o1 mini vs Phi-3.5-MoE Instruct

o1 mini

OpenAI

OpenAI o1 mini, released by OpenAI in September 2024, is a lightweight reasoning model from the o1 family optimized for efficient STEM problem-solving at lower cost and latency. It features a 128K token context window and applies chain-of-thought reasoning specifically tuned for mathematics, science, and coding tasks. o1 mini targets use cases where rapid, cost-efficient reasoning is preferred over the broader capabilities of the full o1 model.

Phi-3.5-MoE Instruct

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.