Apollo-1-2B is a 2 billion parameter instruction-tuned model developed by Noema Research, based on Qwen3-1.7B. It is optimized for general reasoning, language understanding, and lightweight deployment, inheriting Qwen3's long-context capabilities up to 32k tokens. This model is designed for scalable experimentation and real-world applications in constrained environments, offering improved instruction following and reduced hallucinations compared to its base. Its primary applications include conversational AI, lightweight reasoning tasks, and prototyping agents.
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