Gemma 3n vs GLM-5.1

Gemma 3n is Google DeepMind's newest open-weights model optimized for on-device inference across text, image, and audio modalities. It achieves a 4B effective parameter footprint through MatFormer-style parameter sharing, enabling deployment on consumer hardware including mobile phones, laptops, and edge devices without quantization-induced quality loss. The architecture is a significant departure from previous Gemma versions. Gemma 3n uses "nested parameter sets" — at inference time, the model dynamically selects the parameter subset appropriate for the task complexity. A simple text generation task might use the 1B subset; audio transcription with image context uses the full 4B path. This adaptive compute approach keeps average latency low while enabling genuine multimodality without the usual tradeoffs. For developers, Gemma 3n ships with native support for MediaPipe LLM Inference API (Android, iOS, web), LiteRT, and Ollama. The audio capability is particularly notable — it handles multilingual speech recognition and audio classification without a separate speech-to-text step. Google is positioning this as the backbone for next-generation on-device AI assistants, AR glasses, and IoT applications.

GLM-5.1 is Zhipu AI's latest open-weights language model — a 744B parameter mixture-of-experts (MoE) architecture that activates 40B parameters per forward pass. Released under the MIT license with a 200,000-token context window, it has quietly topped the SWE-Bench Pro leaderboard, surpassing both Claude Opus 4.6 and GPT-5.4 on expert-level software engineering tasks. The MoE architecture means GLM-5.1 is significantly cheaper to run per token than a dense 744B model, with inference costs approaching dense 40B models for most workloads. Zhipu AI (a Tsinghua University spin-out) has steadily iterated on the GLM family to produce a text-focused reasoning model that holds its own against proprietary frontier models — now, for the first time, reportedly exceeding them on coding benchmarks. The MIT license is the headline for enterprise and research users: full commercial use, no usage restrictions, no API dependency. This puts GLM-5.1 in direct competition with Qwen3.5 for the "best open-weights model you can actually use for anything" crown, with a differentiating edge in software engineering tasks specifically.