spaturzu vs Helicone
Helicone is an LLM observability platform with a full-featured AI Gateway — built to debug what a model actually said and to route requests across 100+ providers from one endpoint. spaturzu answers a different question: which agent spent the money, and how do we keep it under a hard cap — with no proxy in the request path and no prompt content ever leaving your servers.
Side by side
| Capability | spaturzu | Helicone |
|---|---|---|
| Primary job | Per-agent cost + budgets + fallback | LLM observability + AI Gateway |
| Request path | In-process SDK; calls go direct to provider | Primary: AI Gateway (proxy). Async OpenLLMetry mode also available |
| Prompts stored on tool's backend | Never — only token counts + cost | Yes by default; opt-outs (Helicone-Omit-* headers, async mode) |
| Agent attribution model | run() frames; agentPath propagates to nested calls — designed for cost rollup | Manual: Helicone-Property-* headers + Sessions with slash-path |
| Budget cap before the call | Typed BudgetExceededError, in-process, no proxy | Cost-based rate limit at the gateway (e.g. $5/hr/user), returns 429 |
| Cross-provider fallback | In-process, explicit pairwise translators across 5 providers (20 directional pairs) | AI Gateway covers 100+ providers via OpenAI-SDK translation; gateway-mediated |
| Full prompt/response inspection | Not in scope, by design | Core feature |
| Prompt mgmt, evals, datasets | Not in scope | Prompts, Experiments, Datasets are GA. Evals are score ingestion |
Reflects publicly documented behaviour as of May 2026.
Which should you choose?
Choose spaturzu when…
- →You need cost attributed to the agent and run that made each call — not just per-user or per-key.
- →You cannot send prompt or response content to a third-party backend, by policy or by preference.
- →You want a hard budget cap enforced in-process, before the provider call, with no proxy in the request path.
Choose Helicone when…
- →You want to read and search full prompt and response bodies to debug model behaviour.
- →You want a single proxy endpoint that routes and load-balances across many providers.
- →Per-user or per-key spend rate-limiting at the gateway (returning 429s) fits how you control cost.
Can I use both?
They coexist cleanly: keep Helicone (or its async mode) for deep prompt-level debugging, and add spaturzu for per-agent cost rollups and in-process budget caps. Because spaturzu calls the provider directly and never holds prompt content, it doesn't compete for the request path.
Questions
Is spaturzu a Helicone alternative?
For per-agent cost attribution and in-process budget caps, yes — spaturzu does that without proxying your traffic. For reading full prompt/response bodies and routing across 100+ providers through one gateway, Helicone does more; the two are complementary rather than strictly interchangeable.
Does spaturzu proxy my LLM requests like Helicone's AI Gateway?
No. spaturzu is an in-process SDK: your keys call OpenAI, Anthropic, Bedrock, Gemini, or Mistral directly, and only token counts and cost are sent to spaturzu. There is no proxy in the request path, so no added network hop or shared egress point.
Will spaturzu store my prompts?
Never. The SDK converts prompt and response text to token counts inside your process and sends only the counts. Helicone stores request/response bodies by default (with opt-outs); spaturzu has nothing to opt out of because it never receives them.
Can I run spaturzu and Helicone together?
Yes. Keep Helicone for prompt-level debugging and gateway routing, and add spaturzu for per-agent cost rollups and hard budget caps. They don't compete for the request path.
These claims reflect publicly documented Helicone behaviour as of May 2026. Spot a mistake? Let us know and we'll fix it.
See which agent spent the money.
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Also compare: spaturzu vs Langfuse.
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