TRACK · COMPARE · OPTIMIZE

Stop discovering your AI bill at the end of the month.

Model Meter is AI cost tracking software for engineering teams — LLM spend monitoring across every provider, attributed to project, feature, and model before the invoice arrives. Two-line SDK integration — install, init(), done.

Join the Waitlist How it works

Two-line SDK integration — install, init(), every call tracked.

AI spend overview

Illustrative data · October

Last 30 days

Total spend

$12,544+8.4%

Requests

1.84M+12.1%

Tokens

842M+6.7%

Monthly spend$14k forecast

By provider

OpenAI$5,890 · 47%

Anthropic$3,756 · 30%

Google$1,879 · 15%

Groq$1,019 · 8%

API platform

$4,820

Copilot

$3,170

Support AI

$2,984

Experiments

$1,570

Cost / quality

Best fit identified

The problem

AI spend is invisible until it isn't.

Costs invisible until invoice day

The average team discovers a costly AI bug 3–4 weeks after it ships. Model Meter shows spend in near real-time — by project, model, and environment.

No attribution across providers

OpenAI, Anthropic, Google, and Groq each have separate dashboards. Model Meter puts every provider in one breakdown so you know exactly which feature is spending what.

Model decisions made by gut

GPT-4o isn't always the right call. Cost-per-request and quality comparisons across models give you data to switch — or stay — with confidence.

What it does

One place for all your AI spend.

Unified AI Spend

Every LLM call across every provider, captured automatically via OpenTelemetry. One dashboard instead of four provider portals.

Project-Level Attribution

Know exactly which feature, service, or team is spending what. Stop guessing when the CFO asks.

Cost vs. Quality

Compare cost-per-request and quality side-by-side before switching models in production.

Budget Alerts

Set project-level spend limits. Get alerted when spending crosses thresholds — on Friday afternoon, not the following Monday.

Live dashboard — connect with the SDK

Clarity, from request to budget.

Every provider, every project, one view — spend trends, attribution, and budgets in a single dashboard.

Demo workspace

Month to date

$12,544

Budget used

62.7%

Avg. / 1K req

$6.82

Daily AI spendOct 1–30

Model comparison

Model	Requests	Cost	Latency	Status
GPT-4o	624k	$5,840	1.8s	Active
Claude 3.5 Sonnet	438k	$3,126	1.5s	Active
Gemini 2.0 Flash	302k	$1,879	1.2s	Active

Monthly budget$12,544 / $20,000

On track for this billing period

Project usage

API platform$4,820

38%

Engineering copilot$3,170

25%

Support intelligence$2,984

24%

R&D experiments$1,570

13%

How it works

Two lines of code. Every AI call tracked.

Install the SDK

npm install @model-meter/sdk — then call init() once at app startup with your API key and project ID.

Auto-track via OpenTelemetry

Every generateText() and streamText() call is captured automatically via OTel gen_ai.* spans — no per-call changes needed.

See spend in the dashboard

Spend by project, provider, model, and operation — updated in near real-time instead of at invoice time.

import { init } from '@model-meter/sdk';

// Call once at app startup
init({
  apiKey:      process.env.MODEL_METER_API_KEY,
  endpoint:    process.env.MODEL_METER_ENDPOINT,
  projectId:   'my-app',
  environment: 'production',
});

// Then every generateText() / streamText() call is tracked automatically.

Who it's for

Built for teams with 5–50 engineers using multiple LLM providers.

Role	Pain today	How Model Meter helps
Engineering manager	"Which feature caused this month's AI cost spike?"	Per-project cost breakdown, spend trends, anomaly visibility
Backend engineer	"I have no idea how much my AI calls cost"	Two-line SDK integration, zero impact on existing calls
Finance / FinOps	"The OpenAI invoice doesn't match anything in our systems"	Estimated vs. provider-reported cost side-by-side
AI/ML engineer	"Should I switch from GPT-4o to something cheaper?"	Cost-per-request and quality comparison across models
Startup founder	"We need visibility but can't afford another SaaS tool"	Two-line SDK integration — no proxy, no new infrastructure to buy

Not designed for: personal ChatGPT usage tracking, enterprise SSO/SOC 2, full LLM observability platforms (LangSmith, Langfuse), or universal LLM proxy/caching.

Launch offer

Lock in the best launch pricing.

We're building the managed cloud product. Waitlist members get the best pricing we ever offer, locked in before public rates go live.

Best launch pricing — locked in before public rates

Early-adopter discount on hosted plans

First in line when the hosted dashboard ships

Or read the docs on GitHub

FAQ

Questions, answered clearly.

Is Model Meter a proxy or gateway?

No. Model Meter is a cost tracking and visibility tool, not a proxy or gateway. It does not sit in the critical path of your AI calls. The SDK instruments existing API calls via OpenTelemetry and sends telemetry to Model Meter asynchronously. Your AI requests go directly to the provider.

Does Model Meter store my prompts or completions?

No. Model Meter does not collect prompts or completions by default. The SDK only captures: provider and model name, token usage (input, output, cached), latency, success or error status, and cost estimate. No prompt text or response text is transmitted.

How long does integration take?

SDK integration in an existing Node.js app typically takes 10–15 minutes: install the package, call init(), and set up the OTel span processor. After that, every generateText() and streamText() call is tracked automatically.

Are the cost estimates accurate?

They are estimates, not exact billing amounts. Provider pricing changes, discounts, credits, and batch rates are not always captured by request-level estimates. Model Meter marks estimates clearly as estimated vs. provider-reported. The billing reconciliation feature lets you import provider invoices and compare them against estimates.

What happens when a model's price changes?

Model Meter uses effective-dated pricing records. Each cost record stores the pricing version that was active at the time of the request, so historical cost data is not rewritten when prices change.

Is Model Meter free?

The Model Meter SDK is on GitHub — install it and call init() once at startup. The hosted product will be a paid subscription. Join the waitlist to lock in the best launch pricing.

Which providers are supported?

OpenAI (GPT-4o, GPT-4o-mini, GPT-4 Turbo, GPT-3.5), Anthropic (Claude 3.5 Sonnet, Claude 3.5 Haiku, Claude 3 Opus), Google Gemini (1.5 Pro, 1.5 Flash, 2.0 Flash), Mistral, Groq, and Cohere all have verified pricing records. Any provider supported by the Vercel AI SDK's OTel integration is captured automatically.

How does Model Meter compare to Helicone?

Helicone intercepts your LLM API calls through a proxy, recording requests and responses. Model Meter instruments your application via OpenTelemetry without sitting in the call path. Choose Model Meter when you can't route traffic through a third-party proxy, don't want prompts stored outside your application, or need cost attribution by project and team as the primary feature.

Stop guessing. Start seeing.

Join the waitlist to lock in the best launch pricing before public rates go live.

Join the Waitlist View pricing