Gemma 4 E2B vs Gemma 4 31B

Both Gemma 4 E2B and Gemma 4 31B 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 4 E2B supports a context window of 131K tokens (~98k words), while Gemma 4 31B supports 262K tokens (~197k words). Therefore, Gemma 4 31B can process more textual data and document context in a single prompt.

Gemma 4 E2B scores at the frontier of coding benchmarks, while Gemma 4 31B scores 68.5%. For complex autonomous debugging and agentic engineering, Gemma 4 31B provides robust code generation and tool calling.

Gemma 4 E2B features native chain-of-thought extended thinking mode with configurable reasoning effort. In contrast, Gemma 4 31B provides chain-of-thought reasoning depth for complex math and science.

Gemma 4 E2B generates approximately 260 tokens per second, while Gemma 4 31B delivers 80 tokens per second. In latency-sensitive production environments, Gemma 4 E2B 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 4 E2B, and route deep architectural or complex reasoning queries to Gemma 4 E2B. This balanced routing strategy maximizes system throughput and answer quality.