MLflow vs Respan (2026)
Updated March 27, 2026
vs
Overview
Rating
10.0 / 10
Rating
10.0 / 10
Best For
ML engineers and AI teams, especially those in the Databricks ecosystem
Best For
Engineering and product teams running AI agents and LLM apps in production
Product Summary
MLflow is an open-source AI engineering platform for agents, LLMs, and ML models, with tracing, evals, prompt management, and an AI gateway.
Product Summary
Respan is LLM observability built into an AI router: nested traces for every agent run, evals on live production traffic, and a click from any score to its trace.
Starting Price
Free
Starting Price
$0
Free Trial
No
Free Trial
Yes
Free Version
Yes
Free Version
Yes
Website
Website
Key features
Core capabilities each platform advertises.
- OpenTelemetry-based tracing for LLMs and agents
- 50+ built-in eval metrics and LLM judges
- Prompt versioning and automatic prompt optimization
- AI Gateway with routing, rate limiting, and fallbacks
- Agent server for deploying agents on FastAPI
- Nested traces for every LLM call, tool run, and agent turn
- Threads for multi-turn sessions
- Online evals on live production traffic
- LLM-judge, code, and human evaluators
- Datasets from production logs and experiments at scale
- Monitors with Slack, email, and webhook alerts
- Prompt versioning and deployment without code changes
Strengths and tradeoffs
What each tool does well, and the limitations to keep in mind.
Pros
- Apache 2.0 license with Linux Foundation governance
- Tracing, evals, prompts, and a gateway in one open-source project
- Covers classic ML and GenAI in the same platform
- Managed options on Databricks, SageMaker AI, and Azure ML
- Auth and role-based access built into the open-source server
Cons
- Self-hosting means running the tracking server, database, and artifact store yourself
- Auth and role-based access are opt-in and need configuring on self-hosted servers
- Managed versions bill through a cloud platform's compute rather than a standalone plan
- The broader ML scope can mean more to learn for teams that only need LLM tooling
Pros
- Every score links to the trace that produced it
- Evals run on live production traffic, not only on test sets
- Built into the router, so there's no separate gateway to integrate
- Monitors alert the moment a metric breaches
- Unlimited seats on the free plan
Cons
- The free plan retains data for 7 days
- The free plan includes 1k scores and 2 evaluators
- Ingestion throughput is metered per tier, starting at 412 logs per minute on Free
MLflow or Respan — which should you choose?
Choose MLflow if you wantChoose if you want
- Tracing and evaluating LLM apps and agents
- Versioning and optimizing prompts
- Routing LLM traffic through a self-hosted gateway
- Tracking classic ML experiments alongside GenAI work
- Running AI tooling inside Databricks
Choose Respan if you wantChoose if you want
- Debugging agent failures down to the step that broke
- Catching quality regressions before users report them
- Turning production failures into test datasets
- Testing a prompt or model change against real cases before shipping
- Attributing LLM cost to each end customer
Compare MLflow and Respan on your own traffic
10KFree traces/mo
1,000+Models
5 minSetup
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 1,000+ models through one gateway.
Try Respan free