# Model selection & switching One of the defining capabilities of GLBNXT Workspace is access to a wide range of AI models through a single interface. Rather than being locked into one model or one provider, users can choose the model that best fits their task, and switch between models at any point without leaving the chat environment. This flexibility is a core part of what makes Workspace a professional-grade AI environment, rather than a single-purpose tool. *** ### Available Models GLBNXT Workspace provides access to a broad portfolio of AI models, spanning both open-source models running on GLBNXT sovereign infrastructure and leading frontier models from major providers across the market. This includes models from providers such as OpenAI, Anthropic, Mistral, Google, Meta, DeepSeek, and others, alongside locally hosted open-source models optimised for specific tasks or data sensitivity requirements. The exact models available to you depend on the configuration set by your administrator. Your organisation may have enabled a curated selection of models suited to your industry, use cases, or compliance requirements. Models that have not been enabled for your role or team will not appear in your selection. *** ### Selecting a Model Model selection is available directly within the chat interface. A model selector is displayed at the top of the conversation window, showing the currently active model. Clicking it opens a list of all models available to your account, from which you can select the one you want to use. Each model in the list is typically labelled with its name and provider, giving you enough context to make an informed choice. Some interfaces display additional information such as context window size or a brief description of the model's strengths. Once selected, the model becomes active for your current conversation and any subsequent messages in that thread. *** ### Choosing the Right Model for Your Task Different models have different strengths, and part of getting the most out of Workspace is developing a sense of which model works best for which type of task. As a general guide: **For writing, drafting, and communication tasks**, frontier language models from providers such as Anthropic or OpenAI tend to produce polished, nuanced prose and handle complex instructions well. **For reasoning, analysis, and structured problem-solving**, models with strong reasoning capabilities, including dedicated reasoning-optimised variants, are better suited to working through multi-step logic or quantitative analysis. **For tasks involving sensitive or confidential data**, locally hosted open-source models running on GLBNXT sovereign infrastructure are often the most appropriate choice, as they do not route data through any external provider at all. **For coding and technical tasks**, models specifically trained on code tend to produce more accurate, well-structured output than general-purpose models. Your administrator may have configured model descriptions or labels within Workspace to help guide your team toward the appropriate models for your organisation's use cases. *** ### Switching Models Mid-Conversation You can switch models at any point during a conversation. When you change the active model, subsequent messages in the thread are processed by the newly selected model. Previous messages and responses remain visible in the conversation history, giving you full context regardless of which model generated them. This makes it possible to use different models for different stages of a task within the same conversation thread, for example drafting an initial outline with one model and then switching to a stronger reasoning model to stress-test the logic. *** ### Running Multiple Models in Parallel Some Workspace interfaces support running multiple models simultaneously on the same prompt. When enabled, this allows you to submit a single message and receive responses from two or more models side by side, making it straightforward to compare outputs and select the best result. This is particularly useful when evaluating which model handles a specific type of task most effectively for your workflow, or when you want a second perspective on a response before acting on it. *** ### Model Access and Governance Model availability within Workspace is fully governed by your administrator through the role-based access control layer. Administrators can enable or restrict specific models at the organisation, team, or individual user level. This ensures that model usage within your organisation remains aligned with your data governance policies, cost controls, and compliance requirements. If a model you need is not available in your interface, contact your Workspace administrator to request access. --- # Agent Instructions: Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question. Perform an HTTP GET request on the current page URL with the `ask` query parameter: ``` GET https://docs.glbnxt.com/workspace/ai-chat-and-models/model-selection-and-switching.md?ask= ``` The question should be specific, self-contained, and written in natural language. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.