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Head-to-head

EvalGuard vs MLflow. 

Open-source ML lifecycle platform with LLM evalMLflow is Databricks' open-source ML lifecycle platform with recently added LLM evaluation capabilities.

6
EvalGuard wins
2
Ties
1
MLflow wins

across the 10-row feature matrix · 1 row unverified, counted for neither side · see “where MLflow leads” below

Competitor data (GitHub stars, downloads, feature counts, funding / acquisition status) verified as of 2026-08-10. EvalGuard's own counts are sourced live from the drift-checked registry.

Coverage at a glance

EvalGuard vs MLflow, by the numbers

Where both platforms publish a number, here's the gap. Our values come straight from the drift-checked registry; MLflow's are quoted as published.

Attack Plugins
EvalGuard300
MLflow0
Eval Scorers
EvalGuard200
MLflow24
LLM Providers
EvalGuard90
MLflow15
FeatureEvalGuardMLflow
Attack Plugins300+0
Eval Scorers200+24 built-in + judges
Model RegistryNoYes
Experiment TrackingYesYes
LLM FirewallYes (inline, blocking)No inline blocking (Guardrails AI validators as offline scorers)
Compliance framework mappings50 mapped in-product (EU AI Act, ISO 42001, NIST AI RMF …)Not published
Open SourceApache 2.0 (SDKs + CLI)Apache 2.0
SaaS DashboardYesDatabricks only
Red Team TestingFull suiteNo
LLM Providers90+~15

Why choose EvalGuard over MLflow

  • 300+ attack plugins — MLflow has zero security testing
  • 200+ scorers vs 24 — 10.2x more evaluation metrics
  • Standalone SaaS — MLflow SaaS requires Databricks
  • Inline runtime firewall — MLflow's Guardrails AI integration scores traces, it does not block requests
  • 90+ LLM providers vs ~15

Where MLflow leads

  • MLflow has mature model registry and deployment
  • MLflow ships 24 built-in GenAI scorers plus a judge framework and adapters for deepeval, Ragas, TruLens and Phoenix — this page previously said ~12
  • MLflow is deeply integrated with Databricks ecosystem
  • MLflow has massive open-source community

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