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Continue is the better-documented choice for genuinely offline AI coding. Its setup guide describes installing the extension from a downloaded VSIX, disabling anonymous telemetry, and configuring a local model; Continue says that local-model setup can work without an internet connection. Cursor’s cited documentation describes AI features sending prompts and code context to model providers. Its Privacy Mode concerns data handling, not disconnected inference.

That is a conclusion about documented offline operation, not a claim that Continue writes better code. Local model quality, hardware demands, and feature support vary, and the available documentation does not establish a controlled code-quality or speed winner. If your requirement is simply to prevent training or limit retention, distinguish that policy from a strict no-network rule before choosing.

What does “offline” mean for an AI coding assistant?

It can mean several different things, and they are not interchangeable. For a strict offline requirement, the key question is whether prompts and code can be sent to a hosted service during use. Continue documents a local-model route intended to avoid that connection; Cursor’s cited privacy documentation says its AI features send prompts and code context to model providers.

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  • No internet during use: The editor’s AI must run against a model available locally or within a reachable private network. Continue documents an offline workflow when configured with local models.
  • No training on your code: This is a data-use condition, not proof that inference happens on your computer. Cursor Privacy Mode is described as preventing code from being used for training under its stated arrangements, while AI requests still go to providers.
  • No vendor retention: This concerns whether data is stored and for how long. It does not by itself establish that a request never leaves your environment.
  • Private-network hosting: A model may be hosted on a company server rather than a developer’s workstation. That can satisfy some network-boundary policies, but it is not necessarily disconnected use. The cited material does not specify a universal private-network deployment procedure for either product.

Write down which condition your team must meet. A policy that permits hosted inference under particular data controls is different from an air-gapped workstation that cannot make any external request.

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Which assistant is better for strict offline development?

Choose Continue when the requirement is to use AI without an internet connection, provided you have staged the required software and model files and selected a compatible local model. The official Continue documentation describes that path. The cited Cursor documentation does not document a fully offline AI mode.

This recommendation is narrow. It does not mean every Continue feature works offline with every model, or that Continue is categorically superior for normal connected coding. Continue’s own model guidance warns that local models can have limited tool-calling and reasoning capabilities, which can make agent mode challenging. The documentation reviewed here does not provide controlled comparisons of output quality, latency, or resource use.

Decision point Continue Cursor What it means for offline work
Documented disconnected AI use Setup guide describes installing the extension, disabling telemetry, and configuring a local model. Cited documentation describes AI requests sent to model providers; it does not document a fully offline AI path. Continue has the stronger documented case for no-internet use.
Where inference can run Supports local providers, including Ollama; local configuration is stored on the machine. AI features send prompts and code context to providers. Using an API key does not bypass Cursor’s backend. A privacy setting or API key is not the same as local inference.
Feature and model fit Documented roles include chat, edit, apply, autocomplete, embeddings, and reranking; support varies by provider and model. Documentation describes chat, agent, autocomplete, and cloud workflows using networked model requests. Check the particular role you need against the local provider and model.
Agent workflow Agent performance depends on local-model tool-use support; Continue warns that limitations can make agent mode challenging. Cursor documents Agent and separate Cloud Agents. Cloud Agents require repository access and temporarily store encrypted repository copies while running. Assess both tool capability and your organization’s code-storage boundary.
Preparation for a disconnected environment The guide describes downloading a VSIX, changing telemetry settings, and configuring a local model before use. The cited AI-feature documentation describes provider requests. For an air gap, stage all required artifacts before disconnecting; the cited Continue pages do not promise every dependency can be acquired offline.

How do you set up Continue to work without internet?

Complete installation and model setup while connected, then test the configuration with external networking disabled. Continue’s published workflow covers the extension, telemetry setting, local model configuration, and restart. A fully air-gapped deployment also requires planning for the model runtime and model files: the guide does not claim those can all be downloaded after disconnection.

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  1. Download the extension package while online. Get the latest Continue VSIX from Continue’s GitHub Releases. Keep the VSIX available on the machine or transfer it through your approved software-staging process.
  2. Install the VSIX in VS Code. Use VS Code’s extension installation workflow to install the downloaded VSIX rather than relying on the marketplace while disconnected. The exact interface can vary by VS Code version.
  3. Disable anonymous telemetry. In Continue’s user settings, turn off Allow Anonymous Telemetry. The documented reason is to prevent Continue from attempting its anonymous PostHog telemetry request.
  4. Prepare a local model provider. In config.yaml or through the Continue UI, select a local model/provider. Continue documents options including Ollama. If your environment will be air-gapped, arrange the provider runtime and model artifacts in advance.
  5. Restart VS Code. Continue’s guide instructs users to restart the IDE so configuration changes take effect.
  6. Test the actual boundary. Once the model and extension are ready, disconnect from the internet and verify the specific Continue functions your workflow depends on. Do not treat a successful online test as proof that the whole workflow is offline.

Only the first five steps are the documented setup workflow. Staging runtime and model files, then testing with networking removed, are prudent operational implications for an air-gapped environment; the cited pages do not certify every installation dependency or feature for every such setup.

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Which local models and Continue roles are documented?

Continue’s Ollama guide gives examples for three distinct jobs: Llama 3.1 8B for chat, Qwen2.5-Coder 1.5B for autocomplete, and Nomic Embed Text for embeddings. These are examples in that guide, not universal recommendations or guarantees of current quality.

Role Documented example Important qualification
Chat Llama 3.1 8B Example from Continue’s Ollama guide; suitability depends on model behavior and available hardware.
Autocomplete Qwen2.5-Coder 1.5B Example from the same guide; it does not establish that this is the best current autocomplete model.
Embeddings Nomic Embed Text Example for embeddings, a different role from generating chat or code completions.
Reranking No Ollama reranking model is offered in the cited Ollama guide. Reranking availability depends on provider; do not assume every local setup supports it.

Continue’s documented roles also include edit and apply. Model and provider support varies by role, so selecting a local model for one task does not establish that the same model—or provider—can supply every other task. Continue says local models need sufficient VRAM, but the cited documentation does not establish a one-size-fits-all GPU or computer requirement. Check the requirements for the particular model you intend to run.

What does Continue lose when it runs locally?

Local operation trades reliance on hosted services for dependence on the local model’s capabilities and the machine running it. Continue specifically cautions that local models may have limited tool-calling and reasoning, making agent mode challenging. That is a reason to test your own coding workflow, not a basis for assuming all local models fail at agent tasks.

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Think about the task before selecting a model:

  • Chat and explanation: Check whether the chosen model can handle the questions and code context your team uses.
  • Autocomplete: Confirm that your chosen provider and model support the autocomplete role you need.
  • Embeddings and retrieval: Configure an embedding model where required; a chat model alone does not establish that this role is covered.
  • Agent-style work: Test tool use and reasoning on representative tasks. Continue’s warning means you should not assume that local agent behavior will match another workflow.
  • Hardware fit: Confirm that the machine can run the selected model. The cited materials say sufficient VRAM is needed but do not specify a universal minimum.

For a team, success should mean more than “the model starts.” Validate each required role and the data boundary under the conditions developers will actually use. If an agent task fails because the model cannot reliably use tools, the offline setup may still be useful for chat or completion, but that is a narrower capability.

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Does Cursor Privacy Mode make Cursor work offline?

No. Cursor’s cited documentation says that when AI features are used, prompts and code context are sent to model providers. Privacy Mode is described as a data-use control, including preventing code from being used for training under its stated arrangements; it does not turn provider requests into local inference.

Cursor’s data-use overview adds two details relevant to security reviews: requests made using a user’s API key still go through Cursor’s backend for prompt building, and file contents may be temporarily cached. Therefore, an API key should not be described as a direct, offline connection from the editor to a model provider. Whether those arrangements meet a particular organization’s policy requires comparing the policy with Cursor’s current terms and documentation.

Cursor also describes Cloud Agents as a separate optional workflow. They require repository access over time, use isolated virtual machines, and temporarily store encrypted repository copies while an agent runs. If the policy prohibits code storage, do not enable Cloud Agents. This cloud workflow is distinct from local foreground editing, but it is not a fit for a no-code-storage rule.

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What should an air-gapped team prepare before disconnecting?

Do not assume “offline install” means every dependency will be available automatically. Continue’s guide describes downloading the VSIX and configuring a local model, but it does not promise that every runtime, model file, or supporting artifact can be fetched once the machine is disconnected.

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  • Stage the Continue VSIX from its GitHub Releases while connected.
  • Stage and verify the local provider/runtime and the model files required for your chosen roles.
  • Set Allow Anonymous Telemetry to off before disconnecting.
  • Configure the local provider in Continue’s UI or config.yaml, and restart VS Code.
  • Test the complete workflow with internet access disabled, including the specific model roles your team relies on.
  • Keep model and extension updates within your approved software-transfer process; the cited materials do not define an organization-wide air-gap update procedure.

This is an operational checklist derived from the documented install and configuration requirements, not a guarantee that a particular environment will work without further administration. Local inference also does not automatically prove that every part of a development environment is offline; assess the actual tools, dependencies, and network rules in your setup.

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Is Cursor’s OpenAI API-key option an offline alternative?

No. An API key changes how a request is authorized, not where the model runs or whether the request is networked. Cursor’s data-use documentation says API-key requests still pass through Cursor’s backend for prompt building, so that option does not meet a strict no-network requirement.

As of October 25, 2026, OpenAI’s Help Center says it is planning to wind down its contract providing models to Cursor and proposed November 12, 2026 as a transition date. The Help Center says that date is unconfirmed and Cursor may end access earlier. It also says users can use their own OpenAI API key for Cursor local Chat and Agent, but not for Cursor Tab, Auto, Cloud or Background Agents, Automations, the Cursor CLI, or Cursor API/SDK. This availability is time-sensitive; check the Help Center and Cursor’s current documentation before relying on it. Regardless of availability, an API-key request remains hosted inference rather than offline execution.

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How should you decide between them?

Start with the boundary your work must meet, then test the features you actually need. The products are not interchangeable on the narrow question of documented disconnected operation.

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  1. If no internet connection during AI use is mandatory: Prefer Continue’s documented local-model path. Plan to stage the extension, provider runtime, and model artifacts ahead of time.
  2. If hosted inference is allowed but training or retention is the concern: Evaluate Cursor’s Privacy Mode and data-use disclosures against your organization’s exact requirements. Do not treat those controls as offline operation.
  3. If you rely on agent workflows: Evaluate tool use, reasoning, repository access, and storage behavior separately. Continue warns about local-model tool and reasoning limits; Cursor Cloud Agents have repository access and temporary encrypted copies.
  4. If you need multiple AI roles: Confirm the selected Continue provider/model supports each role—chat, edit, apply, autocomplete, embeddings, or reranking—rather than inferring support from one working feature.
  5. If you need a procurement or performance verdict: The documentation cited here does not establish a controlled code-quality, speed, or hardware comparison. Run an internal evaluation with representative tasks and policy constraints.

Frequently Asked Questions

Can Continue use Ollama without an internet connection?

Continue’s Ollama guide documents Ollama as a local provider option, and Continue says its local-model configuration can support offline use. A disconnected machine still needs the provider runtime and model artifacts available locally.

Does turning off Continue telemetry disable its local AI features?

The offline setup instructions say to turn off “Allow Anonymous Telemetry” to prevent the anonymous PostHog request. They separately direct users to configure a local model, so telemetry control and inference configuration are distinct settings.

Can I use Cursor Tab with my own OpenAI API key?

As of October 25, 2026, OpenAI’s Help Center says its API-key option for Cursor does not cover Cursor Tab. Its stated supported and unsupported feature list is subject to change, so confirm current availability before building a workflow around it.

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Does local AI coding mean I do not need a GPU?

The cited Continue model guidance says local models need sufficient VRAM, but does not set a universal hardware minimum. The required resources depend on the model and machine, so verify the chosen model’s requirements rather than assuming a specific computer will suffice.

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