Three sub-10B generalist models with overlapping benchmark profiles but distinct constraints that determine which fits your deployment context. Gemma 2 9B IT is Google DeepMind's mid-tier Gemma model, a 9-billion-parameter instruction-tuned transformer released July 2024. It performs comparably to Llama 3.1 8B and Mistral 7B on standard benchmarks, and Groq hosts it with some of the lowest latency figures available for sub-10B models. Pricing across providers typically lands below $0.20 per million tokens. The 8K context window is the standing constraint — document-QA, retrieval-augmented generation, and any workload requiring 32K or more context must look elsewhere. The Gemma license is permissive for commercial use but not OSI-approved, which matters for enterprise legal review. Llama 3.1 8B Instruct is Meta's widely deployed 8-billion-parameter model from July 2024, available across virtually every major inference provider and typically priced near the low end of the 8B tier. The Llama 3 community license permits commercial use. Its core strength is ecosystem breadth: more hosted providers, more fine-tune variants, and broader community tooling than any other model in this comparison. Context extends to 128K, covering most document-length tasks. General benchmark performance is solid but not a clear leader over its peers. Qwen 3 8B Instruct, from Alibaba's Qwen 3 family, runs 8 billion parameters with a 131K context window and stands out on multilingual benchmarks — consistently outperforming Llama 3.1 8B on CJK language tasks. For products with East Asian user traffic or mixed-language pipelines, that gap is real and measurable. Per-token pricing runs below $0.10 on most hosted providers, making it one of the cheaper capable 8B models. Released under the Qwen license with commercial terms. Pick Gemma 2 9B for latency-critical applications where Groq hosting and sub-10B cost are the priority and 8K context is sufficient. Pick Llama 3.1 8B for maximum provider flexibility and ecosystem breadth. Pick Qwen 3 8B when multilingual coverage — especially CJK — is a real product requirement.