Continue is an open-source AI coding assistant that operates as an extension for VS Code and JetBrains IDEs, giving developers a fully customizable AI coding workflow without any vendor lock-in. Unlike proprietary tools that bundle a specific model with a fixed feature set, Continue is model-agnostic — you connect it to any LLM provider you choose, whether that is Anthropic's Claude API, OpenAI, local models running through Ollama, or enterprise deployments of open-weight models like Llama or Mistral. This flexibility makes Continue the go-to choice for developers and teams who want the benefits of AI coding assistance on their own terms.
Key Features#
Bring-Your-Own-Model Architecture
Continue's defining characteristic is its model-agnostic design. The config.json file lets you configure one or more model providers with full control over model selection, API endpoint, API key, and temperature. You can run Claude 3.5 Sonnet for complex reasoning, use a local Ollama-served CodeLlama model for completions to keep data on-premise, and switch between them in the IDE sidebar with a single click.
Custom Context Providers
Continue's context system lets developers attach specific sources of information to their AI prompts beyond just the current file. Built-in context providers include @codebase for full codebase search, @docs for documentation sites, @terminal for recent shell output, @git-diff for current changes, and @problems for IDE diagnostics. Third-party context providers can be written and shared as TypeScript modules.
Slash Commands and Custom Actions
Continue supports a slash command system that lets teams define reusable AI workflows. Built-in commands include /edit for inline code modification, /comment for documentation generation, /test for unit test creation, and /share for exporting conversation context. Teams can write custom slash commands in TypeScript to build organization-specific AI workflows that run against selected code.
Inline Editing and Chat Like its commercial counterparts, Continue provides both an inline editing mode where AI suggestions appear in-place within the editor and a chat sidebar for conversational interaction. The inline editing workflow is particularly clean — you select code, describe the change, and Continue modifies the selection while showing a diff you can accept or reject.
Pricing#
Continue is entirely free as an open-source tool — there is no subscription, no usage limit, and no feature gate. All features are available in the open-source version. Your only costs are the API usage fees of the model provider you connect. Using a local model via Ollama incurs zero ongoing cost. Using Claude or GPT-4o incurs normal API usage charges from Anthropic or OpenAI. Continue also offers a Continue Hub where the team provides managed model access and shared context configurations for teams, with pricing available on request.
Who It's For#
- Privacy-first engineering teams: Teams in regulated industries such as finance, healthcare, or government where sending code to external APIs is prohibited can use Continue with fully local models to get AI assistance without any data leaving their infrastructure.
- Developers who want full customization: Engineers who want to tune every aspect of their AI coding environment — model, context, commands, temperature, system prompt — rather than accepting a vendor's defaults will find Continue uniquely flexible.
- Cost-conscious developers: Individual developers and startups who want AI coding assistance without a monthly subscription can self-select a cost-effective model provider or use free local models entirely.
Strengths#
True data privacy with local models. No other mainstream AI coding assistant supports fully local inference as cleanly as Continue. The combination of Continue with Ollama and an open-weight model like CodeLlama or DeepSeek Coder gives developers powerful AI assistance with zero code ever leaving their machine.
Community and extensibility. Continue's open-source nature means it has an active community contributing context providers, slash commands, and integrations. The extension ecosystem is growing rapidly, and developers can contribute features that benefit the entire community rather than waiting for a vendor roadmap.
No vendor lock-in. Switching from Claude to GPT-4o to a local model is a one-line configuration change. Teams are never dependent on a single provider's pricing, availability, or policy decisions — a meaningful advantage as the AI model landscape continues to evolve.
Limitations#
Setup and configuration overhead. Getting the most out of Continue requires more initial configuration than plug-and-play tools like GitHub Copilot. Configuring multiple model providers, setting up local model serving, and authoring custom context providers has a learning curve.
Less polished enterprise experience. Continue lacks the SSO, audit logging, centralized policy management, and dedicated enterprise support that commercial tools offer at their enterprise tiers. Organizations with compliance requirements may need to supplement Continue with additional tooling.
Related Resources#
Browse the full AI Agent Tools Directory to explore the full range of AI coding tools, from open-source to enterprise.
- Best AI Coding Agents Compared — see how Continue compares to Cursor, Copilot, and Cody on features, pricing, and use cases
- What is an AI Agent — foundational concepts behind the AI agents powering tools like Continue
- Tool Use in AI Agents — how AI agents use external tools and context providers to understand code
- Build a Coding Agent Tutorial — learn to build your own AI coding agent from scratch
- AI Agents for Engineering Teams — deployment strategies for AI coding assistants across engineering organizations
- OpenAI Agents SDK vs LangChain — compare orchestration frameworks relevant to building custom Continue extensions