Lunary vs Spanlens: Which is Better in 2026?
A comprehensive comparison of Lunary and Spanlens covering features, pricing, use cases, and which tool is the right choice for your needs.
⚡ Quick Verdict
Choose Lunary if:
- →You want more affordable paid plans (from $20/mo)
- →You need event logging with searchable traces for production and staging or cost, latency and quality tracking in one place
Choose Spanlens if:
- →You need one-line instrumentation via a cli that rewrites your call sites or request logging with cost, latency and token counts for openai, anthropic and gemini
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Lunary vs Spanlens: At a Glance
Pricing Comparison: Lunary vs Spanlens
Understanding the pricing differences between Lunary and Spanlens is crucial for making the right choice. Here's how their plans compare side by side.
Lunary Pricing
Spanlens Pricing
💡 Pricing takeaway: Both Lunary and Spanlens offer free tiers, making it easy to try before you buy. Compare the specific plans to find the best value for your use case.
Feature-by-Feature Comparison
Here's how every feature from Lunary and Spanlens stacks up.
What Makes Each Tool Unique
🔵 Unique to Lunary
Features available in Lunary but not in Spanlens:
- ✓Event logging with searchable traces for production and staging
- ✓Cost, latency and quality tracking in one place
- ✓Versioned prompt management decoupled from application code
- ✓AI playground for testing prompt variants on saved data
- ✓Human review, topic clustering and custom dashboards
- ✓Self-hosting with SSO, RBAC and PII masking on enterprise
🟣 Unique to Spanlens
Features available in Spanlens but not in Lunary:
- ✓One-line instrumentation via a CLI that rewrites your call sites
- ✓Request logging with cost, latency and token counts for OpenAI, Anthropic and Gemini
- ✓Agent workflow tracing in a Gantt view
- ✓PII and prompt-injection detection on request content
- ✓Three-sigma anomaly detection and cheaper-model recommendations with dollar savings
- ✓Fully MIT self-host with no feature gating, plus Ollama and LangGraph tracing
Use Case Recommendations
Best for: Lunary
Lunary is an observability and prompt-management platform for applications built on LLMs, covering the gap between a prototype that works in a notebook and a deployment you can be accountable for. It logs production and staging traffic as events, gives you searchable traces of what the model was asked and what it returned, tracks cost and latency, and surfaces how real users are actually interacting with a chatbot — which is routinely different from how the team assumed they would. Prompt management is versioned and separated from the application code, so a prompt change does not require a redeploy, and an AI playground lets you test variants against saved data before promoting one. Human review and topic clustering turn the raw log into something a product owner can act on, and Smart Views, custom dashboards and CSV/JSONL export cover the reporting layer. The platform is available self-hosted for teams whose data cannot leave their infrastructure, with SSO, granular access control, PII masking and data-warehouse connectors on the enterprise tier. It is a fit for small AI teams who need real observability without adopting a heavyweight enterprise APM, and the free tier covers personal projects at 10,000 events per month across three projects.
Ideal use cases:
- •Teams or individuals who need event logging with searchable traces for production and staging
- •Teams or individuals who need cost, latency and quality tracking in one place
- •Teams or individuals who need versioned prompt management decoupled from application code
- •Teams or individuals who need ai playground for testing prompt variants on saved data
- •Anyone focused on observability workflows
- •Anyone focused on prompt-management workflows
Best for: Spanlens
Spanlens is an MIT-licensed LLM observability platform whose main design goal is that instrumenting an application should cost one line rather than an afternoon. A CLI initialiser rewrites the call sites for you, after which every OpenAI, Anthropic and Gemini request is logged with its cost, latency and token counts, and multi-step agent workflows are traced into a Gantt view that shows where the time and money actually went. Beyond straight logging it runs three checks that most cost dashboards do not: anomaly detection on a three-sigma basis, PII and prompt-injection detection on request content, and a model recommendation pass that proposes cheaper models with a dollar-figure saving attached rather than a vague suggestion. Recent SDK releases added Ollama support for local models and LangGraph tracing, so self-hosted and graph-structured agent stacks are covered alongside the hosted APIs. The licensing position is the sharpest part of the pitch: the vendor states the project is fully MIT with no `ee/` folder, meaning there is no enterprise-only directory carved out of the open-source repository — self-host with Docker Compose and every feature listed on the paid tiers is available at zero cost. The hosted tiers exist to sell managed retention, seats and alerting rather than to gate functionality, and the site publishes direct comparisons against Langfuse and Helicone.
Ideal use cases:
- •Teams or individuals who need one-line instrumentation via a cli that rewrites your call sites
- •Teams or individuals who need request logging with cost, latency and token counts for openai, anthropic and gemini
- •Teams or individuals who need agent workflow tracing in a gantt view
- •Teams or individuals who need pii and prompt-injection detection on request content
- •Anyone focused on llm-observability workflows
- •Anyone focused on tracing workflows
🤖 Other AI Agent Infrastructure Tools to Consider
Lunary and Spanlens aren't the only options. Here are other popular tools in the same space:
SuperAGI
Open-source autonomous AI agent framework with visual dashboard — 14K GitHub stars
MetaGPT
Multi-agent AI framework simulating software teams — 45K GitHub stars, builds full apps from prompts
Cerebras
Fastest LLM inference powered by the Wafer Scale Engine.
Scale AI
AI data platform for training data and model evaluation.
Roboflow
End-to-end computer vision platform for developers.
Labelbox
Enterprise data labeling platform for ML training datasets.
Is one of these your tool?
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Frequently Asked Questions
Is Lunary better than Spanlens?
It depends on your needs. Lunary offers 6 key features including Event logging with searchable traces for production and staging and Cost, latency and quality tracking in one place, while Spanlens provides 6 features including One-line instrumentation via a CLI that rewrites your call sites and Request logging with cost, latency and token counts for OpenAI, Anthropic and Gemini. Lunary uses a freemium model with a free tier, while Spanlens is freemium with free access available. Choose based on which features and pricing model align with your requirements.
Is Lunary cheaper than Spanlens?
Lunary is cheaper, starting at $20/month compared to Spanlens's $29/month. Both tools offer free tiers, so you can try each before committing. Always check the official websites for the most current pricing.
Can I use Lunary and Spanlens together?
Yes, many users combine Lunary and Spanlens in their workflow. Lunary excels at event logging with searchable traces for production and staging, while Spanlens shines with one-line instrumentation via a cli that rewrites your call sites. Using both allows you to leverage the strengths of each tool, though this means managing two subscriptions — though free tiers can help manage costs.
What's the main difference between Lunary and Spanlens?
While both are ai agent infrastructure tools, Lunary emphasizes event logging with searchable traces for production and staging, whereas Spanlens is known for one-line instrumentation via a cli that rewrites your call sites. The best choice depends on your specific workflow and feature priorities.
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