[Gemma 2 9B IT](/models/google--gemma-2-9b-it) and Granite 3.1 8B Instruct are both efficient mid-tier models designed for production workloads, but they optimize for different buyer priorities. The key structural split: Gemma 2 9B is capped at **8K context** while Granite 3.1 8B Instruct supports **128K tokens** — enabling document-level inference at a fraction of the cost of larger models. On benchmarks, Gemma 2 9B scores approximately 71 on MMLU, slightly ahead of Granite 3.1 8B at ~66–68. Gemma 2 9B also benefits from Google's instruction-tuning pipeline, which tends to yield stronger general-purpose text quality and code completion. Pricing is comparable: both run $0.05–$0.12/M input tokens at competitive providers, with Gemma 2 9B slightly cheaper due to broader provider availability. Where Granite 3.1 8B Instruct differentiates is IBM's enterprise focus: explicit safety fine-tuning, bias mitigation, and attribution tracing are built into the model family. That matters for regulated industries — finance, healthcare, legal — where content policy compliance is audited rather than assumed. **Gemma 2 9B IT** is well-suited for general-purpose English workloads: code completion, structured JSON extraction, short-document RAG, and function-calling pipelines where inputs stay under 8K and throughput matters. **Granite 3.1 8B Instruct** is the pick for enterprise environments needing long-context processing — ingesting full support tickets, summarizing policy documents, or running internal Q&A over large knowledge bases — with verifiable safety properties. Pick [Granite 3.1 8B Instruct](/models/ibm--granite-3.1-8b-instruct) if 128K context or enterprise safety certification is a hard requirement. Pick Gemma 2 9B IT for general-purpose workloads where higher benchmark quality and lower cost take priority.