OpenLIT Pricing 2026
Complete pricing guide for OpenLIT — plans, costs, and free options.
💰 OpenLIT Pricing Overview
OpenLIT uses a free pricing model. Completely free to use with no paid plans. Current pricing: The OSS edition is free under Apache 2.0 with unlimited self-hosted usage: full-stack AI infrastructure monitoring for GPUs, LLMs, MCP servers, vector databases and coding agents, core platform features and APIs for tracing, evaluation and prompts, deployment docs and a Helm chart, OAuth sign-in, and community support on GitHub. Deploy from GitHub with Helm or Docker. OpenLIT Cloud, a fully hosted option, is announced as coming soon with no price published yet.. OpenLIT is a popular ai agent infrastructure tool known for an apache 2.0 open-source platform for tracing llms and ai agents through opentelemetry, plus evaluations, prompt management, model comparison and a key vault — self-hosted free via helm or docker.. You can get started with OpenLIT for free and upgrade to a paid plan as your needs grow.
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OpenLIT Plans & Pricing
MCP servers, vector databases and coding agents, core platform features and APIs for tracing, evaluation and prompts, deployment docs and a Helm chart
* Pricing information is based on publicly available data and may not reflect current promotions, annual discounts, or regional pricing. Visit the official OpenLIT website for the latest pricing.
Is OpenLIT Free?
OpenLIT is completely free to use. There are no hidden costs, no premium tiers, and no paywalls. Everything the tool offers is available at no charge, making it accessible to individuals, students, and organizations of all sizes.
Is OpenLIT Worth It?
OpenLIT is a free ai agent infrastructure tool that offers 5 key features including OpenTelemetry-native tracing — spans go to your existing collector and backend, Instruments GPUs, LLMs, MCP servers, vector DBs and coding agents, Built-in LLM evaluations and model comparison. OpenLIT is an Apache 2.0 open-source observability and engineering platform for LLM and agent workloads, built on OpenTelemetry rather than on a proprietary tracing format. That choice is the substance of the product: because instrumentation emits standard OTel spans, traces can go to your existing collector and backend instead of being locked into a vendor's storage, and the same pipeline that carries your service traces carries your agent traces. Coverage runs wider than the usual LLM-call span — it instruments GPUs, LLMs, MCP servers, vector databases and coding agents, which means an agent's slow step can be attributed to the retrieval layer or the GPU rather than assumed to be the model. Around tracing it adds the adjacent pieces teams otherwise assemble separately: running LLM evaluations, managing prompts, comparing models against one another, and storing API keys in a built-in vault rather than in environment variables scattered across services. The lifecycle framing on the site runs instrument, develop, manage, observe, improve, covering both development and production stages. Deployment is self-hosted via Helm chart or Docker with OAuth sign-in, documented for both. A fully hosted OpenLIT Cloud is announced for teams that would rather not operate it, but is not yet available.
✅ OpenLIT is a good choice if you need:
- •OpenTelemetry-native tracing — spans go to your existing collector and backend
- •Instruments GPUs, LLMs, MCP servers, vector DBs and coding agents
- •Built-in LLM evaluations and model comparison
- •Prompt management and an API key vault
- •Apache 2.0, self-hosted via Helm chart or Docker with OAuth sign-in
💡 Value Assessment
With a free tier available, OpenLIT is an easy recommendation for anyone looking to try ai agent infrastructure tools without financial commitment. The paid plans offer good value for power users who need the additional features and higher usage limits.
OpenLIT Key Features
OpenLIT comes packed with features that make it a strong contender in the ai agent infrastructure space. Here's what you get:
Available in the free plan with limits — OpenTelemetry-native tracing — spans go to your existing collector and backend helps you work more efficiently with OpenLIT.
Available in the free plan with limits — Instruments GPUs, LLMs, MCP servers, vector DBs and coding agents helps you work more efficiently with OpenLIT.
Available in the free plan with limits — Built-in LLM evaluations and model comparison helps you work more efficiently with OpenLIT.
Integrate OpenLIT into your own applications and workflows via the API.
Available in the free plan with limits — Apache 2.0, self-hosted via Helm chart or Docker with OAuth sign-in helps you work more efficiently with OpenLIT.
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Visit the official website for the latest pricing and to get started.
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Get a Sponsored Badge →Frequently Asked Questions
Is OpenLIT free to use?
Yes, OpenLIT offers a free tier that you can use without paying. Paid plans starting at See website unlock additional features and higher usage limits.
How much does OpenLIT cost in 2026?
As of 2026, OpenLIT pricing is: The OSS edition is free under Apache 2.0 with unlimited self-hosted usage: full-stack AI infrastructure monitoring for GPUs, LLMs, MCP servers, vector databases and coding agents, core platform features and APIs for tracing, evaluation and prompts, deployment docs and a Helm chart, OAuth sign-in, and community support on GitHub. Deploy from GitHub with Helm or Docker. OpenLIT Cloud, a fully hosted option, is announced as coming soon with no price published yet.. Pricing may vary based on billing cycle (monthly vs annual) and region. Visit the official OpenLIT website for the most current pricing.
What is the cheapest OpenLIT plan?
The cheapest option is the free tier. If you need premium features, the most affordable paid plan is MCP servers, vector databases and coding agents, core platform features and APIs for tracing, evaluation and prompts, deployment docs and a Helm chart at See website.
Is OpenLIT worth the price?
OpenLIT is well-regarded in the agent-infrastructure space, offering features like OpenTelemetry-native tracing — spans go to your existing collector and backend, Instruments GPUs, LLMs, MCP servers, vector DBs and coding agents, Built-in LLM evaluations and model comparison. Whether it's worth the investment depends on your specific needs, usage volume, and budget. The free tier lets you try it before committing to a paid plan.
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