OLMo 2 13B Instruct, Qwen 3 14B Instruct, and StarCoder2 15B Instruct are three models in the 13–15B range with distinct target audiences. Comparing them is less about who wins on a general leaderboard and more about matching model design to workload: research reproducibility, multilingual production inference, or code generation with provenance guarantees. OLMo 2 13B Instruct from Allen AI is the most openly documented model in this comparison — Apache 2.0 weights, Dolma corpus, OLMo-mix training code, and public evaluation results all published together. Released November 2024, it is the model academic teams and reproducibility-focused researchers reach for. The 4K context ceiling and thin hosted coverage are the constraints that limit its use as a production inference endpoint; it is better understood as a fine-tuning base or research reference. Qwen 3 14B Instruct from Alibaba brings a 131K context window, strong CJK multilingual handling, and latency comparable to smaller Llama and Mistral models. For production deployments — customer-facing applications, multilingual summarization, document extraction — it is the pragmatic choice in this size class. The Qwen license permits commercial use with attribution. StarCoder2 15B Instruct from BigCode is a 15-billion-parameter code model trained on The Stack v2, a dataset restricted to permissively licensed source code. The 16K context window handles most single-file and small multi-file completion tasks. On HumanEval benchmarks it has been overtaken by DeepSeek Coder V2 and Qwen 2.5 Coder, so it is not the highest raw throughput coding choice. Its differentiated value is training data provenance: teams in regulated industries with strict IP policies around model training data favor StarCoder2 because every training example carries a verified open-source license. Released under BigCode OpenRAIL-M. Pick OLMo 2 13B for academic research, reproducibility, or fine-tuning base use. Pick Qwen 3 14B for multilingual production inference with long-context capability. Pick StarCoder2 15B for code generation when verifiable training data provenance is a hard requirement.