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1Repair Windows errors before they cause bigger problems2Fix the driver behind crashes, sound loss and screen glitches3Clear out junk files and repair common Windows errorsFor the strongest privacy boundary, run a local model through Ollama inside VS Code. Your notes can stay on the computer while you work, but you give up Copilot-powered semantic search, embeddings, and built-in inline suggestions when offline. Claude Code is the better fit for agentic work across files and tools, provided you accept a cloud-connected workflow governed by Anthropic’s account and retention policies. VS Code sits between those choices: it is an editor and interface that can use either hosted models or local providers.
The important distinction is not the brand on the window. It is the model endpoint: a hosted service receives note content over the network; a local runner performs inference on your device. The same VS Code installation can therefore be either cloud-dependent or largely offline, depending on the provider you select.
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Which option should you choose?
| Priority | Best fit | Why |
|---|---|---|
| Maximum control over note content | VS Code with Ollama and a local model | Ollama says locally processed prompts, responses, model interactions, and other content are not collected, stored, transmitted, or accessible to Ollama. |
| Agent that can work across files and tools | Claude Code | It is designed as an agentic interface, but its privacy and availability depend on Anthropic’s hosted service, account settings, and organization policy. |
| One editor that can switch between cloud and local models | VS Code | VS Code can connect to local providers and hosted services, letting you trade capability for privacy without changing editors. |
| Best offline writing and chat | VS Code with a local provider | Microsoft documents that locally hosted models work without a GitHub account, Copilot plan, or internet connection. |
| Cloud semantic search and embeddings | VS Code with Copilot services enabled | Copilot-backed indexing and semantic features are available when their online services are available; they do not function offline. |
Use the table as a starting point, then check how search, history, and retention affect your specific notes. A private local model can still be undermined by an extension that uploads files, while a cloud workflow can be made more appropriate for some teams through contractual and retention controls.
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What “private” means in this comparison
Privacy has several separate boundaries: where inference runs, whether prompts are retained, whether conversation history is synchronized, and what extensions or indexing services can read. Treating all four as one “AI privacy” setting leads to incorrect assumptions.
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Endpoint privacy comes first
If your model runs on a provider’s servers, note text must leave your machine to be processed. The provider’s terms, account type, deletion controls, and organizational policy then determine retention. If the model runs locally, inference can stay on the device, but local applications, plugins, crash reports, and optional telemetry remain possible data paths.
Claude Code and Anthropic retention
Anthropic’s Privacy Center (2026) says deleted consumer conversations disappear from history immediately and are deleted from backend systems within 30 days. If you allow chats or coding sessions to be used for model improvement, Anthropic may retain de-identified data for up to five years in its model-training pipelines.
Anthropic’s platform documentation separately states that local Claude Code session transcripts are stored for six years by default in compliance contexts, unless an organization configures a finite custom retention period. That is a platform and compliance statement, not a universal rule for every consumer account. Check the account and organization policy that actually handles your sessions.
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VS Code says Copilot sessions synchronize to GitHub by default so they can be accessed across devices and queried. To keep that history on the machine, set chat.sessionSync.enabled to false. VS Code also provides repository exclusions, which are useful when only selected projects must remain out of synchronized history.
Disabling synchronization changes where session history is stored; it does not make a hosted model local. If the selected model is a cloud service, the prompt still travels to that service while the request is processed.
Ollama’s local boundary
Ollama’s March 2026 privacy policy says it does not collect, store, transmit, or access prompts, responses, model interactions, or other content processed locally. The policy does allow limited device and usage metadata collection, and cloud-hosted models have separate handling. “Local” therefore describes the model execution path, not an automatic promise that every surrounding component is telemetry-free.
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How search differs between the three approaches
Claude Code: capable, but dependent on your indexing setup
Claude Code can work with files and connected tools, so its note-search experience depends on which tools, indexes, and permissions you provide. There is no single universal search behavior to assume: a small folder, a custom index, and an organization-managed environment can expose different capabilities and retention paths.
VS Code with Copilot services
When Copilot services are available, VS Code can use semantic search and embeddings to retrieve conceptually related passages instead of matching only exact words. This is useful for questions such as “What did I decide about the launch timeline?” when the note uses different wording.
The tradeoff is service dependence. VS Code documents that semantic search and embeddings tied to Copilot services are unavailable offline. Copilot-dependent inline suggestions are also unavailable without their online service, so a disconnected laptop does not retain the full cloud feature set.
VS Code with a local model
A local model can answer questions over notes without sending their contents to a hosted provider, but the quality of retrieval depends on your local tooling. You can use ordinary text search, a local index, or a retrieval-augmented workflow that creates embeddings on the device. VS Code’s Copilot semantic-search path is not available offline, and VS Code currently does not route a local model into its built-in inline-suggestions path.
For privacy-sensitive archives, separate retrieval from generation: keep the note index local, inspect which files are included, and send only the passages needed for an answer to the local model. This makes it easier to audit what the model saw.
Offline use: what still works and what does not
Claude Code
A hosted Claude Code workflow is network-dependent. If the machine cannot reach the service, requests that require Anthropic’s endpoint cannot run. Local files remain available in your editor or file system, but that is not the same as offline model inference.
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VS Code
VS Code can run local chat without a GitHub account, Copilot plan, or internet connection, according to Microsoft’s documentation. Offline operation applies to the local provider and model you have installed. Cloud chat, Copilot semantic search, embeddings, synchronized history, and Copilot-backed inline suggestions require their respective online services.
VS Code with Ollama
After the model has been downloaded and configured, Ollama can perform inference on the device. You still need hardware capable of running the chosen model, sufficient storage for model files, and a local search or indexing method if you want more than exact-text lookup. The available material does not establish one universal RAM, GPU, or disk requirement; those figures vary by model and quantization.
Setting up a privacy-first local note workflow
- Choose the boundary. Decide whether note content may reach a hosted provider. If the answer is no, select a local model endpoint before importing notes.
- Install a local runner and model. Install Ollama, download a model that your hardware can run, and verify that it responds while the computer is disconnected from the internet. The model download itself requires network access; subsequent inference can be local.
- Connect VS Code to the local provider. In VS Code’s chat model selection, choose the configured local provider rather than a Copilot-hosted model. Confirm the provider name before pasting sensitive text.
- Keep session history local. Open VS Code Settings, search for
chat.sessionSync.enabled, and set it tofalse. Add repository exclusions for projects that must not participate in synchronized history. - Limit the note scope. Open only the folders or files needed for a task. Review workspace and extension permissions, because a plugin can create a separate path for data even when inference is local.
- Add local retrieval if needed. Start with exact-text search for reliability. Add a local index or embedding workflow only after checking where its index files are stored and which process can read them.
- Test in airplane mode. Disconnect the network, reopen the workspace, run a local chat request, search a known note, and confirm that the features you depend on still operate. Expect cloud semantic search and Copilot inline suggestions to fail offline.
Do not treat a successful local chat response as proof that every feature is local. Verify the selected model, session-sync setting, index location, and extension behavior independently.
Using Claude Code’s interface with a local model
Ollama documents an ollama launch workflow that can configure Claude Code to use local models. This creates a hybrid arrangement: Claude Code remains the client and agent interface, Ollama is the local runner, and the model endpoint is on your device.
That arrangement is not Anthropic-hosted Claude running offline. The interface name does not identify the inference location. Before relying on the setup for confidential notes, confirm that the selected endpoint is the Ollama model, disable any history synchronization you do not want, and test with the network disconnected.
Feature and trade-off comparison
| Axis | Claude Code | VS Code with a cloud model | VS Code with Ollama and a local model |
|---|---|---|---|
| Privacy boundary | Anthropic account, retention controls, and organization policy apply. | Copilot or another hosted provider handles cloud features. | Content can remain on-device, subject to local telemetry and extensions. |
| Search | Depends on connected tools and indexing setup. | Strongest when Copilot semantic search and embeddings are enabled. | Local text or retrieval search is possible; Copilot semantic search is unavailable offline. |
| Offline completeness | Hosted workflow is network-dependent. | Cloud features stop offline; local providers can still chat. | Inference can work offline after installation; search quality depends on local tooling. |
| History | Anthropic retention and organization settings matter. | Copilot session sync is enabled by default but configurable. | Local files and runner logs remain under your control, subject to extensions and operating-system access. |
| Setup burden | Low initial setup, with continuing account and service dependence. | Moderate; convenient if you already use VS Code and Copilot. | Highest; model downloads, storage, compatible hardware, and local indexing may be required. |
What you give up when you go fully local
- Cloud semantic retrieval: Copilot embeddings and semantic search are unavailable while offline.
- Built-in inline suggestions: VS Code does not currently connect a local model to its built-in inline-suggestions path.
- Convenience: You must download models, maintain them, and ensure your computer can run the selected size.
- Some agent capabilities: A local model may be less capable for complex multi-step tasks than a hosted model, although quality depends heavily on the model and prompt.
- Automatic cross-device history: Turning off session synchronization intentionally removes the cloud copy that makes conversations available on other devices.
These are feature and operational trade-offs, not proof that local models are unusable. For journaling, meeting notes, drafts, and internal research that must stay on one laptop, local inference may be the more appropriate compromise.
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Vendor-reported efficiency claims: how to interpret them
Ollama publishes results for hybrid Minion and MinionS projects with Stanford Hazy Research. The 2025 figures report a 30.4× reduction in remote cost with 87% of cloud-model performance for one configuration, and a 5.7× reduction with 97.9% of cloud-model performance for another. These are vendor-reported project results, not a controlled benchmark of note-taking accuracy, privacy, latency, or battery life. They should not be used to predict how a particular laptop or note archive will perform.
Common failure modes and fixes
“I selected a local model, but the request still fails offline.”
Check that the model is downloaded locally, the runner is running, and VS Code is pointing to that provider rather than a cloud model. Disconnecting the network before testing helps reveal hidden service dependencies.
“My notes are private, but old chats appear on another device.”
Copilot session synchronization is enabled by default. Set chat.sessionSync.enabled to false and review repository exclusions. Existing copies already synchronized to GitHub require separate account-level handling.
“Local chat works, but semantic search does not.”
This is expected when you rely on Copilot’s online embeddings or semantic-search service. Use exact-text search or install a local indexing and embedding workflow whose storage and permissions you can inspect.
“Claude Code looks local because it is connected to Ollama.”
Check the endpoint, not the interface label. Claude Code can act as the client while Ollama supplies the local model. Anthropic-hosted inference is a different path and remains network-dependent.
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“A local setup still exposes data.”
Audit extensions, workspace automation, crash reporting, synchronization, and backup software. Ollama’s local policy addresses content processed locally by Ollama; it does not override the policies of other programs on the computer.
A practical decision framework
- Classify the notes. If disclosure to a hosted provider is unacceptable, rule out cloud inference for those files.
- Identify the must-have search behavior. If conceptual retrieval across a large archive is essential and internet access is acceptable, a hosted semantic-search workflow is simpler. If the archive must remain offline, plan for local indexing.
- Separate editing from inference. VS Code can remain your editor even when you switch between a cloud model for non-sensitive drafts and a local model for confidential notes.
- Set history policy deliberately. Decide whether cross-device conversation access is worth synchronized copies. Do not leave the default unchanged by accident.
- Run an offline acceptance test. Confirm that the exact tasks you perform—chat, retrieval, file edits, and history review—work without a network before calling the workflow offline.
Bottom line
Choose VS Code with Ollama when keeping note content on your hardware is the deciding requirement and you can accept the setup work and weaker offline feature coverage. Choose Claude Code when an agent that operates across files and tools matters more than a strict local boundary, and configure Anthropic retention and organization controls carefully. Choose VS Code with a hosted model when semantic search, embeddings, and convenience outweigh the need to keep prompts off provider servers.
Remember the four-part vocabulary: client/interface (Claude Code), editor (VS Code), runner (Ollama), and model endpoint (local or cloud). Once those roles are separated, privacy, search, and offline behavior become settings you can verify instead of assumptions based on product names.
Frequently Asked Questions
Can a local model provide semantic search without an internet connection?
Yes, but not through VS Code’s Copilot-backed semantic-search and embedding service. You need a local text index or local embedding and retrieval workflow, and its quality and storage behavior depend on the tools and model you choose.
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Does disabling VS Code session sync stop cloud inference?
No. The setting keeps Copilot session history from synchronizing to GitHub; it does not change where a hosted model processes the prompt.
Are Ollama’s cloud-hosted models covered by its local privacy statement?
No. Ollama distinguishes locally processed content from cloud-hosted models, which have separate handling.
Can I use Claude Code with Ollama and still call it offline Claude?
You can use the Claude Code interface with an Ollama local model through Ollama’s documented launch workflow, but Anthropic-hosted Claude inference is not running offline in that arrangement.
What hardware is required for a local note-taking model?
The available specifications are model-dependent. You need enough storage for the downloaded model and hardware capable of running its size and quantization; no single universal RAM or GPU requirement applies.
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