GitHub Copilot vs Tabnine: Which Should You Pick?

What each tool is

GitHub Copilot is an assistant that works inside Visual Studio Code, Visual Studio, JetBrains IDEs, Neovim, Xcode, Eclipse and Azure Data Studio. It offers completions, chat, an agent mode in the editor, a cloud coding agent that takes GitHub issues and opens pull requests from a GitHub Actions environment, Copilot code review, a CLI, Copilot Spaces for shared project knowledge, MCP integration and a choice of models from Anthropic, OpenAI, Google and others.

Tabnine describes itself in its documentation as a fully private, organization-aware AI coding agent designed to run entirely within your environment. It provides Tabnine Agent, through the CLI or the IDE, and Tabnine Chat for questions about your codebase, with plugins for VS Code, JetBrains, Visual Studio and Eclipse, plus admin analytics, team management and a configurable context engine. The documented plans are Enterprise (SaaS), which the vendor says never stores your code and is SOC 2 and GDPR compliant, and Enterprise (private installation), which runs on-premises or in a VPC. Tabnine states its models are trained exclusively on credible open source code with permissive licensing, and enterprise customers can use fine-tuned or custom models.

Pricing

GitHub Copilot Free is $0 with 2,000 completions a month, a limited allowance of AI credits and automatic model selection only. Pro is $10 a month with 1,500 AI credits, Pro+ is $39 a month with 7,000 credits and access to premium models, and Max is $100 a month with 20,000 credits. One AI credit equals $0.01, unused credits do not carry over, and a $10 additional usage budget covers 1,000 credits. Business is $19 per user a month with 1,900 credits per user; Enterprise is $39 per user a month with 3,900 credits per user and requires GitHub Enterprise Cloud.

Tabnine does not publish prices on a page we could verify. tabnine.com/pricing redirects to a contact form on tricentis.com, and Tabnine's documentation states it cannot provide numeric pricing for each plan. The documented plans are Enterprise (SaaS) and Enterprise (private installation), with a reference to a Pro tier using universal models. For any per-seat figure, check the vendor's pricing page or contact Tricentis; we have not reproduced third-party price lists.

Where GitHub Copilot wins

Transparent, low pricing. A developer can start free, pay $10 a month for Pro, and a company can budget $19 or $39 per user with exact credit allowances published. Tabnine requires a sales conversation before you know what it costs.

Agents and GitHub integration. Copilot's cloud coding agent is assigned from an issue, works in GitHub Actions and opens a pull request, and GitHub says it runs without extra cost inside your included Actions minutes and AI credits. Copilot code review, Copilot Spaces and the CLI extend the same account. Tabnine has an agent in the IDE and CLI, but nothing that lives inside GitHub's issue and pull request flow.

Model breadth and editor reach. Copilot lets you pick from Anthropic, OpenAI, Google and other models on paid plans. Tabnine's published position is its own models trained on permissively licensed code, with custom models for enterprise. Copilot also adds Neovim, Xcode and Azure Data Studio to the editors both support.

Where Tabnine wins

Deployment inside your perimeter. Tabnine Enterprise (private installation) runs on-premises or in a VPC so that code and prompts never leave your infrastructure. Copilot is a cloud service; GitHub Enterprise Cloud governance controls what is sent, but the models run on GitHub's side. For defense, finance or healthcare teams with a hard rule against code leaving the network, Tabnine is the one that fits.

Provenance and IP posture. Tabnine states its models are trained exclusively on credible open source code with permissive licensing, and its SaaS plan states it never stores your code and does not train on it unless you opt in for custom models. If your legal team's first question is about training data, Tabnine has a documented answer.

Organization-aware customization without GitHub. The docs describe fine-tuned and custom models, a configurable context engine and admin analytics. Copilot Enterprise offers codebase indexing and fine-tuned models too, but only on GitHub Enterprise Cloud; Tabnine offers them without requiring a particular source host.

Who should pick which

Pick GitHub Copilot if you are an individual, a startup, or any organization comfortable with a cloud assistant. Its price is public, its free tier is real, its editor support is the widest, and its agents are native to GitHub. Choose Enterprise if you are on GitHub Enterprise Cloud and want codebase indexing and Spaces.

Pick Tabnine if your organization requires on-premises or VPC deployment, if training data provenance is a procurement requirement, or if you use a source host other than GitHub and still want custom models. Expect to engage Tricentis for pricing, and confirm the current plan names before you compare on cost.