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-480B-A35B-Instruct, released by Alibaba's Qwen team on July 22, 2025, is a Mixture-of-Experts large language model with 480 billion total parameters and 35 billion active parameters per inference, specifically designed for agentic coding tasks. It features a 256K token native context window (extendable to 1M tokens with extrapolation) and demonstrated competitive performance on agentic coding, browser automation, and tool-use benchmarks. Qwen3-Coder-480B targets automated software engineering, multi-step code agents, and open-source coding deployments under the Apache 2.0 license.
11 months newer

Phi-3.5-MoE Instruct
Microsoft
2024-08-22
Qwen3-Coder-480B
Alibaba / Qwen
2025-07-22
Context window and performance specifications
Available providers and their performance metrics
Phi-3.5-MoE Instruct
Qwen3-Coder-480B
OpenRouter
Phi-3.5-MoE Instruct
Qwen3-Coder-480B
Phi-3.5-MoE Instruct
Qwen3-Coder-480B