Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-R1, released by DeepSeek on January 20, 2025, is a large reasoning model with 671 billion total parameters (37 billion active in its MoE architecture) designed for extended chain-of-thought reasoning. It features a 128K token context window and demonstrated strong performance on mathematics, coding, and scientific reasoning benchmarks at its release. DeepSeek-R1 targets complex analytical tasks, competitive programming, and applications requiring deep deliberative reasoning under an open MIT license.
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.
5 months newer

Phi-3.5-MoE Instruct
Microsoft
2024-08-22

DeepSeek-R1
DeepSeek
2025-01-20
Context window and performance specifications
Available providers and their performance metrics
DeepSeek-R1
DeepSeek
Phi-3.5-MoE Instruct
DeepSeek-R1
Phi-3.5-MoE Instruct
DeepSeek-R1
Phi-3.5-MoE Instruct