The demand for reliable, accurate AI coding assistants is growing fast (let’s just say our sales team’s inboxes are currently flooded). Many enterprise R&D teams are currently exploring the capabilities of different tools, but it can be challenging to find an AI platform that not only provides accurate coding assistance but also provides enterprise-grade security and privacy while meeting the specific needs of each R&D team.
This post compares Tabnine Enterprise to Codeium for Enterprises, based on a range of key parameters that are critical to developers and R&D enterprise teams. By examining the capabilities of each tool, we aim to help you make an informed decision about which AI code assistant is right for your needs:
- Price: Price point for each user in the organization
- Context-awareness: What level of context can the different AI models take into account when providing suggestions?
- Open source compliance: Each company’s practices regarding the code that the AI models are trained on
- Ability to train AI models on private code: The code that the AI models can be trained on
- Code privacy: Privacy controls offered by each solution
- Enterprise deployment: Deployment options available to the customer
Table comparison of Tabnine Enterprise vs. Codeium for Enterprises
| Parameter | Tabnine | Codeium |
|---|---|---|
| Price | $20 per user per month. Additional cost to deploy on your VPC\On-prem. | Depends on the company’s needs. |
| Inline code completions within the IDE | Supported Tabnine offers inline code completions directly within a large variety of IDEs. | Supported |
| Coding assistance via chat | Supported Tabnine's code-centric chat application allows developers to interact with Tabnine’s AI models in a flexible free-form way, using natural language. | Supported |
| Open-source compliance | Tabnine only trains its AI models exclusively on code with permissive licenses. Only returns code recommendations that won't be subject to future questions of ownership and potential litigation. Full transparency regarding the code that the models are trained on. Provides full attribution, allowing users to view references and avoid future legal issues. | It’s currently unclear if Codeium’s models are trained on open-source or non-permissive licenses. |
| Ability to train AI models on private code | Supported Tabnine allows the organization to choose which code the models should be trained on. AI models can be connected different repos for different teams. | Supported |
| Code privacy | Tabnine never stores or shares any of your code. | Customer code is used by Codeium for telemetry purposes (although it’s possible to opt-out). |
| Air-gapped deployments for Enterprise | Self-hosting: Tabnine offers the options for on-premise or VPC installation. | Codeium allows deployment on the customer’s VPC. |
Drilling down further into Tabnine Enterprise vs. Codeium for Enterprises
This section takes a more in-depth look at how the two solutions compare.
Price
Tabnine Enterprise charges $20 per user, while the cost of Codeium for Enterprises isn’t as straightforward and depends on the customer and their needs.
Inline code completions within the IDE and chat
Both Tabnine and Codieum offer inline code completions within the IDE, as well as chat.
Open source compliance
The use of code to train an AI solution’s models can have legal ramifications for customers using the solution.
Tabnine’s AI models are exclusively trained on code licensed under permissive licenses. This approach guarantees full transparency and attribution, which is critical in ensuring that Tabnine isn’t subject to the copyleft provisions of GPL licenses. By adhering to this policy, Tabnine can safeguard its users and customers from potential legal repercussions.
Furthermore, this practice aligns with Tabnine’s objective of respecting the original intent of code authors and maintaining good faith with the wider developer community.
It’s unclear whether or not Codeium’s models are trained on OpenAI or if they’re trained on nonpermissive licenses.
Air-gapped deployment
Tabnine Enterprise offers customers the option to self-host, deploying on the customer’s VPC or on-premises. Tabnine also supports cases where the customer network is air-gapped and can’t access the internet.
On the other hand, Codeium allows its enterprise customers the option of deploying on the customer’s VPC only. Running on a cloud (even a private cloud) means that code needs to leave the premises, which isn’t viable for some enterprises.
Ability to train AI models on private code
Tabnine Enterprise allows its customers to connect their own code repositories to its AI models, with the option to link specific models to particular repositories based on team or project needs. This feature allows the models to adapt and learn the organization’s unique coding practices, naming conventions, and preferred styles, resulting in highly relevant and context-sensitive code suggestions.
By leveraging this functionality, companies can streamline the onboarding and training process for new team members and junior developers, significantly reducing the burden on senior developers. The AI models learn from the company’s own code repositories, resulting in improved accuracy and efficiency in suggesting code, while maintaining consistency with the organization’s established practices.
Codeium trains its models on different coding languages and then fine-tunes the models on its customer’s codebase.
Code privacy
Tabnine Enterprise prioritizes the confidentiality and security of its enterprise customers’ code, ensuring that customer code and training data are never transmitted to Tabnine or used to train its general AI models. This guarantees that customers’ sensitive and proprietary information remains strictly private and protected.
Additionally, Tabnine Enterprise offers flexible deployment options for its customers, allowing them to install the tool on their virtual private cloud (VPC) or on-premises. By enabling customers to have full control over their data and where it is stored, Tabnine Enterprise ensures that their customers’ privacy needs are fully met.
Codeium, however, uses its customer’s code for telemetry purposes, although it’s possible to opt out of this option.
About Tabnine
Since launching our first AI coding assistant in 2018, Tabnine has pioneered generative AI for software development. Tabnine helps development teams of every size use AI to accelerate and simplify the software development process without sacrificing privacy and security. Tabnine boosts engineering velocity, code quality, and developer happiness by automating the coding workflow through AI tools customized to your team. With more than one million monthly users, Tabnine typically automates 30–50% of code creation for each developer and has generated more than 1% of the world’s code.
Unlike generic coding assistants, Tabnine is the AI that you control:
Tabnine ensures the privacy of your code and your engineering team’s activities. Tabnine lives where and how you want it to — deployed as protected SaaS for convenience, on-premises for you to lock down the environment, or on VPC for the balance of the two. Tabnine guarantees zero data retention, and we never use your code, data, or behaviors to feed our general models.
Tabnine is also personalized to your team. Tabnine uses best-of-breed LLMs (which we’re constantly improving and evolving) and is context-aware of your code and patterns. This means that Tabnine provides coding suggestions and chat responses that take your internal standards and engineering practices into account.
Tabnine works the way you want, in the tools you use. Tabnine supports a wide scope of IDEs and languages, improving and adding more all the time. Tabnine also provides engineering managers with visibility into how AI is used in their software development process and the impacts it is having on team performance.
Try free for 90 days, or contact us to learn how we can help your engineering team be happier and more productive.
