Qodo Unveils Efficient AI Code Embedding Model, Outperforming Competitors in Benchmark Tests
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- Qodo's new open-source code embedding model, Qodo-Embed-1-1.5B, outperforms larger models from OpenAI and Salesforce while being significantly smaller and more efficient.3
- The Qodo-Embed-1-1.5B model scored 70.06 on the Code Information Retrieval Benchmark, outperforming Salesforce’s SFR-Embedding-2_R and OpenAI’s text-embedding-3-large.3
- Qodo's model is designed to enhance code search, retrieval, and understanding for enterprise development teams managing vast codebases.1
- CEO Itamar Friedman emphasized that code generation alone isn’t enough for enterprise software, highlighting the need for high-quality code integration.1
- Qodo, previously known as Codium, has launched a new open-source code embedding model called Qodo-Embed-1-1.5B. This model is noted for its state-of-the-art performance while being significantly smaller and more efficient than its competitors.
- In the Code Information Retrieval Benchmark (CoIR), Qodo-Embed-1-1.5B achieved a score of 70.06, surpassing Salesforce’s SFR-Embedding-2_R at 67.41 and OpenAI’s text-embedding-3-large at 65.17. This performance highlights Qodo's advancements in AI-driven code retrieval across multiple languages and tasks.
- According to Itamar Friedman, CEO and cofounder of Qodo, the innovation is crucial for enterprise development teams dealing with extensive codebases. He emphasized that “code generation alone isn’t enough — you need to ensure the code is high-quality, works correctly and integrates with the rest of the system.”