DeepSeek-V2.5 vs Phi-3.5-MoE-instruct
DeepSeek-V2.5 leads the LLM Stats Score 8.4 to 1.9.
DeepSeek · Microsoft · Updated for 2026
Which is better?
DeepSeek-V2.5 leads the overall LLM Stats Score 8.4 to 1.9, ranking #270 overall.
In the 5 individual benchmarks reported for both models, DeepSeek-V2.5 wins 5; 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 DeepSeek-V2.5
- overall performance matters — it scores 8.4 and ranks #270 on LLM Stats
- your work emphasizes reasoning — it leads those capability indexes
- you value its reported benchmark strengths — it wins 5 of 5 exact shared results
Choose Phi-3.5-MoE-instruct
- you want the most recent training data — it shipped Aug 2024
At a glance
The differences that matter most.
Capability indexes
Additional strengths measured across groups of related public benchmarks
Individual benchmarks
15 reported for DeepSeek-V2.5 · 31 for Phi-3.5-MoE-instruct
DeepSeek-V2.5 outperforms in 5 benchmarks (Arena Hard, GSM8k, HumanEval, MATH, MMLU), while Phi-3.5-MoE-instruct is better at 0 benchmarks.
DeepSeek-V2.5 significantly outperforms across most benchmarks.
Human preference
Blind head-to-head votes and playground preference scores
Model Size
Parameter count comparison
DeepSeek-V2.5 has 176.0B more parameters than Phi-3.5-MoE-instruct, making it 293.3% larger.
Context Window
Maximum input and output token capacity
Only DeepSeek-V2.5 specifies input context (8,192 tokens). Only DeepSeek-V2.5 specifies output context (8,192 tokens).
License
Usage and distribution terms
DeepSeek-V2.5 is licensed under deepseek, while Phi-3.5-MoE-instruct uses MIT.
License differences may affect how you can use these models in commercial or open-source projects.
deepseek
Open weights
MIT
Open weights
Release Timeline
When each model was launched
DeepSeek-V2.5 was released on 2024-05-08, while Phi-3.5-MoE-instruct was released on 2024-08-23.
Phi-3.5-MoE-instruct is 4 months newer than DeepSeek-V2.5.
May 8, 2024
2.3 years ago
Aug 23, 2024
2.0 years ago
3mo newerKnowledge 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 DeepSeek-V2.5 and Phi-3.5-MoE-instruct side-by-side, then vote on the output you prefer.
FAQ
Common questions about DeepSeek-V2.5 vs Phi-3.5-MoE-instruct.