o1-mini vs Phi-3.5-MoE-instruct
o1-mini leads the LLM Stats Score 10.1 to 1.9.
OpenAI · Microsoft · Updated for 2026
Which is better?
o1-mini leads the overall LLM Stats Score 10.1 to 1.9, ranking #255 overall.
In the 3 individual benchmarks reported for both models, o1-mini wins 3; this is a narrower head-to-head signal than the composite indexes.
Based on current LLM Stats indexes, shared benchmarks, pricing, and model metadata for 2026.
Choose o1-mini
- overall performance matters — it scores 10.1 and ranks #255 on LLM Stats
- your work emphasizes reasoning and coding — it leads those capability indexes
- you value its reported benchmark strengths — it wins 3 of 3 exact shared results
- you want the most recent training data — it shipped Sep 2024
Choose Phi-3.5-MoE-instruct
- you need open weights you can self-host or fine-tune
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
6 reported for o1-mini · 31 for Phi-3.5-MoE-instruct
o1-mini outperforms in 3 benchmarks (GPQA, HumanEval, MMLU), while Phi-3.5-MoE-instruct is better at 0 benchmarks.
o1-mini significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Context Window
Maximum input and output token capacity
Only o1-mini specifies input context (128,000 tokens). Only o1-mini specifies output context (65,536 tokens).
License
Usage and distribution terms
o1-mini is licensed under a proprietary license, while Phi-3.5-MoE-instruct uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
Proprietary
Closed source
MIT
Open weights
Release Timeline
When each model was launched
o1-mini was released on 2024-09-12, while Phi-3.5-MoE-instruct was released on 2024-08-23.
o1-mini is 1 month newer than Phi-3.5-MoE-instruct.
Sep 12, 2024
2.0 years ago
2w newerAug 23, 2024
2.0 years ago
Knowledge Cutoff
When training data ends
Neither model specifies a knowledge cutoff date.
Unable to compare the recency of their training data.
Outputs Comparison
Judge for yourself.
Run your own prompts against o1-mini and Phi-3.5-MoE-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about o1-mini vs Phi-3.5-MoE-instruct.