| Category | Function | Share | Rank | Negative rate | Labels | Quadrant |
|---|---|---|---|---|---|---|
| ML platforms | Data platform | 2% | 13 of 99 | 12% | 25 | accepted challenger |
| Model | First choice | Alternative | Mention | Negative | Labels |
|---|---|---|---|---|---|
| Claude Haiku 4.5 | 0 | 0 | 2 | 0 | 2 |
| GPT-5.4 mini | 0 | 1 | 0 | 0 | 1 |
| Gemini 3.5 Flash | 1 | 3 | 0 | 0 | 4 |
| Perplexity Sonar | 0 | 1 | 0 | 0 | 1 |
| Grok 4.1 Fast | 0 | 1 | 0 | 1 | 2 |
| Mistral Small | 0 | 1 | 0 | 0 | 1 |
| DeepSeek V4 Flash | 0 | 2 | 0 | 1 | 3 |
| Llama 4 Maverick | 0 | 1 | 1 | 0 | 2 |
| Qwen 3.7 Flash | 0 | 1 | 0 | 0 | 1 |
| Kimi K2 | 1 | 1 | 1 | 0 | 3 |
| GLM 4.7 FlashX | 0 | 2 | 1 | 1 | 4 |
| MiniMax M2.5 | 0 | 1 | 0 | 0 | 1 |
Verbatim evidence the judge attached to positive labels.
“Use highly flexible, industry-standard MLOps tooling like MLflow or Weights & Biases” Gemini 3.5 Flash · ML platforms · negative prompt · first choice
“starting with a combination of MLflow (for MLOps)” Kimi K2 · ML platforms · budget prompt · first choice
“If you prefer an open-source approach or have specific customization needs, MLflow is a strong alternative.” Mistral Small · ML platforms · paraphrase prompt · alternative
“The industry-standard open-source tool for tracking experiments, managing model registries, and packaging code.” Gemini 3.5 Flash · ML platforms · comparative prompt · alternative
Verbatim evidence attached to negative labels. A warning on a product with few labels is a warning; on a product with many, it is one voice among them.
“Avoid using older versions of MLflow for production environments.” GLM 4.7 FlashX · ML platforms · negative prompt · hard negative
“Multiple critical vulnerabilities (e.g., CVEs 2024-37052 to 37060 in MLflow for RCE via unsafe deserialization” Grok 4.1 Fast · ML platforms · negative prompt · soft negative
“flagged in 2024\u201325 threat reports for deserialization (pickle file) vulnerabilities” DeepSeek V4 Flash · ML platforms · negative prompt · soft negative
Citations exist only for the models that return a source list, four of the twelve in this edition, so these counts come from 46 of the 58 answers that named MLflow and are not a share of its labels.
149 of the 149 domain citations in answers naming MLflow came from somebody else's page.
Pages are listed as the models cited them.
Claiming is free and changes nothing in the data. A claimed page shows a verified contact who is told when each edition publishes and when MLflow's standing changes by more than the noise floor; the right to propose corrections to the vendor table, meaning names the judge wrote that should or should not read as MLflow, applied by version and listed in the change log; and a one-line description supplied by the vendor and marked as such.
It does not get any change to labels, shares or verdicts, any preview, or any say over which quotes appear. A verification link goes to your work email; an address at mlflow.org is approved on the spot, any other address is reviewed by hand.
Your name and company appear on the claimed page, or the company alone if you ask below. A title and a LinkedIn address appear there too if you give them, and are left off if you do not. Your email address is never published.