# OpenLIT vs Helicone

> Helicone routes traffic through a proxy to capture telemetry. OpenLIT instruments your existing SDK calls directly — no proxy, no added latency, fully OpenTelemetry-native.

- HTML: https://openlit.io/compare/openlit-vs-helicone
- Markdown: https://openlit.io/compare/openlit-vs-helicone.md

Compare OpenLIT and Helicone for LLM observability. OpenLIT is SDK-based with no proxy latency, OpenTelemetry-native, and fully self-hostable.

## Feature comparison

### Core Architecture

| Feature | OpenLIT | Helicone |
| --- | --- | --- |
| OpenTelemetry-native | Yes | No |
| Open Source | Apache 2.0 | Apache 2.0 |
| Self-hostable | Yes | Yes |
| Proxy-free (no added latency) | Yes | No |
| SDK-based instrumentation | Yes | No |
| Vendor-neutral data format | Yes | No |

### LLM Monitoring

| Feature | OpenLIT | Helicone |
| --- | --- | --- |
| Token usage tracking | Yes | Yes |
| Cost per request | Yes | Yes |
| Latency / p95 metrics | Yes | Yes |
| Prompt & response logging | Yes | Yes |
| 60+ integrations (LLMs, frameworks, VectorDBs, GPUs) | Yes | OpenAI-compatible endpoints only |

### Infrastructure Monitoring

| Feature | OpenLIT | Helicone |
| --- | --- | --- |
| GPU monitoring (NVIDIA + AMD) | Yes | No |
| Vector DB tracing | Yes | No |
| Multi-environment tagging | Yes | Yes |
| Organisation management | Yes | Yes |

### Developer Tools

| Feature | OpenLIT | Helicone |
| --- | --- | --- |
| Prompt Hub (versioning) | Yes | Yes |
| Evaluations | Yes | Basic |
| Secrets Vault | Yes | No |
| Fleet Hub (multi-deployment) | Yes | No |
| Custom model pricing | Yes | No |
| Request caching | No | Yes |
| Rate limiting & key management | No | Yes |

### Observability Backends

| Feature | OpenLIT | Helicone |
| --- | --- | --- |
| Grafana / Prometheus export | Yes | No |
| Datadog export | Yes | No |
| Any OTLP-compatible backend | Yes | No |

## When to choose OpenLIT

- You cannot tolerate proxy-introduced latency on every LLM call
- You need GPU monitoring for self-hosted models (NVIDIA or AMD)
- You use non-OpenAI-compatible APIs (Anthropic native SDK, Bedrock, Vertex AI, etc.)
- You want to forward telemetry to Grafana, Datadog, or any OTLP backend
- You need Vector DB observability alongside LLM request tracing

## When to choose Helicone

- You want built-in request caching to reduce API costs
- You need proxy-layer rate limiting and API key management
- You prefer a cloud-first setup with minimal local infrastructure

## Related

- All comparisons: https://openlit.io/compare.md
- Pricing: https://openlit.io/pricing.md
- Docs: https://docs.openlit.io/latest/openlit/quickstart-ai-observability