> ## Documentation Index > Fetch the complete documentation index at: https://docs.poolside.ai/llms.txt > Use this file to discover all available pages before exploring further. # Supported models > Compare supported Poolside models by intended use, context window, and reasoning support. Poolside models are foundation models for software engineering. Use this page to choose a model, compare reasoning support and context windows, and find the right setup guidance for API access or deployment planning. Supported models are models that Poolside validates, ships, upgrades, patches, and helps operate in a self-managed Poolside inference deployment. Model availability, provider-specific variants, and model IDs can vary by access method. ## Compare models | Detail | [Laguna S 2.1](/release-notes/models#laguna-s-2-1)
[Laguna S 2.1](/release-notes/models#laguna-s-2-1) | [Laguna XS 2.1](/release-notes/models#laguna-xs-2-1)
[Laguna XS 2.1](/release-notes/models#laguna-xs-2-1) | [Laguna M.1](/release-notes/models#laguna-m-1)
[Laguna M.1](/release-notes/models#laguna-m-1) | | -------------- | ----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | | Best for | Long-horizon agentic coding and extended tool-use workflows | Fast agentic coding and rapid iteration | Complex, multi-step coding tasks where agent quality matters more than raw throughput | | Parameters | 118B total, 8B active per token | 33B total, 3B active per token | 225B total, 23B active per token | | Context window | 1M tokens | 256K tokens | 256K tokens | | Model type | Mixture of Experts | Mixture of Experts | Mixture of Experts | | Modality | Text-to-text | Text-to-text | Text-to-text | | Reasoning | Native reasoning with thinking on or off per request | Native reasoning with thinking on or off per request | Native reasoning with thinking on or off per request | | Model weights | [Hugging Face](https://huggingface.co/poolside/Laguna-S-2.1) | [Hugging Face](https://huggingface.co/poolside/Laguna-XS-2.1) | [Hugging Face](https://huggingface.co/poolside/Laguna-M.1) | | License | OpenMDW-1.1 | OpenMDW-1.1 | Apache 2.0 | ## Reasoning terminology Poolside and compatible providers use related terms for model reasoning behavior: * **Reasoning**: The general model capability or behavior. In API contexts, this can also refer to fields such as OpenRouter's `reasoning` object or assistant `reasoning_content`. * **Thinking**: The Poolside term for turning reasoning behavior on or off per request. * **Effort**: A generic scale used to express how much reasoning to request. ACP clients support `default`, `max`, `xhigh`, `high`, `medium`, `low`, `minimal`, and `none`; OpenRouter `reasoning.effort` values depend on provider model metadata. * **Thought level**: The ACP session config option that maps to effort values. ## Get started * [Try a Poolside model](https://chat.poolside.ai/) in your browser. No sign-up required. * [Follow the quickstart](/get-started/quickstart) to use a model with `pool`. * [Use the Poolside API](/api/overview) for base URLs, model IDs, authentication, and request examples.