Gpt Home is live · free · last verified 25 Oct 2026 · viability monitor
Gpt Home
Self-hosted voice assistant for smart home control, deployed as modular Docker containers
Pick this if you want a transparent, LLM-agnostic voice layer you can read and modify end to end, and you're fine maintaining it yourself. Start from the three split repositories, not the deprecated Docker Hub monolith, which is stale. It's a builders' reference implementation, not a household appliance you can hand to a non-technical family member.
Verdict generatedVerified 5d ago · liveness 65/100 · cite: rightaichoice.com/tools/gpt-home
- Privacy-focused hobbyists with spare hardware who want voice commands over their own devices
- Developers learning LangGraph agent orchestration and LiteLLM model routing on a real project
- Makers comfortable forking and maintaining an open-source Docker stack long term
- Experimenters who want to swap LLM backends per request without changing the pipeline
- Users expecting plug-and-play setup like Alexa or Google Home
- Anyone uncomfortable with Docker CLI, Compose, and Linux troubleshooting
- Households that need vendor support, SLAs, or a guaranteed maintenance roadmap
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Skip Gpt Home if you want a smart home assistant that works out of the box without Docker, Linux troubleshooting, or maintaining a forked open-source project yourself.
You supply the hardware — a Raspberry Pi 4-class host plus storage and a microphone or speaker setup is a real upfront cost even though the software is $0.
Gpt Home is free software at $0 with no subscription or per-user fee, which puts it below nearly every commercial assistant and below paid self-hosted stacks that charge per device or per user. The cost you actually bear is hardware plus your own maintenance hours, so a free cloud-tier smart speaker can still be cheaper for a household that just wants voice control. Against Home Assistant it is also free, but narrower — you are comparing a voice and agent layer to a full device-integration
In short
Gpt Home — Self-hosted voice assistant for smart home control, deployed as modular Docker containers. Best for Privacy-focused hobbyists with spare hardware who want voice commands over their own devices, Developers learning LangGraph agent orchestration and LiteLLM model routing on a real project, Makers comfortable forking and maintaining an open-source Docker stack long term. Free to use.
What is Gpt Home?
Gpt Home — Self-hosted voice assistant for smart home control, deployed as modular Docker containers. Best for Privacy-focused hobbyists with spare hardware who want voice commands over their own devices, Developers learning LangGraph agent orchestration and LiteLLM model routing on a real project, Makers comfortable forking and maintaining an open-source Docker stack long term. Free to use.
Gpt Home is an open-source, self-hosted AI voice assistant for controlling smart home devices by spoken command. It's built for developers and makers who want a ChatGPT-style voice layer running on their own hardware, with speech and device state never routed through a commercial cloud assistant. The pipeline pairs LangGraph for conversational agent orchestration with LiteLLM to route each request to a local model or an external LLM API, so the model behind the voice is your decision. The project has moved off the original all-in-one image. The judahpaul/gpt-home Docker Hub listing now carries a [Deprecated] notice pointing to three separate repositories — gpt-home-backend, gpt-home-frontend, and gpt-home-spotify — with the old image last updated about a year ago at 723.1 MB. That split lets you run the voice and LLM backend alone, attach a frontend, and treat Spotify control as its own container. Deployment is via Docker and Docker Compose on modest hardware, including Raspberry Pi 4-class boards. Setup assumes comfort with the Linux command line and reading source on GitHub; there's no installer wizard, and keeping it running means tracking upstream changes yourself. Against commercial assistants from Amazon and Google, Gpt Home trades plug-and-play convenience for data ownership and full control over the model. Compared with Home Assistant it's narrower — a voice and agent layer rather than a complete device-integration platform — but as a reference for wiring LiteLLM, LangGraph, and speech into one local pipeline, it earns its keep.
Key features
- Self-hosted voice control for smart home devices
- Local LLM inference routed through LiteLLM
- LangGraph-based conversational agent orchestration
- Swap between local LLMs and external LLM APIs per request
- Modular containers: gpt-home-backend, gpt-home-frontend, gpt-home-spotify
- Docker and Docker Compose deployment
- Runs on Raspberry Pi 4-class hardware
- Spotify control via the dedicated gpt-home-spotify container
- Custom agent graph editing with LangGraph
- Local-first design with no required cloud dependency
- Open-source code on GitHub for forking and modification
- Original judahpaul/gpt-home image marked [Deprecated] on Docker Hub
Behind the verdict
In practice, Gpt Home is less a product than a blueprint you run. The appeal is real: you own the audio path, you choose the model, and you can crack open the LangGraph agent graph when the conversation logic misbehaves. For a developer who has been meaning to learn how a local voice assistant is actually put together, that's a better classroom than any tutorial series. Where it bites is maintenance. The Docker Hub page still warns that the monolith is deprecated, so anyone following the most visible link lands on year-old code. New users should go straight to gpt-home-backend, gpt-home-frontend, and gpt-home-spotify. Expect to read GitHub issues and commit history before you expect a working setup. The modular split is the right call for long-term use — run only the backend if you want a headless voice layer, add the frontend when you need a UI, and keep Spotify control isolated. But it also means three moving parts to keep in sync, and no unified release cadence you can point a household at. Compared with Home Assistant, Gpt Home is a narrower tool: it handles voice and agent orchestration, not the full device-integration platform. If your goal is a broad smart-home hub, Home Assistant plus its voice pipeline covers more ground. If your goal is a clean, hackable example of LiteLLM and LangGraph driving speech on local hardware, this is a stronger study. We'd reach for Gpt Home when privacy matters, the hardware is already sitting on a shelf, and someone in the house can debug a Docker Compose stack. Pass if you need vendor support, an SLA, or a device that a non-technical family member can reset without a terminal.
Models under the hood
as of 2026-10-24
Limitations
- The Docker Hub image judahpaul/gpt-home is marked [Deprecated]; new images are deployed to the separate gpt-home-backend, gpt-home-frontend, and gpt-home-spotify repositories.
- That image was last updated about a year ago and is 723.1 MB.
- Deployment requires Docker, and setup assumes Linux command line, Docker Compose, and comfort reading source on GitHub.
- There is no installer wizard and no vendor support contract.
- The project is narrower than Home Assistant: it is a voice and agent layer rather than a full device-integration platform, so most homes will still need another system to talk to the hardware.
- Running a capable local LLM on Raspberry Pi 4-class hardware is limited, and falling back to an external LLM API reintroduces the cloud dependency the project is designed to avoid.
- You maintain it yourself and track upstream changes.
as of 2026-10-08
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Is Gpt Home still active?
Gpt Home is live · free · last verified 25 Oct 2026 · viability monitor.
Viability score
How well maintained and how widely used is Gpt Home? Built from what the vendor actually publishes (docs, changelog, tutorials, integrations, pricing), whether the site is live, and how much real users discuss it. How we calculate this
Last calculated: October 2026
How we score →What do users say about Gpt Home?
What people actually say about Gpt Home — is it worth it?
Our community sentiment research written Jul 3, 2026 is more than 90 days old, so it is being re-reviewed against current data and is not shown.
How we verified this
Every listed fact about Gpt Home— pricing, features, links, status — is re-read from the vendor's own pages by our verification pipeline and each change is logged with a date; the last pass ran on 25 Oct 2026. Pages mix model-assisted synthesis with human review; see how we verify.
Verification history
We have re-verified Gpt Home 12 times since . Each pass re-reads the vendor's own pages and re-checks every listed field against that evidence; passes where nothing had changed are marked as such.
- — changed description, pricing tiers, summary
- — changed pricing page
- — changed who it suits, description, features, who should skip it, summary, our verdict, integrations, pricing tiers
- — changed SSL certificate
- — changed summary, our verdict, pricing tiers, who should skip it, who it suits, description, features, integrations
- — changed pricing page
Showing the 6 most recent of 12 verification passes.
Free to cite with attribution — this page re-verifies continuously.
How much does Gpt Home cost in 2026?
Gpt Home: Free to use. Pricing last verified 25 Oct 2026.
Plans compared
Every published Gpt Home tier, its price as the vendor publishes it, who it fits, and what it adds over the tier below. The 12-month cost projection follows.
| Plan | Price | Billing | Who it's for |
|---|---|---|---|
| Self-hosted | Free | — | Developers and privacy-focused hobbyists who already run Docker and are willing to supply their own hardware, maintain the stack, and pick their own LLM backend.Adds: Starting tier: free open-source software at $0, with no subscription or per-user fee — your cost is hardware plus maintenance time. |
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Where the pricing makes sense
The company stage and team size where Gpt Home's pricing actually pencils out — and where peers do it cheaper.
Gpt Home is free software at $0 with no subscription or per-user fee, which puts it below nearly every commercial assistant and below paid self-hosted stacks that charge per device or per user. The cost you actually bear is hardware plus your own maintenance hours, so a free cloud-tier smart speaker can still be cheaper for a household that just wants voice control. Against Home Assistant it is also free, but narrower — you are comparing a voice and agent layer to a full device-integration
Has Gpt Home's pricing changed?
No plan price for Gpt Home has moved since we began logging in Aug 2026; the pricing page is re-read on every verification pass.
Who should pick Gpt Home?
Pick Gpt Home if you are Privacy-focused hobbyists with spare hardware who want voice commands over their own devices, Developers learning LangGraph agent orchestration and LiteLLM model routing on a real project, Makers comfortable forking and maintaining an open-source Docker stack long term, Experimenters who want to swap LLM backends per request without changing the pipeline.
Look elsewhere if you are Users expecting plug-and-play setup like Alexa or Google Home, Anyone uncomfortable with Docker CLI, Compose, and Linux troubleshooting, Households that need vendor support, SLAs, or a guaranteed maintenance roadmap, Smart home owners who want a full device-integration platform out of the box.
Skip it if Skip Gpt Home if you want a smart home assistant that works out of the box without Docker, Linux troubleshooting, or maintaining a forked open-source project yourself.
GeneratedReal-world workflow fit
Concrete scenarios for the personas Gpt Home actually fits — and what changes day-one when you adopt it.
Pull the gpt-home-backend image, point LiteLLM at a local model, run gpt-home-frontend in a second container, and wire up a microphone and speaker on the Pi.
Outcome: Spoken commands control lights and smart devices with the audio and device state staying on your own network, and no monthly software fee.
Fork the repository, open the LangGraph agent graph, and modify the reasoning steps that turn a spoken request into a device action or a Spotify command.
Outcome: A working, physical-world example of a multi-step agent pipeline you can inspect and change, using the same LangGraph primitives as production agent code.
Deploy the optional gpt-home-spotify container alongside the backend so spoken requests route to Spotify playback.
Outcome: Music control becomes a separate, self-contained service you can update or remove without touching the voice and LLM backend.
Use cases
- Control lights and smart devices via voice commands using a local LLM
- Automate home tasks like reminders and weather queries
- Integrate with Spotify for music playback control
- Experiment with LangGraph-based multi-step agent workflows
- Run a mostly offline AI assistant on a Raspberry Pi 4-class host
Setup time & first value
How long it actually takes to get something useful out of Gpt Home — broken out by persona, not the marketing-page minute.
For a developer already comfortable with Docker Compose, expect a first working voice command within an afternoon once you use the current gpt-home-backend and gpt-home-frontend repositories rather than the deprecated monolith. For a hobbyist new to Linux and containers, budget a weekend: most of the time goes into host setup, audio device configuration, and choosing and running an LLM backend.
Switching to or from Gpt Home
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From judahpaul/gpt-home monolith: move to the split gpt-home-backend, gpt-home-frontend, and gpt-home-spotify images, since the original is marked [Deprecated].
- →From Amazon Alexa or Google Home: keep your existing devices, add Gpt Home as a self-hosted voice and agent layer in front of them.
- →From Home Assistant: run Gpt Home alongside it as the voice and LLM reasoning layer, leaving device integrations to Home Assistant.
- ↗To Home Assistant: keep your devices and voice hardware, and move the intent handling into Home Assistant automations with a cloud or local voice add-on.
- ↗To a commercial assistant: replace the self-hosted stack with an Alexa or Google Home device and accept cloud processing in exchange for zero maintenance.
Resources & guides
Tutorials & Learning
YouTube returned 6 videos for “Gpt Home”, and we withheld 6: 6 did not mention Gpt Home. We are showing none, because we could not prove any of them are about Gpt Home.
Official links
What are the best Gpt Home alternatives?
The closest alternatives to Gpt Home we list are LocalAI, Guaardvark and Olares. Ranked by direct product-type match, not category overlap.
| Alternative | Pricing | Starts at | Last verified |
|---|---|---|---|
| LocalAI | Free | Free | — |
| Guaardvark | Free | Free | — |
| Olares | Freemium | Pricing not published | — |
Alternatives to Gpt Home
View all
LocalAI
An MIT-licensed, self-hosted AI runtime that serves text, voice, vision, image, video, 3D and agent workloads behind an OpenAI-compatible API.
Guaardvark
Guaardvark is a free MIT-licensed self-hosted AI studio for local agents, video generation, voice and RAG on your own GPU.
Tools that pair well with Gpt Home
Common stack mates teams adopt alongside Gpt Home, with the specific reason each pairing earns its keep.
LocalAI
An MIT-licensed, self-hosted AI runtime that serves text, voice, vision, image, video, 3D and agent workloads behind an OpenAI-compatible API.
Guaardvark
Guaardvark is a free MIT-licensed self-hosted AI studio for local agents, video generation, voice and RAG on your own GPU.
Olares
Olares is an open-source personal AI cloud OS for running local LLMs, agents, and self-hosted apps on hardware you own.
Gpt Home vs its closest rival
Gpt Home's closest head-to-head is with Spider Cloud — For a privacy-centric smart home assistant with local LLMs, GPT Home offers a free but deprecated DIY solution for Raspberry Pi tinkerers. For AI agents and RAG pipelines needing fast, scalable web data, Spider Cloud is the clear winner with its powerful Rust engine, Browser AI commands, and freemium pricing. Choose based on whether your priority is offline home automation or high-volume web extraction. Verdict generated
Head-to-head comparisons
Gpt Home vs Spider Cloud
For a privacy-centric smart home assistant with local LLMs, GPT Home offers a free but deprecated DIY solution for Raspberry Pi tinkerers. For AI agents and RAG pipelines needing fast, scalable web data, Spider Cloud is the clear winner with its powerful Rust engine, Browser AI commands, and freemium pricing. Choose based on whether your priority is offline home automation or high-volume web extraction.
GeneratedGpt Home vs Temporal Ai
Choose Temporal AI if you need a battle-tested, durable execution platform for production AI agents or critical workflows, with cloud scalability and extensive SDK support. Choose Gpt Home only if you're a hobbyist who wants a free, self-hosted local LLM assistant on a Raspberry Pi with no support or active development.
GeneratedGpt Home vs Presto Voice
If you run a QSR chain and need a proven voice AI to boost drive-thru revenue, Presto Voice is the clear choice with up to 95% automation and measurable ROI. For a privacy-first, self-hosted home assistant on a Raspberry Pi, GPT-Home is a free open-source option—but it's now deprecated and requires technical proficiency. Choose based on your scale and technical appetite.
GeneratedFrequently asked questions
Best-of guides
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