BenchRank
#24 in AI Development PlatformsUpdated 2026-08

OpenLIT

by OpenLIT · Open source OpenTelemetry platform for LLM and AI agent engineering

59.2 — BenchRank score out of 100

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Overview

OpenLIT is an open source platform for instrumenting and monitoring LLM and AI agent applications. It collects OpenTelemetry traces from its own SDKs, an eBPF controller, a GPU collector or any OTLP source, and stores them in ClickHouse. Alongside tracing it offers LLM evaluations, a Prompt Hub for versioning, a Vault for API keys and the OpenGround model comparison playground.

Best for
Engineering teams self-hosting OpenTelemetry tracing and evaluation for LLM and agent apps.
Pricing
Self-hosting is free under Apache 2.0 with unlimited usage, users and projects; a hosted Cloud plan is marked coming soon with pricing to be published at launch.
Runs on
Self-hostedCLI

Strengths and trade-offs

Strengths

  • Apache 2.0 core, self-hosted free with unlimited usage
  • OpenTelemetry-native; export to Grafana, Datadog or any OTLP backend
  • Tracing, evals, Prompt Hub, Vault and GPU monitoring in one UI
  • 56+ integrations plus ingest from OTel SDKs, OBI or OpenLLMetry

Trade-offs

  • No hosted option yet; Cloud is listed as coming soon with no pricing
  • You run and maintain the stack: OpenLIT, ClickHouse and an OTel collector
  • Support is community-only via GitHub

Pricing

Published plans from OpenLIT’s own pricing page, in USD. Usage charges and add-ons may apply on top.

OpenLIT pricing tiers, monthly rates in USD
PlanMonthlyIncludes
OSS
  • Apache 2.0 licensed platform, self-hosted on your own infra
  • Tracing, evaluations, Prompt Hub, Vault, OpenGround, GPU monitoring
  • Unlimited usage, users, projects and history
  • OAuth sign-in and community support on GitHub
Cloud
  • Fully hosted OpenLIT with managed infrastructure and upgrades
  • Marked coming soon; waitlist only
  • Feature set and pricing to be shared at launch

How this score is made up

Each dimension is scored out of 100 and combined into the headline score using fixed weights.

MCP support
60 out of 100
API quality
20 out of 100
Documentation
90 out of 100
Agent friendliness
98 out of 100
Pricing transparency
30 out of 100
Changelog
100 out of 100
Marketing site structure
70 out of 100
Operational trust
0 out of 100

Measured, but not part of the score

Useful to know, but not a mark for or against the product — so these do not affect the ranking.

Openness
85 out of 100
Maintenance
100 out of 100

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