MLflow vs PromptLayer
On the evidence we track, MLflow leads this comparison with a composite score of 70/100. Scores are only directly comparable because these tools share a category; the full breakdown and every source is below.
Capabilities
Feature-by-feature on the axes that matter for llm gateways. “-” means undocumented, not absent.
What each one is
The product in its own terms, so the numbers below have context.
MLflow
LeaderA comprehensive platform that helps teams debug, evaluate, monitor, and optimize production AI applications. Provides experiment tracking, prompt management, model deployment, systematic evaluation tools, and a unified API gateway for managing access to multiple LLM providers with cost controls.
PromptLayer
A platform that maintains logs of prompts and API requests, enabling debugging and replay of previous completions. Provides version tracking, testing, and monitoring with integrated tracing and evaluation features.
Pricing
List pricing as published by each vendor, with the date we read it. Always verify at the source before you buy.
PromptLayer
Free tier available. Pro starts at $49/month, Team at $500/month, both with usage-based billing ($0.002–$0.003 per transaction). Enterprise custom pricing.
- FreeFree
- 5 Users
- 2.5k/month Requests
- 1 Workspace
- 250/month Eval Cell Executions
- 10MB max per Dataset
- +1 more
- Pro$49/month plus $0.003/transaction
- Unlimited Playgrounds
- Unlimited Workspaces
- 150MB max per Dataset
- Webhooks Included
- Dedicated Support
- Team$500/month plus $0.002/transaction
- 25 Users
- 100k+/month Requests
- 7.5k+/month Eval Cell Executions
- 1GB max per Dataset
- Webhooks Included
- +2 more
- EnterpriseContact sales
- Custom limits on everything
- Role Based Access Controls
- Deployment Approvals
- HIPAA with BAA
- Flexible Hosting Options
- +2 more
Platform & deployment
Where each product runs and how it can be hosted. A dash means undocumented, not unsupported.
Integrations
What each product connects to. Counts come from the vendor's own integration directory where one exists.
- Pydantic AI
- OpenAI
- Anthropic
- OpenTelemetry
MLflow
Leader- Databricks
- AWS S3
- Google Cloud Storage
- Azure Storage
- AzureML
- Kubernetes
- LangChain
- Anthropic Claude
- Google Gemini
- SAP AI Core
- JFrog
- Aliyun
- PostgreSQL
- MySQL
- MSSQL
- Claude Code
- OpenAI Codex
- Gemini
- Ollama
- OpenClaw
- Qwen Code
- LiteLLM
- Amazon S3
- OpenTelemetry/OTLP
- +4 more
PromptLayer
- Google GenAI
- AWS Bedrock
- Azure OpenAI
- Vertex AI
- Gemini API
MLflow or PromptLayer: which one depends on you
A composite score cannot know your constraints. Describe them and both get re-weighted against what you actually need, with the evidence behind every position.
Free to run, no account needed to start. How the evaluation works
Comparison generated from independently-sourced facts. Every value links to its source and retrieval date. See the method.