Helicone vs Galileo: Best Open-Source LLM Observability Platform

Yusuf Ishola· April 28, 2025

As Large Language Models (LLMs) become central to more applications, developers need robust tools to monitor performance, debug issues, and optimize costs.

Helicone and Galileo are two leading platforms in the LLM observability space, each bringing unique strengths to the table.

In this comparison, we'll analyze their features, integration methods, and best use cases to help you determine which platform is the right fit for your needs.

At a Glance: Helicone vs. Galileo

How is Helicone different?

1. Helicone is open-source and self-hostable

Helicone is completely open-source, allowing you full control over your data and implementation. Companies can self-host Helicone within their infrastructure, ensuring flexibility and customization tailored to specific business needs.

While Galileo offers on-premises deployment for enterprise clients, its core platform remains proprietary. Being able to inspect, modify, and contribute to the codebase gives Helicone users a deep level of transparency and control.

2. Helicone offers flexible deployment options

Helicone provides multiple integration methods:

• Proxy-based: Simply change your base URL for a one-line integration
• Async logging: Use Helicone's SDK for background logging without affecting request flow

This flexibility makes Helicone adaptable to various architectural needs. Galileo primarily uses an SDK-based approach, which requires more code changes throughout your application.

3. Helicone has a friendlier pricing model

Helicone offers a generous free tier with 10k free requests/month. This allows you to get started with Helicone without any upfront costs.

Helicone also offers Pro, Team, and Enterprise tiers with transparent pricing, catering to businesses of all sizes.

Galileo offers a limited free tier with 5,000 traces/month and jumps to Enterprise pricing after that, making it more expensive for smaller teams.

Quick Comparison: Helicone vs. Galileo

Platform

LLM Evaluation & Monitoring

Security, Compliance, Privacy

Helicone: Observability for the Complete LLM Lifecycle

Helicone is an open-source observability platform built for developers who need to monitor, debug, and optimize their LLM applications.

It provides comprehensive logging, cost tracking, and debugging tools like Sessions. Developers choose Helicone because of its rich analytics and easy integration.

Key Features

• 1-Line Integration: Get started in minutes with proxy-based integration or async logging
• Sessions: Track multi-step LLM workflows and conversation flows with detailed tracing
• Routing/Gateway: Connect multiple LLM providers and serve as a fallback in case of failure
• Response Caching: Reduce costs and latency with built-in caching
• Prompt Management: Version, test, and optimize prompts with A/B testing
• Comprehensive Analytics: Track costs, latency, usage patterns, and more
• Webhooks: Create automations and alerts based on LLM activity

Why Developers Choose Helicone

• Developer-friendly: Minimal setup process and clean UI for non-technical users
• Cost efficiency: Caching and detailed cost tracking help optimize expenses
• Scalability: Built on distributed architecture (Cloudflare Workers, ClickHouse, Kafka)
• Flexible deployment: Self-host or use cloud with transparent pricing

How to Integrate with Helicone

Here's how simple it is to integrate Helicone with OpenAI:

import OpenAI from "openai";

const openai = new OpenAI({
  apiKey: process.env.OPENAI_API_KEY,
  baseURL: "https://oai.helicone.ai/v1",
  defaultHeaders: {
    "Helicone-Auth": `Bearer ${process.env.HELICONE_API_KEY}`, // Just add this line to your code
  },
});

For other providers, check out the documentation.

Galileo: Evaluation-Focused LLM Monitoring

Galileo AI is an "Evaluation Intelligence Platform" designed to help teams evaluate, iterate, monitor, and protect generative AI applications.

It focuses on ensuring quality outputs and providing guard rails for production LLM deployments.

Key Features

• Galileo Evaluate: Test prompts and models with built-in evaluation metrics
• Galileo Observe: Monitor production LLM applications with real-time dashboards
• Galileo Protect: Enforce policies with real-time guardrails for outputs
• Luna Evaluation Suite: Built-in metrics for context adherence, completeness, correctness
• Agentic Evaluations: Specialized tools for monitoring multi-step AI agents

Why Developers Choose Galileo

• Built-in quality metrics: Automatically score outputs for correctness and safety
• End-to-end observability: From development to production in one platform
• Safety guardrails: Enforce content policies and prevent harmful outputs

How to Integrate with Galileo

Galileo integration typically uses their SDK:

import { OpenAI } from "openai";
import { init, flush, wrapOpenAI } from "galileo";
import dotenv from 'dotenv';
dotenv.config();

// Initialize Galileo
init({
  projectName: "my-project",
  logStreamName: "development"
});

const openai = wrapOpenAI(new OpenAI({ apiKey: process.env.OPENAI_API_KEY }));
const prompt = "Explain the following topic succinctly: Newton's First Law";
await openai.chat.completions.create({
 model: "gpt-4o",
 messages: [{ content: prompt, role: "user" }],
});

// Flush logs before exiting
await flush();

UI & Dashboard Comparison

Choosing the right observability tool depends on more than just features—the dashboard experience significantly impacts your team's ability to extract insights and take action.

Here's a quick comparison of the two platforms:

Helicone Dashboard

Helicone's dashboard highlights the most important operational metrics and is designed for the customizability that developers need:

• Clean, intuitive layout organized by key metrics such as requests, costs, latency
• Deep data segmentation capabilities, allowing you to drill down by models, users, custom properties
• Time-series visualization for tracking trends and anomalies
• Deep filtering abilities to help you identify specific requests

Developers choose Helicone because its UI is user-friendly for both technical and non-technical teams.

Galileo Dashboard

Galileo's dashboard focuses on evaluation metrics and quality assessment:

• Metric-focused views highlighting quality scores (correctness, adherence)
• Side-by-side comparisons for prompt and model experiments
• Guardrail visualizations showing policy violations and risky outputs
• Leaderboards tracking performance across different prompt versions
• Trace exploration for detailed analysis of individual responses

Galileo's UI is tailored for ML engineers and data scientists who need deep insights into model behavior and output quality.

Which platform should you choose?

Both platforms offer valuable tools for LLM observability, but they excel in different areas:

Choose Helicone if you need:

• 🔹 A simple, one-line integration that works with any LLM provider
• 🔹 Comprehensive monitoring, cost tracking, and optimization tools
• 🔹 Full control through open-source and self-hosting options
• 🔹 A platform usable by both technical and non-technical team members
• 🔹 Transparent, flexible pricing that scales with your needs

Choose Galileo if you need:

• ⬥ Built-in evaluation metrics for output quality
• ⬥ Real-time guardrails to enforce content policies
• ⬥ Enterprise-scale evaluation tools
• ⬥ A platform focused specifically on evaluation intelligence

Both platforms offer free tiers. We recommend testing them yourself before making a decision! If you need any support, our team is here to help.

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• Helicone vs. Langfuse: Comparing LLM Observability Tools
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