Tabnine
by Tabnine
Enterprise AI coding platform for code completion, chat, code review, testing, agents, and secure software development.
Tabnine is an AI-powered software development platform focused on coding assistance, enterprise code intelligence, and agentic software development. It provides AI code completions, IDE chat, code generation, code explanation, testing, documentation, code review, refactoring, and autonomous coding agents. Tabnine can use leading models from providers such as Anthropic, OpenAI, Google, Meta, and Mistral, while its Context Engine connects AI workflows to codebases, repositories, dependencies, documentation, APIs, and organizational standards. The platform supports SaaS, VPC, on-premises, and fully air-gapped deployments for organizations that require greater control over code and AI usage.
Provider
Tabnine
Category
AI Coding
Available On
Web, VS Code, JetBrains, Visual Studio, Eclipse, IntelliJ IDEA, Terminal, CLI, CI/CD
Launched
Jan 2018
Use Cases
Coding, Software Development, Code Review, Testing
Best For
Professional developers and enterprises that need secure, context-aware AI coding, code review, testing, and agentic development workflows
🧠 Models (6)
Tabnine Custom ModelsvCurrent
Code Generation
Context Window
Varies by selected model
Input
text, code
Output
text, code
Anthropic ModelsvSupported Models
General Purpose
Context Window
Varies by selected model
Input
text, code
Output
text, code
OpenAI ModelsvSupported Models
General Purpose
Context Window
Varies by selected model
Input
text, code
Output
text, code
Google ModelsvSupported Models
General Purpose
Context Window
Varies by selected model
Input
text, code
Output
text, code
Meta ModelsvSupported Models
General Purpose
Context Window
Varies by selected model
Input
text, code
Output
text, code
Mistral ModelsvSupported Models
General Purpose
Context Window
Varies by selected model
Input
text, code
Output
text, code
✨ Features (14)
AI Code Completions
Generates code completions ranging from individual lines to multi-line and full-function implementations
AI Chat
Provides context-aware AI chat for coding, planning, explaining, debugging, and software development tasks
Code Review
Reviews code in IDEs and pull requests against organizational rules, standards, and expectations
Code Fix Agent
Analyzes selected code errors and can generate fixes presented through a simple diff workflow
Testing Agent
Creates test plans and detailed test cases based on project code and existing testing standards
Documentation Agent
Generates documentation for classes, functions, APIs, comments, and other code components
Code Explain Agent
Explains unfamiliar projects, dependencies, project structure, and code behavior to developers
Jira Agent
Can generate software changes from Jira requirements and validate implementations against those requirements
Context Engine
Builds structured understanding of codebases, dependencies, architecture, documentation, APIs, and organizational standards
Agentic Development
Provides autonomous coding agents with optional human oversight for complex software development workflows
MCP Support
Allows agents to interact with supported development tools and external services through Model Context Protocol
CLI Agent
Provides terminal-native AI agents for coding, refactoring, pull requests, remote environments, and CI pipelines
Private Deployment
Supports SaaS, VPC, on-premises, and fully air-gapped deployment options
Multi-Model Support
Allows teams to select supported AI models from multiple leading model providers
💰 Pricing
✕ Free Plan
✕ Free Trial
✓ Paid Plan
✓ Enterprise
Starting Price
$39/user/month
Billed annual
API Pricing
Tabnine-provided LLM access is usage-based; reserved token consumption is priced according to the underlying LLM provider plus a 5% handling fee.
More Info
View pricing page ↗💬 Prompt Library (5)
Explain Code
CodingUnderstand unfamiliar code and identify potential problems
Explain the following code in simple language. Describe what each important section does, identify possible bugs and security concerns, and suggest improvements. ```[PASTE CODE HERE]```
Fix Bug
CodingDiagnose and fix software bugs
Find the cause of the following bug. Analyze the code and error message, explain the root cause, and provide a clean fix without changing unrelated functionality. Error: [ERROR] Code: ```[PASTE CODE HERE]```
Generate Tests
CodingGenerate practical test cases for code
Create a comprehensive test plan for the following function or feature. Include normal cases, edge cases, invalid inputs, security-related cases, and expected results. ```[PASTE CODE HERE]```
Code Review
CodingPerform a detailed senior-level code review
Review this code as a senior software engineer. Check readability, architecture, security, performance, error handling, scalability, maintainability, and potential bugs. Give specific recommendations. ```[PASTE CODE HERE]```
Refactor Code
CodingImprove existing code without changing its intended behavior
Refactor the following code to make it cleaner, more maintainable, secure, and efficient. Preserve the existing behavior and explain the important changes. ```[PASTE CODE HERE]```
🔗 Integrations (8)
GitHub
git
Connect development workflows and repositories to Tabnine's context-aware AI capabilities
GitLab
git
Connect GitLab repositories and development workflows to Tabnine
Bitbucket
git
Connect Bitbucket codebases to Tabnine's Context Engine
Jira
project-management
Use Jira issues and requirements as context for AI-powered software development
Confluence
documentation
Connect organizational documentation and knowledge to supported Tabnine workflows
MCP
protocol
Connect AI agents to supported development tools, databases, APIs, and external services
VS Code
ide
Use Tabnine AI coding assistance directly inside Visual Studio Code
JetBrains
ide
Use Tabnine within supported JetBrains development environments
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⚠️ Limitations
- •AI-generated code can contain bugs, security issues, or incorrect implementations
- •Advanced agentic features require higher-tier paid plans
- •Pricing is primarily designed around professional and enterprise development teams
- •Available AI models and capabilities can vary by plan and deployment configuration
- •Model context windows and capabilities vary depending on the selected underlying model
- •Enterprise features may require contacting Tabnine for a customized quote
- •AI-generated code should be reviewed and tested before production use
📚 Sources
- https://www.tabnine.com/pricing/(official)
- https://www.tabnine.com/ai-chat/(official)
- https://www.tabnine.com/(official)
- https://www.tabnine.com/changelog/(official)