Qwen 3 8B Instruct is the more recent release and shows it on benchmarks: it scores approximately 73–75% on MMLU versus [Granite 3.1 8B Instruct](/models/ibm--granite-3.1-8b-instruct)'s ~72%, and its multilingual training corpus is substantially larger. Both models sit in the $0.05–0.15/1M token range, though [Qwen 3 8B Instruct](/models/alibaba--qwen-3-8b-instruct) sometimes prices slightly higher at providers reflecting demand. The context window is comparable — Qwen 3 8B supports 32K natively, Granite 3.1 8B up to 128K, so for very long-context workloads Granite actually has the architectural edge. Granite 3.1 8B Instruct holds its ground on enterprise IT and structured-output tasks. IBM's fine-tuning focused on function calling accuracy, structured JSON extraction, and domain-specific classification within enterprise infrastructure contexts (logs, tickets, API schemas). Teams running internal enterprise tooling — IT automation, HR policy QA, compliance document parsing — report that Granite 3.1 8B requires less prompt engineering to stay on-schema than comparable 8B models. Qwen 3 8B Instruct wins on multilingual and agentic use cases. Its training data spans 30+ languages with strong instruction-following fidelity across Chinese, Japanese, Korean, and European languages — Granite doesn't come close on non-English benchmarks. For agentic pipelines with multi-step tool use, Qwen 3 8B also maintains higher accuracy past 10 turns. **Pick Granite 3.1 8B Instruct** for English-language enterprise document workflows, IT automation, or long-context RAG over 32K tokens. **Pick Qwen 3 8B Instruct** for multilingual applications, modern agentic pipelines, or when benchmark recency matters to your evaluation process.