Continue vs Sourcegraph: Which Is Better in 2026?

Continue is an open-source AI code assistant for VS Code and JetBrains that brings customizable, model-flexible AI help right into the editors developers already use. Rather than locking you into one closed platform, Continue lets you configure exactly which models you want to use — including your own keys and even local models — giving you control, flexibility and freedom from vendor lock-in while you get AI completion, chat and assistance inside your normal workflow.

Its strengths are openness and configurability. As an open-source project, it is transparent, community-driven and free, and its flexibility around models means you can tune it to your preferences, budget and privacy needs. It works across popular IDEs, so teams using different editors can share a consistent AI-assisted experience. For developers who want modern AI coding help without committing to a single proprietary editor or model provider, Continue offers a powerful, adaptable middle ground that respects how they already work.

Continue is ideal for developers and teams who value open source, want to choose and control their AI models, and prefer adding AI to their existing VS Code or JetBrains setup rather than switching editors. It sits alongside tools like Cline and Aider in the open-source AI-coding ecosystem, and is a flexible alternative to closed AI editors like Cursor. If you want customizable, open, model-agnostic AI assistance integrated into the IDE you already love, Continue is a standout choice that keeps you in control of both your workflow and your AI.

Sourcegraph is a code intelligence platform built around powerful code search and an AI coding assistant (Cody) that understand your entire codebase. For engineering teams working with large, complex code, simply finding and understanding code is a major challenge — and Sourcegraph's universal code search lets developers search across all their repositories, navigate code, and understand how everything connects, dramatically speeding up the everyday work of reading, navigating and changing code.

Its code search is the foundation: developers can search across millions of lines and many repositories to find functions, references, usages and patterns instantly, which is invaluable for understanding unfamiliar code, assessing the impact of changes, and performing large-scale refactors. Built on top of this deep code understanding is Cody, Sourcegraph's AI assistant, which leverages the whole-codebase context to answer questions, explain code, generate suggestions and help with changes far more accurately than tools that only see a single file. This codebase-aware AI is especially powerful for the large, real-world codebases where context matters most.

Sourcegraph also enables large-scale code changes and automation across repositories, helping teams keep their code consistent and up to date. It's used by many large engineering organizations that need to search, understand and improve big codebases efficiently, and its AI capabilities extend that value into the era of AI-assisted development. As codebases grow ever larger and AI becomes central to how developers work, the combination of deep code search and codebase-aware AI is increasingly compelling. For engineering teams that want to navigate and understand their code faster — and to use an AI assistant that truly knows their codebase — Sourcegraph offers a powerful, mature and well-regarded platform.