Google Antigravity vs Tabnine
Google Antigravity
Quick Verdict
Google Antigravity excels at agentic workflows and ai-native development with a score of 91/100. Google Antigravity represents a paradigm shift in AI-assisted development, moving beyond code completion to full agentic automation.
Tabnine
Quick Verdict
Tabnine excels at code completion and privacy-conscious development with a score of 86/100. Tabnine stands out for its privacy-first approach and highly personalized AI suggestions.
📊 Visual Score Comparison
Side-by-side comparison of key performance metrics across six evaluation criteria
Technical Specifications
| Feature | Google Antigravity | Tabnine |
|---|---|---|
| Core AI Model(s) | Powered by Google's Gemini 3 Pro model as default, with support for Anthropic's Claude Sonnet 4.5 and OpenAI's GPT-OSS for flexible model selection. | Tabnine uses its own proprietary, private AI models for code completion and chat. It also allows users to switch to third-party models from providers like Anthropic (Claude), OpenAI (GPT), Cohere, and Mistral. |
| Context Window | Supports large context windows through Gemini 3 Pro's advanced architecture, with multimodal processing of code, images, and design mocks. | Tabnine is context-aware, analyzing your local IDE environment and project files to provide relevant suggestions. The Enterprise plan allows connecting to an organization's entire codebase (GitHub, GitLab, Bitbucket) for more deeply personalized, context-aware recommendations. |
| Deployment Options | Available as a downloadable desktop application for Windows, macOS, and Linux. Currently in public preview with enterprise features planned. | Tabnine offers flexible deployment. It is available as a secure multi-tenant SaaS for all users. For Enterprise customers, it offers fully private deployments on-premises, in a Virtual Private Cloud (VPC), or in a completely air-gapped environment. |
| Offline Mode | Limited offline capabilities; core agentic features require cloud connectivity for AI model inference and agent orchestration. | Yes, Tabnine's AI can run locally on a developer's machine, on a server behind a firewall, or in the cloud, supporting offline use cases. |
Core Features Comparison
Google Antigravity Features
- Agentic development with autonomous AI agents
- Dual interface: Editor View and Manager View
- Artifact transparency system for trust verification
- Multimodal capabilities (code, images, design mocks)
- Multi-model support (Gemini 3 Pro, Claude Sonnet 4.5, GPT-OSS)
- Self-improvement mechanism learning from user feedback
Tabnine Features
- Personalized AI code completion
- Privacy-focused local processing
- Support for multiple programming languages
- Custom model training on your codebase
Pricing & Value Analysis
| Aspect | Google Antigravity | Tabnine |
|---|---|---|
| Pricing URL | View Google Antigravity Pricing | View Tabnine Pricing |
| Overall Score | 91/100 | 86/100 |
| Best For | Agentic Workflows, AI-Native Development, Multi-Agent Orchestration | Code Completion, Privacy-conscious Development, Personalized AI |
Best Use Cases
Google Antigravity Excels At
- Orchestrating multiple AI agents to work on different parts of a large codebase simultaneously
- End-to-end feature development from design mocks to implementation using multimodal AI
- Complex refactoring tasks with autonomous planning, execution, and validation by AI agents
Tabnine Excels At
- Personalized code completion that learns from your team's coding patterns and maintains consistency across projects
- Privacy-compliant AI assistance for enterprises with strict data security requirements and air-gapped environments
- Custom AI model training on proprietary codebases for domain-specific programming languages and frameworks
Performance & Integration
| Category | Google Antigravity | Tabnine | Winner |
|---|---|---|---|
| IDE Support | Google Antigravity is a standalone AI-native IDE. Integrates with Google Cloud services and supports extensions. | Tabnine supports a wide range of IDEs, including VS Code, the JetBrains suite (IntelliJ, PyCharm, WebStorm, etc.), Visual Studio, Eclipse, and Neovim. | Tie |
| Community | Active community | Active community | Tie |
| Data Richness | Comprehensive | Comprehensive | Tie |
| Overall Score | 91/100 | 86/100 | Google Antigravity |
Google Antigravity vs Tabnine: Agentic vs Completion Focus
Google Antigravity and Tabnine represent two different generations of AI coding tools—autonomous agents vs intelligent autocomplete:
Autonomous Agents vs Autocomplete
Google Antigravity deploys AI agents that independently complete multi-step coding tasks. Tabnine focuses on line-by-line code suggestions as you type.
Privacy-First Architecture
Tabnine offers local processing and strict privacy controls, ideal for sensitive codebases. Antigravity processes code through Google's cloud infrastructure.
Scope of Assistance
Antigravity can architect features, refactor systems, and coordinate multiple files autonomously. Tabnine excels at completing the current line or function you're writing.
Personalization Approach
Tabnine learns your personal coding patterns for highly personalized suggestions. Antigravity uses general-purpose frontier models with self-improvement from feedback.
Integration Model
Tabnine integrates as a lightweight extension in your existing IDE. Antigravity is a standalone IDE with its own interface and workflow.
Enterprise Security
Tabnine offers on-premises deployment and SOC 2 compliance for enterprise security requirements. Antigravity is cloud-based with Google's security model.
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The Bottom Line
Both Google Antigravity and Tabnine are capable AI coding tools, but they serve different needs. Google Antigravity scores higher (91/100 vs 86/100) and excels in agentic workflows and ai-native development. The choice depends on your specific workflow, team size, and technical requirements.
Choose Google Antigravity if: you prioritize agentic workflows and ai-native development and want the higher-rated option (91/100).
Choose Tabnine if: you prioritize code completion and privacy-conscious development and don't mind a slightly lower score for specialized features.