Gemma 2 9B IT, Granite 3.1 8B Instruct, and Qwen 3 8B Instruct form an interesting sub-10B comparison because each brings a distinct strength: low-latency hosting, enterprise structured-output tuning, and multilingual breadth respectively. Gemma 2 9B IT is Google DeepMind's 9-billion-parameter instruction-tuned model, released July 2024 and distilled from Gemini Ultra training data. On general benchmarks it is competitive with peers in this size class, and Groq's hosting delivers some of the lowest latency numbers available for sub-10B models. The 8K context ceiling and the non-OSI Gemma license are the main constraints to evaluate before committing. IBM's Granite 3.1 8B Instruct ships Apache 2.0 and carries a 128K context window — the longest in this comparison. The 3.1 revision released December 2024 expanded the context from 4K, which was a significant practical upgrade for enterprise RAG pipelines and long-document extraction tasks. IBM's tuning emphasis on structured outputs and tool-use makes it a natural fit for extraction and function-calling workloads rather than open-ended generation. Qwen 3 8B Instruct from Alibaba brings 131K context and the best multilingual coverage in the group, with measurably stronger CJK and Arabic handling than either Gemma 2 9B or Granite 3.1 8B. On reasoning benchmarks it competes at the top of the sub-10B tier. The Qwen license permits commercial use. Provider coverage has expanded steadily through 2025 and into 2026. Pick Gemma 2 9B for low-latency short-context inference, especially on Groq. Pick Granite 3.1 8B for long-document enterprise tasks under Apache 2.0 terms. Pick Qwen 3 8B when multilingual support or CJK language quality is a deciding requirement alongside long-context capability.