GitHub Copilot provides code completion, chat, and agent workflows across supported editors and GitHub. Its coding agent can work on repository tasks and create pull requests for review. The former Copilot Workspace technical preview was sunset on May 30, 2025. Availability and usage allowances vary by plan.
Starting at: $10/mo (freemium) — Free tier available
Pros- Broadest IDE support of any AI coding assistant, covering virtually every major editor
- Integrated with GitHub issues and pull requests
- Used by over 1.8 million developers, meaning issues, patterns, and workarounds are well documented
Cons- Completions can confidently suggest outdated APIs or deprecated patterns
- Agent changes require review and depend on repository context and plan limits
- No option to run models locally, so all code is sent to Microsoft/OpenAI servers
Cursor is a code editor with AI completion and agent workflows. It can inspect repository context, coordinate edits across files, and run tools to help implement and debug changes. Developers can choose among supported models, subject to plan and usage limits.
Starting at: $20/mo (freemium) — Free tier available
Pros- Tab completion is meaningfully ahead of Copilot for predicting multi-line intent
- Composer makes large refactors and feature additions feel like a conversation
- Model flexibility lets teams swap LLMs without changing their workflow
Cons- Forked from VS Code, so extensions occasionally break or lag behind upstream
- Composer can produce overconfident edits that need careful review on large diffs
- Free tier has a strict monthly limit on fast model requests
Devin Desktop is the successor to Windsurf, announced by Cognition on June 2, 2026. It combines an IDE with a manager for local and cloud coding agents. Spaces group sessions and shared context, while ACP support allows compatible agents to use the same interface. Devin Local succeeds the former Cascade agent.
Starting at: Free (freemium) — Free tier available
Pros- Combines an IDE and agent management
- Supports multiple compatible coding agents
Cons- Agent usage depends on provider and plan allowances
- Review generated changes before merging
Amazon Q Developer is AWS's AI coding assistant, offering inline completions and a conversational interface in VS Code and JetBrains with deep native understanding of AWS services, SDKs, and infrastructure patterns. Beyond completions, it includes a code transformation feature that can automatically upgrade Java applications across major versions — a task that typically requires weeks of manual effort. Built-in security scanning detects vulnerabilities and exposed credentials in real time, surfacing issues before code is committed. It also extends into the AWS console and CLI, helping engineers understand service configurations, troubleshoot CloudWatch errors, and navigate AWS documentation without leaving their current context.
Starting at: $19/mo (freemium) — Free tier available
Pros- Best-in-class AI assistance for AWS-specific code — service APIs, IAM policies, and CDK constructs are suggested with high accuracy
- Automated Java upgrade feature can handle a major version migration in hours rather than weeks of manual effort
- Free tier is generous and includes security scanning, which is a paid add-on in competing tools
Cons- Noticeably weaker for general-purpose coding tasks outside the AWS ecosystem compared to Copilot or Cursor
- Code transformation features are limited to Java and .NET, leaving other language ecosystems without equivalent tooling
- The AWS-console chat is useful but the IDE experience feels less polished than dedicated AI IDEs
Cody is Sourcegraph's code assistant for enterprise deployments, with repository context and support for organization-managed models. Cody Free, Pro, and Enterprise Starter were discontinued on July 23, 2025. Enterprise customers should confirm availability and pricing with Sourcegraph; the former $59 per-seat figure is not a current self-serve quote.
Starting at: Check provider pricing (paid-only)
Pros- Codebase-wide understanding is genuinely superior for large, complex repositories where other tools only see the open file
- LLM flexibility lets teams choose the best model for a given task or meet data residency requirements
- Self-hosted option makes it viable for enterprises with strict data governance policies
Cons- Requires an enterprise agreement and setup
- Model availability and data routing depend on organization configuration
Tabnine is an AI code completion assistant built around a privacy-first architecture, making it the go-to choice for enterprises with strict data security and IP requirements. Unlike cloud-only competitors, Tabnine can run its models entirely on-device or on a private cloud deployment, ensuring that source code never leaves the corporate environment. Its training data is limited to permissively-licensed open-source code, which removes the licence contamination risk that concerns legal teams at large organisations. Tabnine holds SOC 2 Type II certification and supports enterprise access controls, audit logging, and SSO.
Starting at: $39/mo (paid-only)
Pros- Strongest data privacy guarantees of any mainstream AI coding assistant, with genuine air-gap options
- Trained only on permissively-licensed code, reducing legal exposure for enterprise IP teams
- SOC 2 compliance and private deployment options satisfy security requirements that rule out other tools
Cons- Completion quality lags behind Copilot and Cursor when running smaller local models
- No agentic or multi-file editing capabilities — strictly an inline completion tool
- Higher per-seat cost than competitors once you factor in the private cloud tier