Comparison

Nexus vs Helicone

Helicone is an AI gateway that captures LLM calls automatically by routing requests through a proxy. Here's an honest look at when Nexus makes more sense — and when Helicone is the better fit.

TL;DR

Choose Nexus if you…

  • ✓ Build multi-step agents with custom logic between LLM calls
  • ✓ Need full trace/span visibility into agent workflows
  • ✓ Use TypeScript agents or non-OpenAI/Anthropic models
  • ✓ Don't want to route production traffic through a third-party proxy
  • ✓ Want $9/mo flat rate (not $120/mo for team features)

Choose Helicone if you…

  • ✓ Want zero-instrumentation LLM call logging via proxy
  • ✓ Need built-in caching, rate limiting, or prompt management
  • ✓ Are primarily making direct OpenAI/Anthropic API calls
  • ✓ Need team collaboration features at scale
  • ✓ Want LLM cost tracking per user or request

The fundamental difference: proxy vs instrumentation

Helicone works as a proxy: you change your OpenAI base URL from api.openai.com to oai.helicone.ai and every LLM call is automatically captured. No SDK, no code changes beyond a one-line config edit.

Nexus works via instrumentation: you wrap your agent logic with the Nexus SDK to capture traces (entire agent runs) and spans (individual steps — LLM calls, tool use, retrieval). This means more setup, but you get visibility into the full agent workflow — not just raw LLM calls.

If your "agent" is mostly a single LLM call with a system prompt, Helicone's proxy model is simpler. If you're building multi-step agents where you need to understand what happened between calls, Nexus's trace/span model gives you the full picture.

Pricing

Plan Nexus Helicone
Free $0 · 1K traces/mo · 1 agent $0 · 10K requests/mo
Pro / Growth $9/mo · 50K traces · unlimited agents $120/mo · 2M requests/mo
Enterprise Custom pricing

Helicone pricing as of 2026. Nexus counts agent traces (full runs); Helicone counts individual LLM API requests — these are not equivalent units.

Feature comparison

Feature Nexus Helicone
Agent trace & span model
Zero-code LLM call capture ✓ (proxy)
TypeScript SDK ✓ open-source ✓ (proxy wrapper)
Python SDK ✓ open-source ✓ (proxy wrapper)
Multi-step agent visibility ✓ full waterfall Partial (per-request)
LLM cost tracking
Request caching
Rate limiting
Prompt management
Email alerts on failure ✓ (Pro)
Self-hosted option ✓ (open-source)
Cloudflare edge (global CDN)
Open-source server
Multi-agent dashboard Partial
Setup time < 2 min < 1 min (proxy change)

The honest take

Helicone is genuinely excellent for its use case: if you're building applications that make direct OpenAI or Anthropic API calls and you want logging, caching, and rate limiting without touching your application code, the proxy model is hard to beat. One line change to your base URL and you have full request/response logging.

The proxy model has real tradeoffs. Your production LLM traffic routes through Helicone's servers — that's an extra network hop and a dependency on their availability. For most teams this is fine, but it's worth considering. There's also a mental model gap: Helicone shows you individual requests, not agent runs. When a complex agent makes 12 LLM calls, you see 12 separate entries rather than one trace with 12 spans.

Nexus is built for the agent workflow problem specifically. If you're debugging "why did my agent fail on step 3?" you want traces with spans in waterfall order, not a list of raw API calls. The instrumentation overhead is 3–5 lines of SDK code, but you get the full agent timeline in return.

The pricing difference is significant for indie developers: $9/mo vs $120/mo at the first paid tier. Helicone's free tier is generous (10K requests/mo) but the paid jump is steep for individual developers.

Related

Try Nexus free — no credit card needed

1,000 traces/month free. Drop in 3 lines of code and see your first trace in under a minute.