Six of fourteen models named Databricks Mosaic AI first on the direct prompt; two named Google Vertex AI. Both were named by all fourteen models and Databricks Mosaic AI carries 44 labels and Google Vertex AI 57, so the shares are not directly comparable.
Named in two categories this edition.
Named in three categories this edition.
Share is the count of first choices across the direct, paraphrase, budget and scale prompts over all fourteen models, for a mid-market B2B company; rank is within the category; every quote names the model and the prompt it came from. Both figures come from the ML platforms page.
Across every category in the October 2026 Edition, Databricks Mosaic AI and Google Vertex AI were named in the same answer 107 times, of the 136 answers naming Databricks Mosaic AI and the 173 naming Google Vertex AI. In those answers Google Vertex AI took the first choice nine times and Databricks Mosaic AI twenty-six.
| Model | Direct | Paraphrase | Comparative | Budget-constrained | Scale-constrained | Negative |
|---|---|---|---|---|---|---|
| Claude Haiku 4.5 | ||||||
| GPT-5.4 mini | ||||||
| Gemini 3.5 Flash | ||||||
| Perplexity Sonar | ||||||
| Grok 4.1 Fast | ||||||
| Mistral Small | ||||||
| DeepSeek V4 Flash | ||||||
| Llama 4 Maverick | ||||||
| Qwen 3.7 Flash | ||||||
| Kimi K2 | ||||||
| GLM 4.7 FlashX | ||||||
| MiniMax M2.5 | ||||||
| GPT-6 Luna | ||||||
| Muse Glimmer 30B |
Bold names in an answer are the products the judge labeled a first choice; a model naming several gives each of them that label. The full answer text for every row is in the record.
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“Databricks (full platform) | Can be expensive unless you already need the lakehouse architecture” Kimi K2 · paraphrase prompt · hard negative
“Nearly all major platforms (Databricks, SageMaker, Vertex AI, SAS) were flagged by users as having steep learning curves” DeepSeek V4 Flash · negative prompt · soft negative
“Steep learning curve - Confusing for newcomers... High cost - Particularly expensive for large data projects” GLM 4.7 FlashX · negative prompt · soft negative
“Databricks (Mosaic AI) and Google Vertex AI are top choices due to their balance of power, ease of use, and integration with popular cloud ecosystems.” Mistral Small · direct prompt · first choice
“my default pick would be Databricks if you have moderate complexity and want fewer moving parts” Perplexity Sonar · paraphrase prompt · first choice
“I'd suggest starting with Databricks or DataRobot as they balance power with usability” MiniMax M2.5 · direct prompt · first choice
Every negative label with a quote, up to three, then the highest-weighted positives, up to three. Six of eight in this category shown.
“it is often recommended to avoid for small teams or startups due to complexity and cost concerns” Mistral Small · negative prompt · hard negative
“Some AI models advise against using this service for enterprise tasks until stability improves.” Llama 4 Maverick · negative prompt · hard negative
“be cautious if you are not already on Google Cloud, have a limited budget, or need a small-scale/simple setup” Perplexity Sonar · negative prompt · soft negative
“the most recommended MLOps platforms for training and deploying models are Vertex AI and Amazon SageMaker” Mistral Small · paraphrase prompt · first choice
“Azure Machine Learning and Google Vertex AI are the most broadly suitable platform choices” Perplexity Sonar · direct prompt · first choice
“I'd usually recommend Amazon SageMaker or Google Vertex AI as the best default choices” GPT-5.4 mini · paraphrase prompt · first choice
Comparisons are drawn for the top eight products in each category, each against each. The output is the models' output; nothing here is a recommendation by the index.