Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
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.
Alibaba / Qwen
Qwen3 Coder Next is a coding-specialized open-weight model from Alibaba's Qwen3 family, built on the Qwen3-Next architecture with hybrid attention and Mixture-of-Experts design optimized for local development and agentic coding workflows. It targets on-device and self-hosted deployments requiring a capable coding agent that can operate within consumer hardware constraints.
1 year newer

Phi-3.5-MoE Instruct
Microsoft
2024-08-22
Qwen3 Coder Next
Alibaba / Qwen
2026-02-04
Available providers and their performance metrics
Phi-3.5-MoE Instruct
Qwen3 Coder Next
Phi-3.5-MoE Instruct
Qwen3 Coder Next