Duck.ai is the best hosted private ChatGPT alternative for most people. DuckDuckGo says chats are not recorded or stored by default, prompts are not used to train the models, and personal metadata such as your IP address is removed before a request reaches a model provider. If you need maximum data locality instead of convenience, run a model locally with Ollama or LM Studio. Proton Lumo is another hosted privacy-first option, but the strongest claims currently available for it come from secondary reporting and should be checked against Proton’s latest documentation.
There is no single definition of “private.” Retention, training use, metadata, provider access, jurisdiction, account identity, and support for files or voice all affect the answer. The comparison below separates those dimensions so you can choose an AI assistant that fits your threat model rather than relying on a privacy label.
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What makes an AI assistant private?
When you send a prompt to a hosted assistant, the text leaves your device and is processed by at least one remote service. Privacy therefore depends on several separate questions:
- Retention: Does the service keep chats, prompts, responses, logs, backups, or cached copies?
- Training: Can your conversations be used to improve a model, either by default or after an opt-in?
- Metadata: Does the provider receive your IP address, account identity, device details, location, or timestamps along with the prompt?
- Human and automated access: Can staff, contractors, safety systems, or file-moderation systems inspect content?
- Jurisdiction: Which company and legal regime can compel access or govern data handling?
- Locality: Can inference happen entirely on your computer, without a cloud request?
A VPN addresses only part of this list. It can conceal your network location and reduce what your internet provider sees, but the AI service still receives the prompt itself. As TechRadar puts it, “A VPN is great at hiding where you are and what your internet provider sees.” It does not make a hosted assistant unable to read, store, or process the text you submit.
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Best private alternatives at a glance
| Option | Where processing occurs | Chat retention | Training use | Metadata and identity | Model choice | Convenience | Main trade-off |
|---|---|---|---|---|---|---|---|
| Duck.ai | Hosted model providers, reached through DuckDuckGo | DuckDuckGo says chats are not recorded or stored by default; providers agree to delete prompts and responses immediately after generating a reply, subject to documented exceptions | DuckDuckGo says conversations are not used to train models by DuckDuckGo or the underlying providers | DuckDuckGo says personal metadata, including IP addresses, is removed before prompts are sent to providers; account requirement is not stated in the cited material | Multiple providers are available, but the current roster can change | Highest among the privacy-oriented choices | It is still a hosted service, and provider exceptions and model availability can change |
| Proton Lumo | Hosted infrastructure in Europe, according to secondary reporting | TechRadar reports that Lumo keeps no logs on its servers | TechRadar reports no training on user data unless the user opts in | Specific metadata and account requirements are not established in the cited material | Not stated; verify the current model lineup | Hosted and convenient | The privacy claims summarized here are secondary-source claims; confirm current Proton documentation |
| Ollama | Locally on your computer when used with local models | Prompts can remain on the computer; local file, operating-system, and backup logs are your responsibility | No cloud provider receives a prompt during local inference, but model downloads and optional integrations can create network activity | No model-provider metadata is required for local inference; your own computer may still record activity | Open-source model selection depends on compatible hardware and the models you install | Lower; installation, model management, and updates are your responsibility | Hardware requirements and maintenance replace the convenience of a hosted service |
| LM Studio | Locally on your computer when using downloaded local models | Prompts can remain on the computer; local storage and backups must be secured by you | No cloud provider receives a prompt during local inference, unless you deliberately use a cloud-connected feature | No provider identity is needed for local inference; operating-system telemetry and optional services remain separate considerations | Depends on the models and hardware you select | Lower than a hosted assistant, but its graphical interface can simplify local model management | Performance, storage, RAM, and GPU capability determine the experience |
The table reflects the claims and limits documented for these options. File upload, voice, exact account rules, model quality, and current model rosters are not consistently established for every candidate, so check the service’s current settings before moving sensitive work.
1. Duck.ai: the easiest hosted privacy-first choice
Duck.ai is the strongest all-round recommendation when you want a web-based assistant without making local hardware your problem. DuckDuckGo’s help material says that, by default, Duck.ai does not record or store chats and that conversations are not used to train chat models by DuckDuckGo or the underlying model providers. DuckDuckGo’s privacy policy also says: “We don’t save or share your search, chat, or browsing history when you search on DuckDuckGo, chat on Duck.ai, or use our apps and extensions.”
How Duck.ai handles a prompt
- You enter a prompt in the Duck.ai interface.
- DuckDuckGo removes personal metadata such as your IP address before sending the request to an underlying model provider, according to its help documentation.
- The provider generates a response. DuckDuckGo says providers agree to delete prompts and responses immediately after generating that response, a practice it calls Zero Data Retention (ZDR).
- The answer returns through Duck.ai without DuckDuckGo retaining a default chat history.
This design separates the interface from the model companies. It does not mean that no system ever processes your text: a provider must still process the prompt long enough to generate a reply, and the policy describes exceptions. Treat “not stored by default” and “immediate deletion” as specific commitments with boundaries, not as a guarantee that content is invisible during processing.
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Exceptions and checks
Duck.ai’s provider agreements include exceptions, and the model roster and terms can change. Before using it for confidential material, read the current help and privacy pages for language covering abuse prevention, legal obligations, safety review, caching, outages, and uploaded files. If a business, school, or regulated workflow requires a written retention commitment, keep a copy of the applicable policy and its date. The DuckDuckGo privacy-policy update date captured here is June 3, 2026; that date describes the policy version, not a usage or security statistic.
When Duck.ai is the right fit
- You want an anonymous AI chat experience with minimal setup.
- You prefer a hosted assistant but do not want default chat history or model training on your conversations.
- You can tolerate provider-side processing and policy exceptions.
- You want to switch among available models without installing and maintaining them yourself.
2. Proton Lumo: a hosted option with European privacy positioning
TechRadar reports that Proton Lumo uses zero-access encryption, keeps no logs on its servers, and does not train on user data unless the user opts in. The same reporting places its infrastructure in Europe and associates the service with GDPR and Swiss privacy laws.
Those are useful signals for readers who care about jurisdiction and encrypted storage, but they are secondary-source claims rather than first-party documentation in the material available for this guide. Confirm Proton’s current privacy notice, terms, data-processing details, account requirements, and model-provider arrangements before treating Lumo as suitable for sensitive or regulated information.
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Questions to answer before adopting Lumo
- Does the current plan retain prompts, responses, attachments, or diagnostic logs?
- What does “zero-access encryption” cover, and can the service decrypt content for abuse prevention, support, or file moderation?
- Is model training disabled by default, and what exactly happens if a user opts in?
- Which entities process prompts, where are they located, and what legal exceptions apply?
- Are voice, file, and image features governed by the same retention rules as text chat?
Lumo is most attractive when you want a conventional hosted interface and place meaningful weight on European and Swiss legal context, but you should not infer that jurisdiction alone prevents provider access or compulsory disclosure.
3. Ollama and LM Studio: run an AI assistant offline
If your priority is keeping prompts on your own computer, local inference is the clearest route. Ollama and LM Studio are canonical local options: you download the application and one or more compatible open-source models, then generate responses on your machine instead of sending each prompt to a hosted model provider.
What local operation protects
- Prompts and responses can remain on the computer during inference.
- No remote model provider needs to receive your text for a purely local session.
- You choose which model files to install and can disconnect the computer from the internet after downloading them.
What local operation does not protect automatically
- Your operating system, backups, browser history, crash reports, and screen-sharing tools may still expose content.
- A model download, update check, plug-in, or cloud-connected feature can create network traffic.
- Anyone with access to the computer or its unencrypted storage may be able to read local chats.
- Model files and applications require updates, and you are responsible for checking their provenance.
Ollama versus LM Studio
Choose Ollama when you prefer a lightweight local runtime that can be integrated into other applications. Choose LM Studio when a graphical interface for downloading and switching among local models is more important. Neither choice guarantees a particular response quality: results depend on the model, quantization, available memory, processor, graphics hardware, and the task.
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Local assistants also trade convenience for control. You must estimate storage, install model files, monitor temperature and memory use, update the runtime, and troubleshoot slow or failed generations. A local model may be less capable than the largest hosted systems, especially for complex reasoning, long context, multimodal input, or current information, but it can be the right answer when data locality outranks convenience.
A privacy-conscious local setup
- Install Ollama or LM Studio from the vendor’s current official distribution.
- Download a model whose license and source you understand; downloading is the point at which network activity is expected.
- Run a simple test prompt while monitoring whether the application offers a cloud or remote-provider mode.
- Disable optional telemetry, automatic sharing, plug-ins, and cloud features unless you explicitly need them.
- Store chat histories, model files, and exports on encrypted storage with access controls appropriate to the material.
- Keep the runtime and model files updated, but review release notes and privacy settings after each update.
Hosted convenience versus local control
| Reader priority | Best starting point | Why | What to give up |
|---|---|---|---|
| Fast setup and a browser-based workflow | Duck.ai | Clear first-party statements on default chat storage, training, metadata removal, and provider deletion | Some provider-side processing and changing exception language |
| Hosted service with European and Swiss privacy positioning | Proton Lumo | Reported zero-access encryption, no server logs, and opt-in training | Claims require confirmation in current Proton documentation |
| Prompts must stay on a controlled computer | Ollama or LM Studio | Local inference keeps prompt traffic away from cloud model providers | Hardware cost, setup, maintenance, and potentially lower capability |
| Frequent file or voice use | Verify each service feature-by-feature | Support and retention rules are not established consistently across these options | You may need separate tools or a less private workflow |
Can a VPN hide your prompts from ChatGPT?
No. A VPN can hide your IP address and destination details from your internet provider and can make the AI service see the VPN server’s address instead of your home address. It does not hide the prompt from the AI service, because the service must receive and process that prompt to answer it. A VPN therefore complements, rather than replaces, a no-retention policy, metadata minimization, or local inference.
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If your concern is network surveillance, use a reputable VPN and HTTPS. If your concern is the AI provider learning from confidential text, address provider retention and training controls—or use a local model. These are different threat models.
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How to choose an AI assistant for your threat model
Choose a hosted service when
- You need the best available convenience and do not want to manage model files.
- Your prompts are low or moderate sensitivity and you can accept documented provider processing.
- You value a simple interface, model switching, or access from multiple devices.
Choose local inference when
- Prompts contain trade secrets, private records, unpublished work, or other material that cannot leave your device.
- You can provide suitable hardware and are willing to maintain software and storage.
- You can accept that model quality, speed, and features vary by local model.
Use a two-tier workflow when
Many people can use Duck.ai or another hosted option for public facts and brainstorming while reserving Ollama or LM Studio for confidential drafts. Keep the boundary explicit: remove names, identifiers, credentials, and proprietary details before sending anything to a hosted service, and do not assume that a VPN makes redaction unnecessary.
Privacy checklist before sending a sensitive prompt
- Remove names, email addresses, customer numbers, access tokens, exact locations, and unnecessary dates.
- Check whether chat history is enabled and whether a training opt-in is present.
- Read the current retention and exception language, including abuse prevention, legal retention, caching, and file moderation.
- Confirm whether attachments and voice recordings follow the same rules as text prompts.
- Determine which company and jurisdiction process the request.
- For high-sensitivity material, use a local model and secure the computer, backups, and exports.
- Recheck settings after major product updates; privacy defaults and available model providers can change.
Bottom line for replacing ChatGPT, Claude, or Gemini
For an easy hosted replacement, start with Duck.ai because its first-party statements directly address the privacy questions that matter most: default chat storage, model training, IP and metadata removal, and provider deletion. Proton Lumo is worth evaluating if its reported encryption, no-log design, opt-in training, and European infrastructure match your needs, but verify those claims in current Proton documentation. If “private” means that prompts never leave your computer, neither hosted option is enough: use Ollama or LM Studio, accept the hardware and maintenance burden, and secure the local system as carefully as the model itself.
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