Observability & Analytics Pricing Comparison
29 providers compared by pricing model, free tiers, hosting options, and headquarters. Last updated May 2026.
25 with free tiers · 14 open source · 9 self-hostable · 4 European
| Provider | Pricing Model | Starting Price | Free Tier | Hosting | Open Source | HQ |
|---|---|---|---|---|---|---|
| Freemium | Free | ✓ | — | ✓ | 🇩🇪 Germany | |
| Freemium | Free | ✓ | — | ✓ | 🇺🇸 United States | |
| Freemium | $249/mo | ✓ | Cloud + Self-hosted | — | 🇺🇸 United States | |
| — | — | ✓ | — | — | 🇺🇸 United States | |
| Free + Usage Based | — | — | — | — | 🇺🇸 United States | |
| Freemium | $39/mo | ✓ | Cloud + Self-hosted | ✓ | 🇺🇸 United States | |
| — | — | ✓ | — | — | 🇺🇸 United States | |
|
D
DeepEval
|
— | — | ✓ | — | ✓ | 🇺🇸 United States |
| — | — | ✓ | — | ✓ | 🇺🇸 United States | |
| — | — | ✓ | — | — | 🇺🇸 United States | |
| — | — | ✓ | — | ✓ | 🇫🇷 France | |
| — | — | ✓ | — | ✓ | 🇺🇸 United States | |
| Subscription | Contact sales | — | Cloud | — | 🇺🇸 United States | |
| Freemium | $20/seat/mo | ✓ | Cloud + Self-hosted | ✓ | 🇺🇸 United States | |
| Enterprise | — | ✓ | Cloud + Self-hosted | — | 🇺🇸 United States | |
| — | — | ✓ | — | — | 🇺🇸 United States | |
| Freemium | $29/mo | ✓ | Cloud + Self-hosted | ✓ | 🇩🇪 Germany | |
| Freemium | $39/seat/mo | ✓ | Cloud + Self-hosted | — | 🇺🇸 United States | |
| Freemium | Free / €499/mo | ✓ | Cloud + Self-hosted | ✓ | 🇳🇱 Netherlands | |
| — | — | ✓ | — | — | 🇺🇸 United States | |
| Freemium | $20/user/mo | ✓ | Cloud + Self-hosted | — | 🇺🇸 United States | |
| — | — | — | — | — | 🇺🇸 United States | |
| — | — | ✓ | — | ✓ | 🇺🇸 United States | |
| Freemium | $49/mo | ✓ | Cloud + Self-hosted | — | 🇺🇸 United States | |
| Free | Free | — | — | ✓ | 🇺🇸 United States | |
| — | — | ✓ | — | ✓ | — | |
| Freemium | Free trial | ✓ | Cloud | — | 🇺🇸 United States | |
| — | — | ✓ | — | ✓ | 🇺🇸 United States | |
| Freemium | Free | ✓ | — | — | 🇺🇸 United States |
Providers with free tiers
These observability & analytics providers offer free credits, free tiers, or open-source self-hosting options to get started without upfront costs.
AI observability platform with tracing, evaluation, and monitoring for LLM an...
From: Free
Testing and monitoring platform for AI voice and chat agents
LLM tracing, evaluation, and prompt monitoring built into the Datadog APM pla...
Show all 25 providers with free tiers
Open-source LLM evaluation framework with 50+ metrics for testing agents, RAG...
Open-source ML and LLM evaluation with 100+ built-in metrics and CI/CD integr...
AI evaluation and observability platform with hallucination detection and rea...
Eliminate risks of biases, performance issues & security holes in AI models. ...
Gain comprehensive insights into the cost, performance, feedback, traces of y...
Join thousands of startups and enterprises who use Helicone's Generative AI p...
From: $20/seat/mo
AI Performance and Reliability, Delivered
Collaborate on prompts, evaluate, and optimize LLM-powered Apps with Klu.
Traces, evals, prompt management and metrics to debug and improve your LLM ap...
From: $29/mo
LangSmith is a unified DevOps platform for developing, collaborating, testing...
From: $39/seat/mo
LLM observability platform with quality monitoring, guardrails, and evaluatio...
From: Free / €499/mo
LLMOps platform for logging, debugging, and improving LLM-powered applications
AI gateway for routing to 1,600+ LLMs with observability, guardrails, and pro...
Visually manage prompts. Evaluate models. Log LLM requests. Search usage hist...
From: $49/mo
Open-source testing platform for LLM and agentic applications. Test generatio...
Production monitoring for AI agents with automated failure detection and diag...
From: Free trial
Open-source LLM observability built on OpenTelemetry, with automatic instrume...
ML experiment tracking, LLM observability, and evaluation platform for AI teams
From: Free
Frequently asked questions
What is the cheapest LLM observability tool?
Langfuse is free and open-source for self-hosting with no usage limits. For managed services, Helicone offers a free tier up to 10,000 requests/month, and Lunary has a free plan for small projects. Braintrust charges per log row rather than per seat, which can be cheaper for small teams with high volume. The comparison table above lists pricing models for all tools in this category.
Which LLM observability tools are open source?
Langfuse (MIT), Opik by Comet (Apache 2.0), Phoenix by Arize (custom open-source), Traceloop (Apache 2.0), and LangWatch are open-source and can be self-hosted. Langfuse has the largest self-hosted community. Use the "Open source" filter above to see the full list.
What is the difference between LangSmith and Langfuse?
LangSmith is a commercial product by LangChain with tight LangChain integration, prompt versioning, evaluation, and a managed cloud. Langfuse is open-source (MIT), framework-agnostic, and can be self-hosted. LangSmith is easier if you already use LangChain. Langfuse is the common choice if you want to avoid vendor lock-in or need to keep trace data on your own infrastructure.
Which LLM observability platforms support self-hosting?
Langfuse, Opik, Traceloop, Phoenix, and LangWatch can all be self-hosted. This matters for teams with strict data residency requirements or those who want to avoid sending prompt/completion data to third-party servers. Langfuse and Opik both offer Docker-based deployments that run on a single machine.
Do I need a dedicated LLM observability tool?
It depends on your setup. If you make a handful of API calls, logging to your existing monitoring stack is usually enough. Once you have multi-step chains, agents, or multiple providers, dedicated tools add value through token-level cost tracking, prompt/completion tracing, latency breakdowns per step, and evaluation frameworks that catch quality regressions before users do.
Which observability tools work with OpenTelemetry?
Traceloop is built on OpenTelemetry and exports traces in OTLP format, meaning you can send them to any OTLP-compatible backend (Datadog, Grafana, Jaeger). Helicone and Portkey use a proxy-based approach instead. Langfuse has its own SDK but also accepts OTLP. If your team already runs an OpenTelemetry pipeline, Traceloop fits in with the least friction.
How to choose an inference API provider
The right provider depends on workload type, latency requirements, and budget. Most providers use pay-per-token pricing for LLMs and per-second GPU billing for custom models. Token-based pricing varies by model, so the cheapest provider for one model may not be cheapest for another.
Free tiers are useful for prototyping but often come with rate limits. For production, compare per-token costs for your specific model, cold start latency, rate limits, and whether the provider supports the models you need.
Teams with data residency requirements should check hosting options and provider headquarters. European providers like Agenta, Giskard, Langfuse keep data within EU jurisdiction. See the full European AI Infrastructure directory. Self-hostable options like Braintrust and Comet Opik give full control over data location.
For a deeper analysis, read AI Inference API Providers Compared on the blog. Pricing changes frequently, so verify current rates on each provider's website. Submit a correction.
See how these tools fit into a full stack
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