Gemma 3n vs Gemma 3

Both Gemma 3n and Gemma 3 are open-weights foundation models available at $0.00 direct API cost when self-hosted, or offered at identical baseline rates across major inference providers. Model selection depends on GPU deployment sizing and specialized benchmark performance rather than raw token price.

Gemma 3n supports a context window of 32K tokens (~24k words), while Gemma 3 supports 131K tokens (~98k words). Therefore, Gemma 3 can process more textual data and document context in a single prompt.

Gemma 3n scores at the frontier of coding benchmarks, while Gemma 3 scores competitively for software generation. For complex autonomous debugging and agentic engineering, Gemma 3n provides robust code generation and tool calling.

Gemma 3n is optimized for low-latency direct generation. In contrast, Gemma 3 focuses on standard fast inference.

Gemma 3n generates approximately 150 tokens per second, while Gemma 3 delivers 105 tokens per second. In latency-sensitive production environments, Gemma 3n provides faster time-to-first-token (TTFT) and higher streaming response velocity.

Yes! Tiered multi-model routing can optimize for latency and accuracy: you can route high-frequency conversational turns and latency-sensitive queries to Gemma 3n, and route deep architectural or complex reasoning queries to Gemma 3n. This balanced routing strategy maximizes system throughput and answer quality.