All Hands AI (OpenHands) vs Continue

Detailed side-by-side comparison to help you choose the right tool

All Hands AI (OpenHands)

🔴Developer

AI Coding

Open-source platform for cloud coding agents — formerly OpenDevin — usable as CLI, web GUI, or SDK.

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Starting Price

Custom

Continue

🔴Developer

AI Coding

Open-source AI code assistant for VS Code and JetBrains with a hub for custom assistants, MCP tools, prompts, and rules — the go-to when a team wants a Copilot-shaped experience they fully control.

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Starting Price

Custom

Feature Comparison

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FeatureAll Hands AI (OpenHands)Continue
CategoryAI CodingAI Coding
Pricing Plans6 tiers187 tiers
Starting Price
Key Features
    • Open-source AI assistant for configurable developer workflows
    • Source-controlled AI checks on every pull request
    • Custom team standards that can be reviewed like code

    All Hands AI (OpenHands) - Pros & Cons

    Pros

    • Genuinely open — tens of thousands of GitHub stars and active community PRs
    • Three usable surfaces (CLI/GUI/SDK) cover both interactive and embedded use cases
    • Model-agnostic, so you avoid vendor lock-in on the inference layer
    • Strong SWE-Bench numbers give defensible eval-based credibility
    • Air-gapped/self-hosted deployment is a real option for regulated enterprises

    Cons

    • Self-hosted setup has more moving parts than commercial competitors
    • Cloud-tier pricing is usage-based and can be hard to forecast for heavy users
    • Agent quality depends heavily on which underlying model you choose
    • Documentation is good but moves fast — version skew between releases happens
    • Newer enterprise features (SSO, audit) lag behind dedicated commercial vendors

    Continue - Pros & Cons

    Pros

    • Supports chat, autocomplete, edits, and agents in VS Code and JetBrains
    • Works with hosted, self-hosted, and local model providers
    • Versioned assistants package models, rules, docs, prompts, and tools
    • Apache 2.0 licensing gives teams meaningful control over deployment

    Cons

    • Model and embedding configuration can be more work than a bundled assistant
    • Local models require capable hardware and careful quality testing
    • Team-tier prices and exact entitlements were not independently verified
    • A broad provider matrix can create inconsistent experiences across developers

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