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Duck.ai is the best private ChatGPT alternative for most people who want a hosted service. DuckDuckGo says chats are not saved by default, prompts are not used to train models, and personal metadata such as your IP address is removed before a request reaches the model provider. Proton Lumo is a strong hosted choice for users who prefer Proton’s European infrastructure and zero-access encryption claims. If prompts must stay on your own machine, Ollama or LM Studio are the better path—but they require compatible hardware, downloaded models, and more maintenance.
No assistant is simply “private” or “not private.” You need to examine retention, training use, metadata, provider access, jurisdiction, account requirements, and whether files or voice data are handled differently from ordinary text chats.
Quick comparison
| Option | Where prompts are processed | Retention and training position | Identity and metadata | Convenience | Main trade-off |
|---|---|---|---|---|---|
| Duck.ai | Hosted model providers, reached through DuckDuckGo | No chat storage by default; DuckDuckGo and underlying providers say conversations are not used for training; providers agree to immediate deletion after reply generation, subject to documented exceptions | DuckDuckGo says personal metadata, including IP address, is removed before provider transmission; account requirements are not established in the available policy material | Highest among the privacy-oriented options | Still requires hosted processing, and provider exceptions and model availability can change |
| Proton Lumo | Proton-hosted European infrastructure | TechRadar reports zero-access encryption, no server logs, and no training on user data unless the user opts in | European infrastructure is described as operating under GDPR and Swiss privacy laws; current Proton documentation should be checked for exact exceptions | Hosted and straightforward | Several key claims are secondary-source claims rather than the primary Proton documentation |
| Ollama | Your computer when using locally downloaded models | Prompts can remain local; retention depends on your operating system, applications, backups, and any optional cloud connection | No model provider needs to receive a prompt for a genuinely local session; local network and account settings still matter | Moderate after setup | Hardware, storage, model downloads, updates, and troubleshooting are your responsibility |
| LM Studio | Your computer when running a local model | Local processing can avoid hosted prompt retention and training; your own device and backup policies become the privacy boundary | Provider-side metadata is avoided for local inference, but optional online features may have different handling | Moderate after setup | Performance and model quality depend on your computer and the model you select |
File-upload, image, and voice behavior is not established consistently for these choices in the available policy material. Treat each capability as a separate privacy decision and read the current product documentation before uploading sensitive material.
What “private AI assistant” actually means
Privacy has several independent dimensions. A service can hide your IP address while retaining your prompt, or promise deletion while still receiving identifying metadata. Evaluate each dimension instead of relying on a marketing label.
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Retention
Retention asks whether the service keeps your prompts, generated answers, uploaded files, voice recordings, safety logs, or account history. “No chat history” in an interface does not automatically prove that backend systems never create short-lived logs or abuse-prevention records. Look for the service’s definition of deletion and the time at which it occurs.
Training use
A provider may store data without using it to train a model, or train on data only after an opt-in. Check whether the rule applies to all products, human review, uploaded files, voice transcripts, and third-party model providers. A setting that disables training is not the same as a guarantee that the prompt is never retained.
Metadata and provider access
Even when the text is not stored, a model provider may receive an IP address, account identifier, device information, timestamps, or other routing metadata. Privacy-focused services may remove some of that information before forwarding a prompt, but the model still has to process the prompt to produce a reply.
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Where a company and its infrastructure operate affects applicable law and lawful-access procedures. Jurisdiction does not replace a retention policy: a service in a privacy-friendly jurisdiction can still keep data, while a service elsewhere may delete it quickly. Read exceptions covering legal orders, abuse prevention, caching, moderation, outages, and security investigations.
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Network privacy versus provider privacy
A VPN can hide your destination and IP address from your internet provider and can make your connection appear to originate elsewhere. It does not hide the prompt from the AI service that receives it. Once the request reaches ChatGPT, Gemini, Duck.ai, Lumo, or another provider, that service can process the content under its own policies.
Duck.ai: the easiest hosted private alternative
Duck.ai has the clearest first-party privacy position among the hosted options covered here. DuckDuckGo’s help material says that, by default, Duck.ai does not record or store chats, and conversations are not used to train chat models by DuckDuckGo or the underlying model providers. DuckDuckGo also says that personal metadata, including IP addresses, is removed before prompts are sent to model providers.
How provider deletion works
DuckDuckGo says all Duck.ai model providers agree to delete prompts and responses immediately after generating a reply, a practice it calls Zero Data Retention. “Immediately” applies to the normal response-generation flow; the policy also documents exceptions. Those exceptions matter more than the headline, so read the current Duck.ai help and privacy pages before relying on the service for regulated, confidential, or legally sensitive work.
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What Duck.ai is good for
- Everyday questions where you want a hosted interface without a conventional saved chat history.
- Trying different supported models without opening separate accounts with every model company.
- Reducing the amount of identifying network metadata sent to downstream model providers.
- Users who want privacy defaults without maintaining a local AI installation.
Limitations to check
- The available model roster can change, so a model you rely on today may later be replaced or removed.
- Provider exceptions, safety processing, caching, moderation, and legally required retention can differ from the normal deletion path.
- The available material does not establish a universal account or identity requirement; check the current sign-in flow for your region and device.
- Do not assume that file, image, or voice inputs receive exactly the same treatment as text prompts.
Duck.ai privacy checklist
- Open the current Duck.ai privacy and help documentation from the service itself.
- Confirm the default retention and training settings shown for your account or session.
- Read the provider exception language, including abuse prevention, legal requests, and moderation.
- Use the least identifying information needed in the prompt, even when metadata stripping is enabled.
- Remove names, account numbers, customer records, and secrets before uploading documents.
DuckDuckGo’s privacy policy was updated on June 3, 2026. That date identifies the policy version, not a performance or usage statistic; recheck the wording whenever the product, model roster, or provider list changes.
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Proton Lumo: a privacy-first hosted service
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 coverage describes Lumo as running on European infrastructure under GDPR and Swiss privacy laws. These are useful signals for people already comfortable with Proton’s privacy model, but they are secondary-source claims. Verify the current Proton documentation for retention, encryption scope, account data, file handling, and exceptions before making Lumo your confidential-work assistant.
Why choose Lumo
- You want a conventional hosted chat experience rather than a local installation.
- European and Swiss legal protections are important to your organization’s risk assessment.
- You prefer a provider that presents encryption and data minimization as core product features.
- You are willing to opt out of any optional data-use setting and review future policy changes.
Questions to answer before using it for sensitive work
- Does “zero-access encryption” cover active prompt processing, stored conversations, attachments, and backups, or only particular stored data?
- What operational logs exist for security, abuse prevention, billing, and account administration?
- What happens to prompts and files when a response is blocked, flagged, or sent for moderation?
- Which features require a Proton account, and what account metadata is linked to activity?
- Are optional cloud, browsing, sharing, or voice features governed by different terms?
Because the available Lumo evidence comes from TechRadar rather than a quoted Proton policy page, treat the service as promising rather than automatically equivalent to Duck.ai’s directly stated defaults.
Ollama and LM Studio: run an AI assistant offline
Ollama and LM Studio are local options for readers asking, “Can I run an AI assistant offline?” When a compatible model is downloaded and inference is performed locally, the prompt can remain on your computer instead of being sent to ChatGPT, Gemini, Claude, or another hosted model provider. This is the strongest way to keep data within a device boundary, but it transfers responsibility from a service provider to you.
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- Prompt text does not need to cross the internet for local inference.
- A hosted model provider cannot retain or train on a prompt it never receives.
- Your organization can apply its own access controls, encryption, retention, and deletion policies.
- Offline use can continue during an internet outage once the model and application are installed.
What local operation does not solve automatically
- Your operating system, application logs, crash reports, clipboard history, backups, and cloud-sync tools may still expose prompts.
- Anyone with access to the computer may be able to read chat files or model directories.
- Downloading a model requires network access, and optional extensions or cloud features may send data online.
- Local models can produce inaccurate, outdated, or less capable answers than the largest hosted systems.
- Model files consume storage, and updates, compatibility fixes, and security maintenance are your responsibility.
Choosing between Ollama and LM Studio
Both are named as local options, so the privacy boundary is similar when each is configured for local inference. Choose based on the interface and workflow you prefer, the models supported by your hardware, and whether you need a graphical application or a developer-oriented local runtime. The available evidence does not establish a universal performance winner, model-quality ranking, or feature parity between them.
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A safe local setup sequence
- Check whether your computer has enough system memory, graphics memory, storage, and cooling for the model size you intend to run.
- Install Ollama or LM Studio from the developer’s current distribution and review network permissions during installation.
- Download a model from a source you trust; record its name and version so you can reproduce or remove the setup later.
- Disable optional cloud, telemetry, synchronization, or remote-access features unless you have a specific reason to use them.
- Test with non-sensitive prompts while monitoring whether the application creates local logs or makes outbound connections.
- Protect the computer with an account password, disk encryption, operating-system updates, and controlled backups.
- Set a retention rule for local chat files and delete them securely when they are no longer needed.
“Offline” describes the inference path, not every action performed by the application. A local assistant is only as private as the machine, network settings, downloaded software, and people who can access it.
Hosted privacy services versus local assistants
| Decision factor | Hosted Duck.ai or Lumo | Local Ollama or LM Studio |
|---|---|---|
| Initial effort | Open a web or app interface and review settings | Install software, select a model, and configure the computer |
| Data locality | Prompt is processed by the hosted service and its model provider | Prompt can remain on the device during local inference |
| Maintenance | Provider maintains servers and models; policies can change | You maintain software, models, storage, security, and updates |
| Model access | Convenient access to the provider’s available roster | Choice depends on compatible downloadable models |
| Hardware burden | Mostly shifted to the provider | Paid by your computer’s memory, graphics capability, storage, and electricity |
| Legal and jurisdictional review | Must assess the provider, subprocessors, and applicable law | Primarily your own organization’s policies and jurisdiction, plus any online features |
Hosted services win on convenience and often on the breadth of available models. Local tools win on data locality and control. Neither category is universally safer: a neglected local laptop can leak more than a well-run hosted service with short retention, while a hosted service remains able to process your prompt and may have legal or operational exceptions.
What about ChatGPT, Claude, and Gemini?
Popular assistants should be evaluated by their current product and account settings rather than by brand reputation. Google’s Gemini Apps Privacy Hub says Gemini processing is governed by Google’s privacy policy and covers content generated through Gemini Apps. TechRadar’s analysis notes that mainstream assistants may read, store, and learn from prompts depending on settings.
For any mainstream assistant, inspect the controls for chat history, model-improvement use, human review, temporary chats, shared links, connected applications, uploaded files, and voice recordings. A privacy setting may apply to one product tier or account type but not to an API, business workspace, mobile app, or third-party integration. Record the setting you selected and revisit it after major product updates.
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Can a VPN hide your prompts from ChatGPT?
No. A VPN is useful for hiding your network location and reducing what your internet provider can see about the connection. It does not conceal the prompt from ChatGPT or another AI service after that service receives the request. The AI provider can still process the text, files, and generated response under its own retention, training, moderation, and legal policies.
Use a VPN for network-security reasons, such as protecting traffic on an untrusted Wi-Fi network or limiting IP-address visibility. Do not treat it as a substitute for disabling chat retention, removing identifying details, choosing a no-training setting, or running a model locally.
How to choose the right alternative
Choose Duck.ai when convenience matters most
Pick Duck.ai if you want a hosted, general-purpose assistant with clearly stated defaults against chat storage and training, plus metadata reduction before provider calls. It is the practical starting point for most people replacing ChatGPT for ordinary, non-confidential questions.
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Pick Lumo if European infrastructure, GDPR and Swiss-law considerations, and Proton’s privacy positioning are important. Confirm the primary Proton documentation first, especially if you will upload documents or enable optional features.
Choose a local tool when prompts must stay on your machine
Pick Ollama or LM Studio when your threat model does not permit hosted prompt processing, or when offline operation is a requirement. Budget for hardware, model storage, maintenance, access control, and the possibility that local quality and speed will not match a large hosted model.
Use a mainstream assistant when its controls satisfy your policy
A mainstream service can still be appropriate for low-risk work when its current account, workspace, and training settings meet your requirements. Document those settings rather than assuming that a paid plan, a VPN, or a “temporary” interface automatically prevents retention.
Quick Recap
Privacy checklist for every AI assistant
- Identify exactly what is sent: prompt text, files, images, audio, account identifiers, IP address, and device metadata.
- Find the retention period for chats, attachments, safety logs, backups, and blocked requests.
- Confirm whether data is used for model training, human review, evaluation, or abuse detection.
- Read the exceptions for legal demands, security incidents, moderation, caching, and service providers.
- Check whether the policy differs by country, plan, app, API, business workspace, or age group.
- Remove names, secrets, credentials, health details, financial information, and customer identifiers before sending a prompt.
- Separate ordinary questions from regulated or confidential work; use a local model when the data cannot leave the device.
- Review settings after product updates because model rosters, providers, and privacy terms can change.
Product prices and availability are accurate as of the date/time indicated and are subject to change. Any price and availability information displayed on Amazon at the time of purchase will apply.
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