Gemma 3 27B vs Phi-3.5-MoE Instruct

Gemma 3 27B

Google DeepMind

Gemma 3 27B is a 27-billion-parameter open-weight model from Google DeepMind, released in March 2025 alongside the Gemma 3 12B as the higher-capability variant in the series, built with native vision-language support for text and image inputs across a 128K token context window. Among the Gemma 3 releases, the 27B delivered the strongest results on instruction-following and knowledge-intensive reasoning tasks, making it the preferred option for developers needing greater accuracy from a self-hostable model. Its open-weight availability under a permissive license made it a common starting point for vision-language fine-tuning projects.

Phi-3.5-MoE Instruct

Microsoft

Phi-3.5-MoE-instruct is a sparse mixture-of-experts model from Microsoft's Phi research team, released in August 2024 with 42 billion total parameters across 16 experts and approximately 6.6 billion active parameters per forward pass. The model applies Microsoft's small-data, high-quality training philosophy — developed across earlier Phi generations — to a MoE architecture, targeting reasoning quality comparable to much larger dense models at a fraction of the inference compute. Released under the MIT license, it was notable in the research community for demonstrating that MoE efficiency gains could be realized at smaller total parameter counts than typical large-scale MoE deployments.