The Tool Desk
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Home Assistant can use a locally hosted Ollama model as a conversation agent, and that agent can control smart-home devices when you explicitly enable control and expose the entities it may use. The key distinction: Home Assistant connects to an external Ollama server; the integration does not turn Home Assistant itself—or an old GPU—into a model host. The GPU is part of your particular server build, not a universal requirement.
How Ollama, Home Assistant, and your GPU fit together
The setup has three separate parts: Home Assistant provides the smart-home context and device actions, Ollama runs the language model, and the computer hosting Ollama supplies the CPU, GPU, memory, and storage used for inference. Home Assistant’s built-in Ollama integration connects to an Ollama server that is external to the Home Assistant instance and reachable over the network. It adds an Ollama-powered conversation agent; it does not host the model itself. See the Home Assistant Ollama integration documentation.
That means an older GPU may be useful if it can run your chosen model at an acceptable speed, but the official Home Assistant setup documentation does not name a required GPU, minimum VRAM, model, or performance target. Suitability depends on the model and quantization, context window, available memory, other workloads, and the response time you consider acceptable. The title’s particular GPU is therefore a build detail, not a promise that every old graphics card will work equally well.
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What the local LLM can—and cannot—do
By default, a conversation agent can respond to a conversation; device control is a separate capability that you enable in the Ollama integration. Home Assistant’s LLM API gives compatible agents a way to call tools—operations such as retrieving information or performing an action—with arguments validated against a defined parameter schema. The developer documentation describes tool behavior using annotations such as read-only, destructive, idempotent, and open-world. This is the interface between the model and Home Assistant, not unrestricted access to every device or service in your home. Read the Home Assistant LLM integration documentation and LLM API developer documentation.
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Only entities exposed to the agent are available for its Home Assistant control. The official Ollama integration says, “Only models that support Tools may control Home Assistant.” It also recommends exposing fewer than 25 entities when experimenting with local LLMs. That is experimentation guidance, not a formal safety threshold: expose only the devices and information needed for the tasks you intend to try.
Tool calling is not a guarantee that a model will interpret a request correctly. Home Assistant warns that smaller models may make mistakes and may not reliably maintain a conversation when control is enabled. Treat model-generated actions as fallible, particularly for consequential devices, and check the entity permissions and resulting behavior before relying on the setup.
Connect an Ollama server to Home Assistant
First install and run Ollama on a separate computer or server that Home Assistant can reach over your network, and make the model you intend to use available there. The integration downloads models during setup according to its configuration flow; available models and settings can change, so use the current integration instructions for the exact options shown by your Home Assistant version.
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- In Home Assistant, open Settings > Devices & services. Choose the option to add an integration, search for “Ollama,” and select it.
- Enter the Ollama server URL. Use the network address and port at which the external Ollama server is reachable from Home Assistant. Provide an API key if your server setup requires one.
- Select the model and configure the agent. The integration flow offers settings for prompt instructions, context-window size, conversation-history limit, keep-alive duration, and whether the model should think before responding. Choose settings appropriate to your model and intended workload rather than assuming one configuration fits every host.
- Decide whether to allow Home Assistant control. Leave control disabled if you want a conversational agent without device actions. If you enable it, expose only the entities needed for the tasks you want to test.
- Finish setup and test with a low-risk request. Confirm the model responds, then test any enabled tool action with a device whose state you can easily verify.
The server URL, model, and optional API key connect the two systems; the control setting and exposed-entity list determine whether the conversation agent can act on Home Assistant devices. A connected model alone does not imply it can control your home.
Using the agent through Assist or text chat
The Ollama agent can be used for text conversations, and Home Assistant Assist can route conversations to a selected local or cloud LLM agent. Assist control is a choice, not an automatic consequence of installing Ollama: select the agent and decide whether it should have control, subject to the entities you expose. Home Assistant’s Assist documentation explains the voice-agent configuration.
Voice hardware and audio processing are separate from the language model. A microphone or voice endpoint captures speech; speech-to-text converts it to text, the conversation agent handles the request, and text-to-speech can read the reply aloud. Configure speech-to-text and text-to-speech separately if you want voice input and output. Assist may handle recognized commands before sending less direct or open-ended requests to an AI agent; Home Assistant says this can be faster than routing every intent through an LLM. The exact behavior depends on your Home Assistant version, selected agent, audio stack, and configuration.
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Home Assistant’s 2025 discussion of Assist and AI also describes sharing context between Assist and an AI agent and using streaming text-to-speech to reduce perceived waiting. Those are configuration- and version-dependent capabilities, not features to assume are active in every Ollama setup. See Home Assistant’s 2025 article on AI in Home Assistant.
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Both local and cloud agents can be used in Home Assistant, but they differ in where processing happens and what you must maintain. The trade-offs below are qualitative: the available Home Assistant material does not establish current service prices, response-time benchmarks, or a universal capability ranking.
| Consideration | Local Ollama server | Cloud conversation agent |
|---|---|---|
| Data routing | Model inference runs on the Ollama host; network access is still needed between that host and Home Assistant. Check your own configuration to understand any other data flows. | Conversation processing is handled by the selected cloud provider; its data handling depends on that service. |
| Recurring service cost | No cloud-model subscription is inherent in the local integration, but the host uses hardware and electricity. No amount is established here. | Any cost depends on the chosen provider and its current plan; no current price is established here. |
| Model capability | Depends on the model you can run and its tool-calling support. Home Assistant cautions that smaller models may make mistakes or struggle to maintain conversation with control enabled. | Home Assistant’s 2024 comparison described cloud models as more powerful at that time. That historical characterization is not a current benchmark or a guarantee about a particular service. |
| Response latency | Depends on the model, host, configuration, and workload. No GPU benchmark or timing is established for the unspecified build. | Depends on the service and network conditions; no comparable measurement is established here. |
| Setup and maintenance | You maintain an Ollama host, model, and network connection to Home Assistant. | You configure the selected provider and rely on its service availability and connection. |
| Internet reliance | The Home Assistant-to-Ollama connection is local-network traffic, but local operation does not by itself establish that every part of your setup works without internet access. | Cloud processing relies on reaching the provider. |
Home Assistant’s 2024 article about AI agents for the smart home provides historical context for the local-versus-cloud distinction. Its comments about relative capability and cost should not be read as today’s pricing or performance data.
When a community integration may be relevant
The built-in Ollama integration is the reproducible starting point for connecting an Ollama server to Home Assistant. A separate, third-party project called home-llm describes a custom Home Assistant integration and model for local smart-home control. Its repository release history includes work on multiple backends, tool calling, voice streaming, and Home Assistant 2026.9 fixes. It is optional community software, not a prerequisite for the built-in Ollama integration; review its current documentation and compatibility before choosing it.
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