> ## Documentation Index > Fetch the complete documentation index at: https://docs.together.ai/llms.txt > Use this file to discover all available pages before exploring further. # Usage limits & analytics > Understanding rate limits, model access, and cost analytics on Together AI. ## Rate limits Most users can expect to use Together AI serverless inference without encountering rate limits. Rate limiting may occasionally occur with high request volumes or large bursts of traffic. Response times can vary depending on the model and current demand. ### Errors during high demand When demand is high, Together may limit requests to maintain performance goals: * **`429 Too Many Requests`:** Reduce your request rate, spread out bursts, and retry with exponential backoff. * **`503 Service Unavailable`:** Wait briefly, then retry with exponential backoff. For workloads that need committed throughput and reliability, consider [provisioned throughput](/docs/inference/provisioned-throughput). See [serverless demand and performance](/docs/serverless/rate-limits#demand-and-performance) for details. ### Enterprise and Scale contracts If you have an active Enterprise or Scale contract, your purchased rate limits stay in place until your contract expires. Nothing changes during your current term. ### Need guaranteed throughput? If your workload needs committed throughput and reliability guarantees, [provisioned throughput](/docs/inference/provisioned-throughput) provides reserved capacity with a defined service level agreement (SLA). [Contact sales](https://www.together.ai/contact-sales-pt) to discuss your requirements. ### Exceptions Occasionally, due to the popularity of a specific model, Together may apply custom rate limits or access restrictions. These exceptions are called out in the relevant model documentation. ## Cost analytics Together AI provides built-in spend analytics so you can track usage and costs across products and models over time. To control spend with balance cut-offs or keep prepaid workloads funded with auto-recharge, see [Spend controls](/docs/billing-spend-controls). To access organization-level cost analytics, open your [billing settings](https://api.together.ai/settings/organization/~current/billing) and scroll to the **Usage** section. You can also select **See detailed cost analytics** on the monthly spend card, or open your [project's cost analytics page](https://api.together.ai/settings/projects/~current/cost-analytics) to scope the view to a single project. Select **Current Usage** on the billing page to see a draft view of your monthly invoice. Cost analytics dashboard showing daily spend by product ### Measure and grouping The chart toolbar lets you choose how to measure and group usage: * **Measure: Cost (\$)** - Chart daily spend in US dollars for the selected period. This is the default view. * **Measure: Units** - Chart daily billable units (for example, tokens) instead of dollar amounts. Totals and tooltips show unit counts. The chart subtitle updates to **Daily Units by …**. * **Group by Product** - Break down by product (Endpoints, Storage, Serverless Inference). * **Group by Line items** - Show individual usage line items. * **Group by Project** (beta) - Attribute spend or units to projects in your organization. * **Group by API key** (beta) - Attribute spend or units to API keys. When **Measure** is **Units**, grouping by product, project, or API key aggregates line-item quantities for that dimension. Group by **Line items** shows each billable line item's unit count directly. ### Filtering and time range * **Filter** - Include or exclude specific series from the current group-by dimension with a multi-select filter (type to search options). The control shows **All usage** until you apply a filter, and filtering is not available when you group by line items. * **Time range** - Adjust the start and end dates to analyze any period of usage history. All dates are in UTC. The chart updates as you change controls. The summary in the top right shows the total cost or total units for the selected period, depending on the measure. This documentation is built and hosted on [Mintlify](https://mintlify.com), a developer documentation platform.