Comprehensive side-by-side LLM comparison
InternS1 supports multimodal inputs. Both models have their strengths depending on your specific coding needs.
Shanghai AI Lab
InternS1, released by Shanghai AI Laboratory at WAIC 2025 on July 26, 2025, is a multimodal scientific reasoning large language model designed for advanced problem-solving across mathematics, physics, chemistry, and related domains. It supports text, image, and potentially other scientific data formats as input, and demonstrated strong performance on competition-level scientific benchmarks. InternS1 targets open-source scientific research, STEM education, and applications requiring deep domain reasoning across natural science disciplines.
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.
11 months newer

Phi-3.5-MoE Instruct
Microsoft
2024-08-22
InternS1
Shanghai AI Lab
2025-07-26
Available providers and their performance metrics
InternS1
Phi-3.5-MoE Instruct
InternS1
Phi-3.5-MoE Instruct