CodeGemma
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CodeGemma is a family of open code LLMs built on Gemma, released in 2B (pretrained), 7B (pretrained), and 7B-IT (instruction-tuned) variants. The 2B model is optimized for low-latency code completion, and the 7B-IT model leads its weight class on HumanEval.
Three-variant family: 2B for fast on-device completion, 7B as a capable pretrained coder, and 7B-IT for chat-style code assistance, all derived from Gemma and released with open weights.
Training recipe: Trained on 500B additional tokens of code, math, and synthetic data with a Fill-in-the-Middle objective (80% FIM rate, 50/50 PSM/SPM split), plus novel dependency-graph-based packing and unit-test-based lexical packing.
Benchmark results: HumanEval pass@1 of 31.1% (2B), 44.5% (7B), and 56.1% (7B-IT). Single-line infilling reaches 78.4% for the 2B model, making it a strong low-latency IDE companion.
Deployment focus: FIM tokens enable direct use in IDE auto-completion pipelines, and quantized builds are already available for llama.cpp, LM Studio, Jan, and Ollama for local deployment.
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