Braintrust vs Helicone: Which Is Better in 2026?
A side-by-side comparison of Braintrust and Helicone, two ai tools tools — what each does, who it's best for, and how to choose between them.
Quick verdict
Braintrust and Helicone are both ai tools tools, so it comes down to fit. Pick Braintrust if you want An evaluation and observability platform for AI — systematically test, measure and improve your LLM applications. Pick Helicone if you want Dead-simple LLM observability — often a one-line proxy change to monitor your AI app's requests, costs…
Braintrust
An evaluation and observability platform for AI — systematically test, measure and improve your LLM applications.
- Category
- AI Tools
- Rating
- Not yet rated
- Best for
- LLM evaluation, AI observability, prompt engineering
Helicone
Dead-simple LLM observability — often a one-line proxy change to monitor your AI app's requests, costs and latency.
- Category
- AI Tools
- Rating
- Not yet rated
- Best for
- LLM observability, monitoring, open source
| At a glance | Braintrust | Helicone |
|---|---|---|
| What it is | An evaluation and observability platform for AI — systematically test, measure and improve your LLM applications. | Dead-simple LLM observability — often a one-line proxy change to monitor your AI app's requests, costs and latency. |
| Category | AI Tools | AI Tools |
| Type | Software | Software |
| Best for | LLM evaluation, AI observability, prompt engineering, testing | LLM observability, monitoring, open source, AI |
What is Braintrust?
Braintrust is an evaluation and observability platform for building reliable AI applications, helping teams systematically test, measure and improve the quality of their LLM-powered products. As companies move generative AI from impressive demos into production, they hit a hard truth: AI outputs are non-deterministic and hard to evaluate, and without rigorous testing it's nearly impossible to know whether a prompt change, model swap or new feature makes things better or worse. Braintrust brings the discipline of evaluation and experimentation to AI development.
At its core, Braintrust lets teams define evaluations — datasets of inputs with criteria or expected outputs — and run their AI against them to score quality objectively and repeatably. This means you can experiment with prompts, models and logic, then measure the impact with real data rather than gut feel, catching regressions before they reach users and steadily improving performance. It supports a range of scoring methods, including using AI to grade outputs, and makes it easy to compare versions side by side, turning AI development from guesswork into an iterative, measurable engineering process.
Beyond evaluation, Braintrust provides logging and observability for AI in production, so teams can monitor real-world behavior, capture interesting or problematic cases, and feed them back into their evaluation sets — closing the loop between production and improvement. This makes it a central tool for serious AI teams who treat quality and reliability as first-class concerns. It's used by companies building AI features that must work consistently, where the cost of poor or unpredictable outputs is high. As evaluating and trusting AI becomes one of the defining challenges of shipping generative AI, platforms like Braintrust are increasingly essential. For teams that want to build AI applications they can actually trust — and to measure and improve them rigorously — Braintrust offers a powerful, purpose-built evaluation and observability solution.
What is Helicone?
Helicone is an open-source LLM observability platform built around simplicity and speed of setup. Its headline feature is how easy it is to start: often you just route your LLM calls through its proxy with a one-line change, and instantly you have monitoring of your requests, costs and latency — no heavy integration required. For developers who want visibility into what their AI app is doing and what it is costing, fast, Helicone gets you there in minutes.
It provides clean, useful dashboards for cost and usage monitoring, request logging, caching and other practical features, all with minimal effort. While it is less focused on deep tracing of complex chains and rigorous evaluations than some heavier tools, it nails the everyday operational need: understanding your LLM usage, spotting cost spikes, debugging requests and keeping an eye on performance. Because it is open source with a self-hosting option, you can keep your prompt and response data under your control, which matters for teams handling sensitive information.
Helicone suits developers who want the fastest, simplest path to LLM observability — monitoring costs, usage and latency without a complex setup — and is a popular alternative alongside tools like Langfuse, which lean more toward deep tracing and evals. A common pattern is starting with Helicone for instant visibility, then adding a deeper tool as your AI app grows in complexity. If you are building with LLMs and want to stop guessing about cost and behavior, Helicone is an easy, low-friction way to get the visibility every production AI app needs.
Key differences at a glance
- Purpose: Braintrust is An evaluation and observability platform for AI — systematically test, measure and improve your LLM applications. Helicone, by contrast, is Dead-simple LLM observability — often a one-line proxy change to monitor your AI app's requests, costs and latency.
- Category & type: both sit in AI Tools, and both are offered as software.
- Best suited for: Braintrust leans toward LLM evaluation, AI observability, prompt engineering, whereas Helicone leans toward LLM observability, monitoring, open source.
- Community rating: Braintrust is not yet rated vs Helicone is not yet rated. Ratings are community-submitted and change over time.
Braintrust vs Helicone: which should you choose?
Braintrust and Helicone both serve the ai tools space, so the best choice depends on your priorities. Choose Braintrust if you want An evaluation and observability platform for AI — systematically test, measure and improve your LLM applications. Choose Helicone if you want Dead-simple LLM observability — often a one-line proxy change to monitor your AI app's requests, costs and latency.The smartest move is to try each one's free tier or trial on a real task — that's the fastest way to feel the difference and pick the tool you'll actually stick with.
Frequently asked questions
Is Braintrust better than Helicone?
It depends on what you need. Braintrust is An evaluation and observability platform for AI — systematically test, measure and improve your LLM applications. Helicone is Dead-simple LLM observability — often a one-line proxy change to monitor your AI app's requests, costs and latency. Both are ai tools tools, so the right pick comes down to your specific priorities, budget and workflow.
What's the main difference between Braintrust and Helicone?
Braintrust focuses on An evaluation and observability platform for AI — systematically test, measure and improve your LLM applications. while Helicone focuses on Dead-simple LLM observability — often a one-line proxy change to monitor your AI app's requests, costs and latency. Read the full breakdown above and check each tool's site for current features and pricing.
Can I use both Braintrust and Helicone?
In many cases, yes — teams often use complementary tools together. Whether it makes sense depends on overlap in functionality and your budget. Try the free tier or trial of each to see how they fit your stack before committing.
Which is cheaper, Braintrust or Helicone?
Pricing changes often, so check each tool's pricing page for the latest. Many tools offer a free tier or trial, which is the best way to evaluate value for your specific usage before you pay.