Gemma 4 users weigh MoE, dense

The dense model looks like the safer default for agentic work, while the MoE model is the better speed-first choice. On a machine with 128GB unified memory, I’d bias toward reliability unless your workflow is dominated by interactive latency.

• –Google says the 26B MoE activates only 3.8B parameters per token, so its throughput edge is real and intentional.
• –The 31B dense model is the one Google describes as maximizing raw quality and serving as a stronger fine-tuning base, which matters for tool calling and multi-step workflows.
• –For OpenClaw-style tasks, small inconsistencies compound across tool plans, so a denser model is usually the more conservative daily driver.
• –With 128GB unified memory, the 31B dense model is practical on Apple Silicon, so the main tradeoff is speed versus robustness, not feasibility.
• –Best split in practice: 31B dense for primary agent runs, 26B MoE for fast drafting, quick iterations, and lower-latency interactive sessions.