive alternatives
Amazon SageMaker, Azure Machine Learning, BentoML, Google Vertex AI, Weights & BiasesLlama 4 Maverickno first choiceno first choiceHeldno first choiceAzure Machine Learning, Google Colabno first choiceagainst: Amazon SageMaker, DagsHub, Google Vertex AI, Kubeflow, MLflow, Modal, Replicate, Together AI
One alternative
Google CloudQwen 3.7 FlashGraphite Note, Pecan AIagainst: Amazon SageMakerModalChangedagainst: Amazon SageMaker, Databricks Mosaic AI, Kubeflow, KubernetesGoogle Vertex AIagainst: Amazon SageMakerKNIME Analytics Platformagainst: Amazon SageMaker, Azure Machine Learningno first choiceagainst: IBM Watson, Kubeflow, Kubernetes, Oracle AI, SAP AI
Three alternatives
Azure Machine Learning, BigML, Google Vertex AIOne alternative
Banana.devFour alternatives
Azure Machine Learning, DataRobot, Modal, ReplicateFour alternatives
AutoGluon, Google Colab, PyCaret, RapidMinerKimi K2Google Vertex AI, H2O.aiagainst: Amazon SageMaker, Azure Machine LearningGoogle Vertex AIChangedagainst: DataRobot, Domino Data Lab, H2O Driverless AIAmazon SageMaker, Azure Machine Learning, Google Vertex AIagainst: Databricks Mosaic AI, DataikuKNIME Analytics Platform, TensorFlowagainst: Alteryx, Amazon SageMaker, Azure Machine Learningno first choiceagainst: DataRobot, Domino Data Labagainst: Amazon SageMaker, Azure Machine Learning, Google Vertex AI
Two alternatives
Amazon SageMaker, MLflowThree alternatives
DataRobot, H2O.ai, Weights & BiasesThree alternatives
Google Cloud, H2O-3, KaggleGLM 4.7 FlashXAzure Machine Learningagainst: DataRobotGoogle Vertex AIChangedagainst: Amazon SageMakerAmazon SageMaker, Azure Machine Learningagainst: Databricks Mosaic AI, DataikuAmazon SageMaker Canvas, Google Colab, KNIME Analytics Platformagainst: Obviously AIno first choiceagainst: Amazon SageMaker, DataRobot, Databricks Mosaic AI, Gemini Enterprise Agent Platform, Google Vertex AI, H2O Driverless AI, IBM Watson Machine Learning, JMP, Oracle Machine Learning, SAP AI, Salesforce Einstein
Five alternatives
Amazon SageMaker, Google Vertex AI, H2O.ai, KNIME Analytics Platform, Saturn CloudFive alternatives
Azure Machine Learning, DataRobot, Kubeflow, MLflow, ZenMLTwo alternatives
Google Vertex AI, KNIME Analytics PlatformFive alternatives
BigML, Google Vertex AI, MLflow, PyCaret, TensorTurnMiniMax M2.5Azure Machine Learning, Google Vertex AIDataiku, Google Vertex AIChangedDatabricks Mosaic AI, Google Vertex AI, Hugging FaceGoogle Colab, Kaggleno first choiceagainst: Amazon SageMaker, Azure Cognitive Services, Azure Machine Learning, DataRobot, Databricks Mosaic AI, Domino Data Lab, Google Vertex AI, H2O.ai, IBM Watson Machine Learning, Kubeflow, MLflow
One alternative
Amazon SageMakerTwo alternatives
Amazon SageMaker, MLflowThree alternatives
Amazon SageMaker, Azure Machine Learning, KNIME Analytics PlatformTwo alternatives
Azure Machine Learning, KNIME Analytics PlatformBold 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 12:08 | no | 0 | 4 s |
| Direct recommendation | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 11:13 | yes | 3 | 5 s |
| Direct recommendation | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 09:57 | yes | 13 | 21 s |
| Direct recommendation | Perplexity Sonar | sonar | 2026-09-17 12:44 | yes | 20 | 6 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 09:47 | yes | 32 | 16 s |
| Direct recommendation | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 12:11 | yes | 9 | 8 s |
| Direct recommendation | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 11:24 | yes | 18 | 17 s |
| Direct recommendation | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 11:51 | yes | 5 | 3 s |
| Direct recommendation | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 11:22 | yes | 15 | 52 s |
| Direct recommendation | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 11:48 | yes | 8 | 18 s |
| Direct recommendation | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 11:49 | yes | 29 | 135 s |
| Direct recommendation | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 14:03 | yes | 5 | 30 s |
| Paraphrase | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 10:36 | yes | 9 | 7 s |
| Paraphrase | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 11:14 | yes | 2 | 4 s |
| Paraphrase | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 13:48 | yes | 11 | 28 s |
| Paraphrase | Perplexity Sonar | sonar | 2026-09-17 13:56 | yes | 20 | 6 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 12:14 | yes | 30 | 17 s |
| Paraphrase | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 12:47 | no | 0 | 4 s |
| Paraphrase | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 10:16 | yes | 16 | 18 s |
| Paraphrase | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 12:56 | yes | 5 | 3 s |
| Paraphrase | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 12:39 | no | 0 | 32 s |
| Paraphrase | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 12:18 | yes | 20 | 26 s |
| Paraphrase | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 13:00 | yes | 18 | 58 s |
| Paraphrase | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 14:03 | yes | 6 | 61 s |
| Comparative | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 11:33 | yes | 17 | 13 s |
| Comparative | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 11:02 | yes | 7 | 9 s |
| Comparative | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 10:57 | yes | 28 | 30 s |
| Comparative | Perplexity Sonar | sonar | 2026-09-17 10:11 | yes | 20 | 10 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 12:11 | yes | 37 | 16 s |
| Comparative | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 10:54 | yes | 5 | 9 s |
| Comparative | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 11:52 | yes | 18 | 18 s |
| Comparative | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 10:03 | yes | 5 | 2 s |
| Comparative | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 10:02 | yes | 5 | 43 s |
| Comparative | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 10:51 | yes | 15 | 53 s |
| Comparative | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 13:09 | yes | 23 | 40 s |
| Comparative | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 11:42 | yes | 11 | 32 s |
| Budget constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 12:04 | no | 0 | 4 s |
| Budget constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 12:47 | yes | 4 | 22 s |
| Budget constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 10:31 | yes | 6 | 23 s |
| Budget constrained | Perplexity Sonar | sonar | 2026-09-17 09:41 | yes | 20 | 6 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 12:22 | yes | 17 | 9 s |
| Budget constrained | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 11:52 | yes | 5 | 5 s |
| Budget constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 11:56 | yes | 8 | 15 s |
| Budget constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 12:45 | yes | 5 | 2 s |
| Budget constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 10:35 | yes | 9 | 48 s |
| Budget constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 10:08 | yes | 10 | 25 s |
| Budget constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 11:05 | yes | 15 | 107 s |
| Budget constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 11:11 | yes | 8 | 34 s |
| Scale constrained | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 10:26 | no | 0 | 7 s |
| Scale constrained | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 09:26 | no | 0 | 9 s |
| Scale constrained | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 10:49 | no | 0 | 16 s |
| Scale constrained | Perplexity Sonar | sonar | 2026-09-17 11:50 | yes | 20 | 9 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 11:54 | yes | 13 | 10 s |
| Scale constrained | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 10:28 | no | 0 | 9 s |
| Scale constrained | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 14:11 | yes | 18 | 23 s |
| Scale constrained | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 11:34 | yes | 5 | 3 s |
| Scale constrained | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 10:36 | no | 0 | 36 s |
| Scale constrained | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 11:32 | yes | 15 | 64 s |
| Scale constrained | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 10:52 | yes | 13 | 102 s |
| Scale constrained | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 12:00 | yes | 5 | 28 s |
| Negative framing | Claude Haiku 4.5 | claude-haiku-4-5-20251001 | 2026-09-17 11:28 | yes | 17 | 10 s |
| Negative framing | GPT-5.4 mini | gpt-5.4-mini-2026-03-17 | 2026-09-17 11:02 | yes | 2 | 6 s |
| Negative framing | Gemini 3.5 Flash | gemini-3.5-flash | 2026-09-17 09:44 | yes | 23 | 22 s |
| Negative framing | Perplexity Sonar | sonar | 2026-09-17 11:50 | yes | 20 | 8 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 09:46 | yes | 37 | 16 s |
| Negative framing | Mistral Small | mistral/mistral-small via mistral | 2026-09-17 11:36 | yes | 5 | 4 s |
| Negative framing | DeepSeek V4 Flash | deepseek/deepseek-v4-flash via fireworks | 2026-09-17 09:35 | yes | 20 | 19 s |
| Negative framing | Llama 4 Maverick | meta/llama-4-maverick via bedrock | 2026-09-17 11:38 | yes | 5 | 3 s |
| Negative framing | Qwen 3.7 Flash | alibaba/qwen3.7-flash via alibaba | 2026-09-17 12:41 | yes | 10 | 51 s |
| Negative framing | Kimi K2 | moonshotai/kimi-k2 via novita | 2026-09-17 13:09 | yes | 25 | 35 s |
| Negative framing | GLM 4.7 FlashX | zai/glm-4.7-flashx via zai | 2026-09-17 12:50 | yes | 25 | 81 s |
| Negative framing | MiniMax M2.5 | minimax/minimax-m2.5 via minimax | 2026-09-17 12:35 | yes | 10 | 88 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
Amazon SageMaker Studio read as Amazon SageMaker
Apache Spark read as Apache Spark MLlib
Azure Databricks read as Databricks Mosaic AI
Databricks read as Databricks Mosaic AI
Databricks (Mosaic AI) read as Databricks Mosaic AI
Databricks (community edition) read as Databricks Mosaic AI
Databricks (incl. Mosaic AI) 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 read as KNIME Analytics Platform
Snowflake Cortex read as Snowflake Cortex AI
Unresolved, counted raw
Altair
Amazon SageMaker Autopilot
Azure Cognitive Services
Banana.dev
Google AI / Vertex AI
Google AutoML Tables
Google Cloud AI / Vertex AI
Google Gemini Flash
Google Vertex AI AutoML
Graphite Note
JMP (by SAS)
Lightning AI
Microsoft Azure Free Trial
Oracle Machine Learning (OML)
Qwak
SageMaker Studio Lab (free)
Seldon
TensorTurn
V7
Vertex AI AutoML
cnvrg.io
Discontinued, still offered
No shut-down product was recommended here.