Tabnine vs. Codeium

Tabnine and Codeium are AI code assistants. Both products offer AI-powered chat and code completions to accelerate the software development life cycle and support common use cases such as planning (i.e., asking general coding questions or better understanding code in an existing project), code generation, explaining code, creating tests, fixing code, creating documentation, and maintaining code. 

However, Tabnine offers significant advantages over Codeium. Unlike Codeium, Tabnine gives you total control over its AI code assistant:

• The ability to use new state-of-the-art LLMs with AI chat, with Tabnine admins having full control over choosing specific models and connecting Tabnine to an LLM endpoint inside their corporate network if needed 
• Industry-standard compliances like GDPR, ISO 9001, and SOC2 Type 2
• Highly personalized recommendations, both for code competitions and all the Chat commands such as generating code, explaining code, and more 
• Full transparency around the data that was used to train our proprietary model 
• IP indemnification for further peace of mind

This blog post goes through each of the differences between these products in detail, demonstrating why we believe that Tabnine is the ideal choice for enterprises and individual developers. 

Tabnine: A more mature product

Codeium is a relatively new product (released in late 2022), which is reflected by its significantly lower product downloads and users, and the state of its product docs and support. 

Tabnine is the originator of the AI code assistant category, having introduced our first AI-based code completion tool for Java in the IDE in June 2018. Tabnine is now the leading AI code assistant on the market with a million monthly active users. This enables us to gather feedback from a vast number of users and make continuous improvements and refinements to the product. 

Tabnine’s position as a leader in this space was recently reinforced as we were featured as a luminary in Everest Group’s Innovation Watch Assessment for Generative AI Applications in Software Development. Everest Group — a world-renowned research firm that provides strategic insights on IT, business processes, and engineering services — assessed 14 leading providers of generative AI solutions for software development for this report. The assessment framework evaluated each provider on four criteria (Scale, Level of maturity, Partnerships, and Investments) and segmented them into four categories (Luminaries, Fast Followers, Influencers, and Seekers). Tabnine performed exceptionally well in the entire assessment framework and is recognized as a Luminary. Codeium, on the other hand, was categorized as a Seeker.

• Product downloads: The product downloads for Tabnine across popular IDEs (e.g., VS Code, the JetBrains family of IDEs) is orders of magnitude higher than for Codeium.
• Support: Codeium offers support via their Discord community on Codeium Teams tier, whereas Tabnine’s equivalent product tier offers dedicated support via customer support team. For enterprise customers, we offer priority support with an SLA of as low as 2 hours for the initial response time.
• Docs: Robust product documentation is a hallmark of any dev tools product. However, Codeium’s docs are rudimentary at best and lack product how-tos and best practices. Tabnine’s Docs, on the other hand, are very thorough. 

Lack of industry-standard compliances

GDPR, one of the strictest data privacy laws in the world, is a must-have for AI code assistants as it reflects a company’s strong commitment towards data protection and privacy. Codeium is not GDPR compliant, making it difficult for companies based in the EU or global companies that have customers in the EU to use it. 

Codeium also lacks ISO 9001 compliance, a globally recognized standard for quality management that demonstrates a company’s commitment to maintaining high quality, meeting customer expectations, and improving performance. 

Tabnine offers key compliances like SOC 2 Type 2, GDPR, and ISO 9001 to ensure the security and privacy of your data. 

Personalization 

In AI context is everything. To increase the effectiveness of AI code assistants, it’s imperative to provide contextual awareness to the LLMs so that they can understand the subtle nuances that make a developer and organization unique. Without this context, AI code assistants provide recommendations that are often generic and not tailored to a developer’s needs. 

Codeium gains the context by leveraging many sources of information, such as locally available data in the IDE, company codebases, and by fine-tuning the model. However, Codeium’s Chat considers the context only for a handful of operations. Context is not available when using Codeium Chat for performing refactoring, explaining, or generating docstring operations, thus reducing the relevancy and accuracy of the results. 

Tabnine leverages locally available data in the developer’s IDE, including variable types used near the completion point in the code, comments you’ve added, open files you’ve interacted with, imported packages and libraries, open projects, and many more sources as shown in the image below. We’ve seen that personalized AI recommendations based on awareness of a developer’s IDE are accepted 40% more often than AI suggestions generated without these integrations.

Tabnine administrators can connect Tabnine to their organization’s git repositories (e.g., GitHub, GitLab, BitBucket) to significantly increase the context and get highly personalized results when completing code, explaining code, creating tests, writing documentation, and more.

Tabnine also offers model customization to further enrich the capability and quality of the output. We use your codebase to fine-tune the proprietary models that we purpose-built for software development teams. Model customization is extremely valuable when you have code in a bespoke programming language or a language that’s underrepresented in the training dataset, such as System Verilog. 

Protection from IP issues

Codeium has its own proprietary models for chat and code completions. Codeium mentions that they don’t train their models on repositories with nonpermissive licenses to remove issues with IP infringement. Codeium doesn’t offer indemnification against IP violations for any and all generated code.

Tabnine eliminates concerns around IP infringement from the get-go. We’ve trained our proprietary models (Tabnine Protected 2 for Chat, and the universal model for code completion) exclusively on permissively licensed code. This ensures that the recommendations from Tabnine never match any proprietary code and removes any concerns around legal risks associated with accepting the code suggestions. Unlike Codeium, we’re transparent about the data that was used to train our proprietary model and share it with customers under NDA. Additionally, we offer an IP indemnification to enterprise users for peace of mind. 

Ability to support new models 

Codeium uses its proprietary model to power its AI chat. Additionally, they plan to introduce support for GPT-4.0 and Llama models for Chat. (This capability is in Beta and is not widely available). These limited model options prevent users from leveraging the new and powerful models as they become available. 

Tabnine currently offers users eight different model choices for Tabnine Chat: two custom-built, fully private models from Tabnine; Open AI’s GPT-4o, GPT-4.0 Turbo, and GPT-3.5 Turbo; Anthropic’s Claude 3.5 Sonnet; Cohere’s Command R+; and Codestral, Mistral’s first-ever code model. This flexibility enables users to pick the right model based on their use case or a project. For projects where data privacy and legal risks are less important, you can use a model optimized for performance over compliance. As you switch to working on projects that have stricter requirements for privacy and protection, you can change to a model like Tabnine Protected 2 that’s built for that purpose. 

Enterprises have complete control when selecting models that power Tabnine Chat. Tabnine admins can choose any specific models from the list of available LLMs and make them available to their teams. They can also connect Tabnine to an LLM endpoint inside their corporate network if needed. 

Many new, powerful LLMs were released in the first half of 2024 alone: OpenAI’s GPT-4o, Anthropic’s Claude 3.5 Sonnet, and Cohere’s Command R+ to name a few. At Tabnine, we’re committed to adding support for new, state-of-the-art LLMs as they become available. This prevents LLM lock-in, future-proofs your AI strategy, and enables you to take advantage of all the innovation happening in this space. 

Comparing Tabnine and Codeium

The table below summarizes the differences between Tabnine and Codeium. Both products support common use cases such as code generation, creating documentation, generating tests, and more. However, if you need an AI code assistant that gives you complete control over data privacy, personalization, protection from IP infringement issues, and the freedom to choose the right LLM for your use case, then you should consider Tabnine. 

To learn more about Tabnine, check out our Docs or contact us to schedule a demo with a product expert. If you want to try it out for yourself today, sign up here to try it free for 90 days.