Helicone and Arize AI both offer observability solutions but cater to different audience scales and integration philosophies. Helicone is favored for its simplicity in LLM observability with a higher rating of 4.5/5 from fewer reviews and a smaller team size, while Arize AI, boasting 9,104 GitHub stars, offers more extensive integrations and advanced functionalities, reflected in its broader user base and 4.3/5 average rating from 20 reviews.
Best for
Helicone is the better choice when a small, agile team needs a straightforward observability tool for monitoring and optimizing LLMs, especially in environments where specific integration with AI models like OpenAI is crucial.
Best for
Arize AI is the better choice when dealing with complex AI agent deployments, offering scalability and comprehensive features that are beneficial for larger teams with robust technical infrastructure.
Key Differences
Verdict
Helicone is ideal for smaller teams focused on LLM observability with a limited budget, enjoying strong but concentrated community support. In contrast, Arize AI suits larger organizations needing comprehensive AI infrastructure integration and support, with the backing of substantial funding and a broader user base. Organizations should choose based on their scale, complexity of needs, and desired depth of integrations.
Helicone
AI Gateway & LLM Observability
Helicone appears to be well-regarded, achieving positive ratings of 4/5 and 5/5 on G2, indicating user satisfaction with its functionality. Users highlight its integration within the domain of LLM (Large Language Model) tools, although it seems to have its own tracing format, which may add complexity in environments where standardization, like OpenTelemetry, is present. While pricing specifics are not detailed, the overall sentiment regarding value appears to be positive, given the high ratings. Helicone has a solid reputation, with notable mentions across multiple platforms, suggesting a strong presence and interest in its capabilities.
Arize AI
Unified LLM Observability and Agent Evaluation Platform for AI Applications—from development to production.
Arize AI is widely praised for its advanced capabilities and integration in AI infrastructure, with strong satisfaction reflected in consistent high ratings from users on platforms like g2. Users appreciate its technical sophistication and benefits for autonomous agent deployment. Some minor complaints arise regarding the learning curve or complexity associated with its use. Pricing appears to be acceptable given the tool's robust features, contributing to its positive overall reputation in AI model monitoring and optimization communities.
Helicone
-67% vs last weekArize AI
Not enough dataHelicone
Arize AI
Helicone
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Helicone
Pricing found: $79, $799, $5, $100
Arize AI
Pricing found: $50, $10, $3
Helicone (9)
Arize AI (1)
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Only in Arize AI (14)
Helicone
What do you like best about Helicone?Track usage, costs, and latency metrics with one line of codes. Review collected by and hosted on G2.com.What do you dislike about Helicone?How long it takes to scan the computer while doing the upload. Review collected by and hosted on G2.com.
What do you like best about Helicone?It's actually a great Open-source and cheap Platform for tracking different LLM usage, and can also create alerts on LLM responses. It supports multiple LLMs, including open-source ones. You'll get 100,000 free token uses. It's easy to implement and also offers great customer support. I use it more to integrate it into my projects. Review collected by and hosted on G2.com.What do you dislike about Helicone?The issue is that there are numerous alternatives, and implementing a custom LLM proxy on a framework like Axflow is challenging. The Experiment features are yet to be introduced, so we'll have to wait and see how go it is. Review collected by and hosted on G2.com.
Arize AI
What do you like best about Arize AI?Custom Code Evaluator and Live tracing projects. Review collected by and hosted on G2.com.What do you dislike about Arize AI?when you choose to run 10/20 rows in the playground by selecting the dataset. Instead of first 10 rows it randomly runs any 10 examples. Which doesn't helps with the consistency in running the evals Review collected by and hosted on G2.com.
What do you like best about Arize AI?I like how accessible it is to view traces, spans, and sessions, along with the evaluation methods. It’s also helpful that I can access them either through the UI or even offline. The filtering of data also makes it very easy to view the required spans, traces and sessions. Also the trace tree feature is very helpful to view the kind of each span. Review collected by and hosted on G2.com.What do you dislike about Arize AI?There’s really nothing to dislike. The only thing I’d change is making the filtration a bit simpler, because it took me a while to understand. Once I got how the filtration works, though, I was able to connect without any issues. Review collected by and hosted on G2.com.
What do you like best about Arize AI?The product is crisp and I understood how it operates through courses. It has almost got everything for model monitoring and other important features. It helps in all the for ML operations. Review collected by and hosted on G2.com.What do you dislike about Arize AI?Arize AI, if I am not wrong is like a dashboard. It would have been better if there was an API sort of thing where we can leverage the features through a package. Review collected by and hosted on G2.com.
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Arize AI

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Helicone
Arize AI
Helicone
OpenTelemetry just standardized LLM tracing. Here's what it actually looks like in code.
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Arize AI
Engineering the Autonomous Local Enterprise: A Technical Blueprint for Agentic RAG and Sovereign AI Infrastructure
# Engineering the Autonomous Local Enterprise: A Technical Blueprint for Agentic RAG and Sovereign AI Infrastructure The transition from reactive large language model applications to autonomous agentic workflows represents a fundamental paradigm shift in enterprise computing. In the 2025–2026 techn
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For real-time API call tracing in LLMs, Helicone is better suited, whereas Arize AI excels in complex AI agent deployment and unified observability.
Helicone offers a range of pricing plans including freemium and usage-based models, while Arize AI maintains a tiered subscription approach starting from $3.
Arize AI benefits from a larger community presence with 9,104 GitHub stars, compared to Helicone's 5,406 stars, indicative of wider adoption and discourse.
While possible, the tools serve different scales and integration ecosystems; Helicone could be used for specific LLM observability alongside Arize AI's comprehensive AI infrastructure.
Helicone likely offers a gentler learning curve due to its streamlined LLM focus and fewer features compared to the complexity associated with Arize AI's robust platform offerings.