Prompt
Helicone alternative for prompt and cost tracking
Latest observation
Oct 9, 2026
OpenAI APIWeb search: off
If you want a Helicone alternative for prompt logging + cost tracking, here are the strongest options depending on what you need:
Best alternatives
1) Langfuse
- Open-source and self-hostable
- Tracks prompts, completions, token usage, latency, traces
- Good for debugging, evals, and prompt versioning
- Works with OpenAI, Anthropic, LangChain, LiteLLM, etc.
Best for: teams that want an observability platform similar to Helicone, but more control.
2) Portkey
- AI gateway with logging, analytics, retries, caching, routing
- Tracks usage and cost across models/providers
- Easy to sit between your app and model APIs
- Good for production traffic management
Best for: teams that want both observability and an LLM gateway.
3) LangSmith
- Strong tracing and debugging for LLM apps
- Great with LangChain ecosystem
- Supports prompt logs, runs, evaluation workflows
- Cost tracking is available, though not as gateway-oriented as Helicone
Best for: LangChain-heavy apps.
4) LiteLLM Proxy + Dashboard
- Open-source proxy layer for many model providers
- Centralized logging, spend tracking, rate limiting, routing
- Can act as a drop-in gateway across OpenAI-compatible APIs
Best for: teams wanting provider abstraction plus cost controls.
5) Humanloop
- Prompt management, evals, feedback loops, logging
- More product/workflow oriented
- Useful for teams iterating on prompts in production
Best for: prompt ops and human-in-the-loop workflows.
Quick recommendation
- Closest open-source alternative to Helicone: Langfuse
- Best gateway + cost control: Portkey or LiteLLM
- Best if you already use LangChain: LangSmith
If you want a simple stack
A common setup is:
- LiteLLM Proxy for routing + spend tracking
- Langfuse for tracing + prompt observability
This gives you both infrastructure control and deep analytics.
If you want, I can also give you:
- a feature comparison table, or
- the best option for your stack if you tell me whether you use OpenAI, Anthropic, LangChain, or self-hosted models.