# How to see LLM cost in Datadog > Datadog tracks LLM cost in two places that don't meet. One prices calls in real time, the other ingests your OpenAI invoice and forecasts it. URL: https://getculpa.com/llm-cost-in-datadog Last reviewed: 2026-08-03 Rates effective: 2026-07-02 ## Answer Datadog answers LLM cost twice. LLM Observability monitors token usage and cost across agents in real time, and Cloud Cost Management ingests OpenAI as a SaaS spend source and forecasts it. Culpa, a local-first LLM cost, margin, and forecast ledger, prices each call and sets it against the revenue the customer who triggered it pays you. ## Why this happens The common assumption about general observability platforms, that they see an LLM call as an HTTP span and lose the cost, is out of date for Datadog and this page won't repeat it. Its LLM Observability product says it monitors latency, token usage and cost across all AI agents in real time, with span-level inputs and outputs across prompts, retrieval, tool calls and decisions. Separately, Cloud Cost Management lists AI Costs alongside Snowflake and Databricks, with OpenAI named as an ingested spend source, plus reporting, budgets and spend forecasting. So Datadog can tell you what a call cost and what the OpenAI invoice will look like. The gap is between those two answers rather than in either of them. One is built from your traces and the other from a vendor bill, they live in different products with different pricing, and neither carries what your customer pays you, so neither can divide one by the other. Worth knowing before you build on it: Cloud Cost Management Pro is priced at $5 per $1,000 of cloud and SaaS spend per month, so the cost of watching scales with the spend being watched. ## What this usually looks like - You can see cost per agent in one product and the OpenAI invoice in another, and nobody has joined them. - Your spend forecast covers the vendor bill and says nothing about which customer drove it. - The observability bill grew because you instrumented more, not because you spent more on models. - A cost spike is visible and the customer behind it takes a day to find. - Nobody can say whether your largest AI customer is profitable. ## Common mistakes - Assuming an APM can't track LLM cost. Why it hurts: Datadog's LLM Observability tracks token usage and cost per agent in real time, so this argument loses on the facts. Do instead: Check what your existing tooling already does before buying anything to fill a gap it doesn't have. - Reading a Cloud Cost Management forecast as a unit-economics forecast. Why it hurts: It projects an ingested vendor invoice, which has no customer, feature or prompt version in it. Do instead: Forecast from your own per-call ledger if you need the answer broken down by anything. - Ignoring what the cost tooling itself costs. Why it hurts: Cloud Cost Management Pro is published at $5 per $1,000 of cloud and SaaS spend, so it scales with what it watches. Do instead: Price the cost tool against the spend it covers before assuming it pays for itself. - Instrumenting every span because storage feels free. Why it hurts: Datadog bills ingestion and custom metrics, so richer LLM traces raise a bill that has nothing to do with your model spend. Do instead: Decide what each span is for, and price the telemetry as a line of its own. ## Self-check - Open LLM Observability and find cost for one agent, then open Cloud Cost Management and find the OpenAI line. - Try to reconcile the two, and note how long it takes. - Ask what your top AI customer costs you and what they pay you, and see which system holds each half. - Price your Cloud Cost Management tier against the spend it watches. ## What the cost tool costs Datadog publishes Cloud Cost Management Pro at $5 per $1,000 in cloud and SaaS spend per month, read from its pricing page on 2026-08-03. Take a team with $40,000 a month of combined cloud and AI spend and price the watching against the watched. The spend figure is modelled and the rate is published. $40,000 monthly spend / $1,000 = 40 units 40 x $5.00 = $200.00 a month for Cloud Cost Management Pro which comes to 0.5% of the spend it reports on at $200,000 of monthly spend the same rate is $1,000.00 a month Half a percent is a fair price for cost visibility and it still costs, and it scales with the thing it measures rather than with the work you do. Worth putting in the same model as the spend itself, which almost nobody does. ## Cost figures Every figure carries its confidence and its source. No figure on this page is provider-reported. - $200.00 per month, Datadog Cloud Cost Management Pro on a modelled $40,000 of monthly cloud and SaaS spend [calculated] Source: $5 per $1,000 in cloud and SaaS spend per month, published on datadoghq.com/pricing and read 2026-08-03, applied to a modelled $40,000 monthly spend: 40 x $5.00 = $200.00, which is 0.5% of the spend covered. The rate is published and the spend figure is modelled. ## FAQ Q: Does Datadog track LLM costs? A: Yes, and this page says so plainly rather than implying otherwise. Datadog LLM Observability states it monitors latency, token usage and cost across all AI agents in real time. Separately, Cloud Cost Management lists AI Costs with OpenAI named as an ingested SaaS spend source. Q: Can Datadog forecast my AI spend? A: Cloud Cost Management publishes spend forecasting, budgets and anomaly detection, and its free tier is limited to Datadog's own costs while paid tiers cover cloud and SaaS spend. That forecast is built from an ingested vendor invoice, so it projects the bill rather than the economics underneath it. Q: What does Datadog's cost tooling cost? A: Cloud Cost Management Pro is published at $5 per $1,000 in cloud and SaaS spend per month, which works out at 0.5% of the spend it reports on. A free tier exists, limited to Datadog costs only. Read from its pricing page on 2026-08-03. Q: So why would I run Culpa alongside Datadog? A: For the one question neither of Datadog's two cost products can reach. Both work from telemetry or from invoices, and neither holds the revenue a customer pays you, so cost per customer stays a cost rather than becoming a margin. ## Sources - Datadog LLM Observability: https://www.datadoghq.com/product/llm-observability/ - Datadog pricing: https://www.datadoghq.com/pricing/ Run the free Cost Leak Scan: https://app.getculpa.com/scan?source=pseo&slug=llm-cost-in-datadog&cluster=problem Machine-readable index of every guide: https://getculpa.com/api/pages Human-readable index of every guide: https://getculpa.com/guides Site overview: https://app.getculpa.com/llms.txt Privacy: Culpa runs on your infrastructure. Your prompts and responses never leave it. Culpa counts calls to run your plan, and it fails open, so if it ever breaks your app keeps running.