AI Observability Model Pricing - Set LLM Token Costs

Use the Model pricing tab of AI Observability to set the price for each model. SigNoz uses these prices to calculate the cost of each span in USD. For prerequisites, see the AI Observability overview. To open the tab, select More > AI Observability in the side navigation, then select the Model pricing tab.

The tab has two parts: Model Costs lists your pricing rules, and Unpriced models lists models that no rule prices.

Model Costs tab #

SigNoz Cloud includes default prices for common models. In self-hosted SigNoz, add a pricing rule for each of your models.

To find a rule, type a model name or a provider name in the Search by model or provider box. To show only one type of rule, select User override or Auto in the source filter.

To share the filtered table, copy the page URL.

Add a pricing rule #

Only Admins can add, edit, map, or delete pricing rules.

1. On the Model Costs tab, selectAdd model cost .
2. In Billing Model ID , type an ID for the rule, for exampleopenai:gpt-4o . You cannot change the ID or theProvider after you save.
3. Select the Provider .
4. In Model name patterns (prefix match) , add thegen_ai.request.model values that this rule prices. To match every name that starts with a prefix, end the pattern with* , for examplegpt-4o* . A pattern without* matches only that exact name.
5. In Pricing (per 1M tokens, USD) , type theInput Cost and theOutput Cost . If the provider charges a different cached-token price, selectAdd pricing bucket . Add acache_read orcache_write price.
6. If you added cache prices, select the Cache mode that matches the provider:

• Subtract (OpenAI style) : the input token count includes cached tokens. SigNoz subtracts the cache-read tokens from the input tokens and bills them at thecache_read price.
• Additive (Anthropic style) : the input token count excludes cached tokens. SigNoz bills input,cache_read , andcache_write tokens at their own prices.
• Unknown (default): SigNoz bills all input tokens at the input price and does not use the cache prices.

7. Select Save .

Edit or delete a pricing rule #

To edit a rule, open the menu (⋮) at the end of its row and select Edit.

You cannot change the prices of an Auto-populated rule. To set your own, change the source to User override. To go back to the default price, select Auto-populated again and confirm. SigNoz discards your custom prices.

To delete a rule, open the menu (⋮) on its row. Select Delete, then confirm.

Price an unpriced model #

The Unpriced models tab lists models that SigNoz found in spans from the last hour but that match no pricing rule. SigNoz cannot calculate cost for spans from these models. In this tab, the UI calls a pricing rule a pricing model.

To price a model:

1. In the Map to billing model column of the model, open theSelect / Create a pricing model dropdown.
2. Select an existing rule.
3. Select Map model . SigNoz adds the model name as a pattern on that rule.

To set a new price instead, select Create a new pricing model at the bottom of the dropdown. The Add model cost drawer opens with the model name in Billing Model ID. Complete it as in Add a pricing rule.

When no model from the last hour is unpriced, the tab shows "All models in your traces are priced."

When price changes take effect #

A price change applies to spans that SigNoz receives after the change. If you reset a rule to the default SigNoz price, the reset can take up to 24 hours. Stored spans do not change.

Validate #

1. After the new price takes effect, send a new LLM span for the model from your application.
2. In the ExplorerList View , run a filter on the model, for examplegen_ai.request.model = 'gpt-4o' .
3. Select a span. The span opens in Trace Details.
4. In the span attributes, make sure that signoz.gen_ai.usage.tokens.cost exists. If it is missing, no rule matches the model name, so check the patterns of the rule. A value of0 means the price or the token count is zero.

Next steps #

- [AI Observability overview](https://signoz.io/docs/ai-observability/) : see cost, tokens, latency, and tool calls on one dashboard.
- [Explorer](https://signoz.io/docs/ai-observability-explorer/) : query your LLM and agent traces.
- [Attribute Mapping](https://signoz.io/docs/ai-observability-attribute-mapping/) : map other attribute names to the GenAI names.
- [LLM Observability integrations](https://signoz.io/docs/llm-observability/) : instrument OpenAI, Anthropic, LiteLLM, CrewAI, and other frameworks.

Get Help #

If you need help with the steps in this topic, please reach out to us on SigNoz Community Slack. If you are a SigNoz Cloud user, please use in product chat support located at the bottom right corner of your SigNoz instance or contact us at cloud-support@signoz.io.