Comprehensive side-by-side LLM comparison
Qwen2.5 72B Instruct leads with 7.4% higher average benchmark score. Overall, Qwen2.5 72B Instruct is the stronger choice for coding tasks.
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
Qwen2.5-72B-Instruct is the flagship of Alibaba's Qwen2.5 series, a 72-billion-parameter open-weight model released in September 2024 after training on 18 trillion tokens spanning code, mathematics, and multilingual text. It offers strong generalist performance across coding, instruction-following, and structured reasoning while remaining fully open-weight under Apache 2.0 — a combination that made it a widely referenced model in open-source evaluations and community benchmarking. The 128K context window and built-in structured output support made it a common choice for document analysis and multi-step agentic pipeline development.
28 days newer

Phi-3.5-MoE Instruct
Microsoft
2024-08-22
Qwen2.5 72B Instruct
Alibaba / Qwen
2024-09-19
Average performance across 1 common benchmarks
Phi-3.5-MoE Instruct
Qwen2.5 72B Instruct
Performance comparison across key benchmark categories
Phi-3.5-MoE Instruct
Qwen2.5 72B Instruct
Available providers and their performance metrics
Phi-3.5-MoE Instruct
Qwen2.5 72B Instruct
Phi-3.5-MoE Instruct
Qwen2.5 72B Instruct