Augment Code vs Continue

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

Augment Code

🔴Developer

AI Coding

Enterprise-grade AI coding assistant with a proprietary Context Engine that indexes millions-of-line codebases in real time, plus an Auggie CLI agent — pitched at large engineering orgs where Cursor/Copilot lose the plot at scale.

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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

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Feature Comparison

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FeatureAugment CodeContinue
CategoryAI CodingAI Coding
Pricing Plans4 tiers187 tiers
Starting Price
Key Features
  • • Context Engine for large-codebase understanding across organizational repositories
  • • Cosmos platform coordinating agents across triage, authoring, review, and verification
  • • MCP and native tools listed in pricing, plus SOC 2 Type II and no-AI-training language
  • • 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

Augment Code - Pros & Cons

Pros

  • ✓Repository-aware Context Engine is designed for monorepos and cross-service changes
  • ✓Works across VS Code, JetBrains, Vim/Neovim, terminal, GitHub, and Slack
  • ✓Agent instructions and enterprise deployment controls suit platform teams
  • ✓Auggie CLI supports repeatable terminal and CI workflows

Cons

  • ✗Published prices and quotas require manual verification because the vendor pages were unreachable
  • ✗A proprietary index is less transparent than open-source retrieval pipelines
  • ✗The strongest governance and deployment controls sit in sales-led tiers
  • ✗Smaller repositories may not benefit enough to justify another coding subscription

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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