Does an LLM proxy add latency to my application?

Yes — every request takes an extra network hop. Well-run proxies keep it to tens of milliseconds, but it is a hard dependency: if the proxy is slow or down, so is your application.

Which is more accurate for cost, a proxy or the billing API?

The billing API, by definition — it returns what you will be charged. A proxy computes cost from observed tokens and a price table it maintains, which can drift from your actual invoice through stale prices, caching, credits or discounts.

Proxy vs Billing API for LLM Cost Tracking

The choice is about what you can tolerate failing. A proxy sits in your request path and sees everything. A billing reader sits outside it and sees only aggregates. Neither is safer in general — they fail in different directions.

How each works

Proxy. You point your SDK at the vendor instead of the provider. Every request passes through them; they count tokens and multiply by a price table.

client = OpenAI(base_url="https://gateway.example.com/v1", api_key=KEY)

Billing API. A tool authenticates to the provider's billing endpoint with an admin credential and reads what you were charged. Your application is untouched and unaware.

GET /v1/organization/costs  →  daily buckets of dollars

Side by side

	Proxy	Billing API
Code change	Base URL, or a full SDK	None
In your request path	Yes	No
Latency added	Yes, an extra hop	None
Can take your app down	Yes	No
Sees prompts and responses	Yes	No
Granularity	Per request	Daily
Freshness	Seconds	Daily
Per-customer attribution	Yes, with tagging	No
Per-feature attribution	Yes	Only via key or project structure
Sees untracked traffic	No	Yes — everything on the account
Cost figures are	Computed from a price table	What you are billed
Extra capabilities	Caching, fallbacks, routing	None
Credential needed	Their API key	Provider admin key

Two rows decide most cases: "can take your app down" and "sees untracked traffic".

The failure modes

A proxy fails loudly. If it degrades, your product degrades. That's a real availability decision, not a theoretical one — you're adding a dependency to the hot path in exchange for observability.

A billing reader fails quietly. If it breaks, you stop getting numbers and your application never notices. Much safer, and the reason it's a reasonable default.

A proxy has a coverage hole. It only sees what was routed through it. The prototype key from March, the script a teammate runs locally, the notebook, the cron job someone set up and forgot — none of it appears. That is very often exactly the spend that surprises you, so the tool built to prevent surprises is structurally blind to the most common cause.

A billing reader has a resolution hole. It cannot tell you which endpoint or which customer. If that's your question, no amount of billing data answers it.

Prompt visibility

Worth separating from performance, because it's frequently the deciding factor.

A proxy must see request and response content to do its job. For most applications that's fine — it's the same trust you already extend to the model provider. For applications handling health data, legal documents, or anything under a data-processing agreement, adding a second processor is a compliance question, not a preference.

Billing data contains no content. Dollars, tokens, model names, dates. Nothing else.

This is also why Langfuse's self-hosting option matters: it resolves the objection by keeping the data inside your own estate.

Cost accuracy

Slightly counter-intuitive: the proxy is faster but less accurate.

A proxy computes cost from tokens it observed times a price it has on file. That price table can go stale after a provider change. It can't know about your negotiated discounts, your credits, or prompt-caching hits priced differently. It's a very good estimate.

The billing API returns what the provider will invoice. It is the number, several hours late.

For alerting, the estimate is fine. For reconciliation or reporting a real figure, use billing data.

Which to pick

Proxy, if you need: cost per customer or per feature · prompt-level debugging with cost attached · caching or automatic failover · to catch a runaway within minutes.

Billing API, if you need: no third party in production · prompt confidentiality · zero integration work · coverage of _all_ account spend including things you forgot · the actual billed figure · several providers in one number.

Both, if: you're optimising a production service _and_ want a total that catches everything outside it. This is the setup most teams converge on, and the two tools genuinely don't overlap.

Where TKN sits

TKN is a billing-API reader, so everything in the right-hand column applies — including the limitations. It is daily. It cannot tell you what one request cost. If you need per-feature attribution, use Helicone and we'd tell you the same thing in person.

What TKN adds beyond reading: several providers in one figure, spend rules checked against live daily spend, keys held in the device Keychain rather than on a server, and a kill switch that revokes at the provider — the one thing neither architecture normally does at all.

Proxy-based vs billing-API cost tracking