Open-Source Model
A model whose weights are publicly available, enabling local deployment, inspection, and fine-tuning.
Full Definition
Open-source (or more precisely, open-weight) AI models release their trained parameters publicly, allowing developers to download, run, inspect, modify, and fine-tune them without API access or usage restrictions. Key examples include Meta's Llama family, Mistral, Falcon, and Qwen. Open models enable privacy-preserving local deployment, academic research, and community-driven improvement. The 'open' label is contested: some models release weights but not training data or training code, limiting true reproducibility. Open models lag frontier closed-source models by 6–18 months on benchmarks but are rapidly closing the gap, especially through efficient architectures and community fine-tuning.
Examples
A healthcare company running Llama 3 on-premises to process patient records without sending data to a third-party API.
Academic researchers reproducing and extending Mistral's findings by running the model locally on university compute clusters.
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Related Terms
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View →Fine-Tuned Model
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