What are the key differences between Phi-3.5-MoE and DeepSeek-V3?

Compare Phi-3.5-MoE and DeepSeek-V3 side by side on Lunoo to see detailed feature differences, AI scores, and expert analysis.

How are Phi-3.5-MoE and DeepSeek-V3 scored?

Phi-3.5-MoE has an AI score of 7.9/10 and DeepSeek-V3 has an AI score of 9.0/10. Scores are based on category fit, feature coverage, pricing signals, public reception, and recency.

Phi-3.5-MoE vs DeepSeek-V3 2026 - Compared

Phi-3.5-MoE

DeepSeek-V3

WINNER DeepSeek-V3

DeepSeek-V3 edges ahead with a score of 9.0/10 compared to 7.9/10 for Phi-3.5-MoE. While both are highly rated in their...

Phi-3.5-MoE

7.85 Good

Model Get Phi-3.5-MoE open_in_new

emoji_events WINNER

DeepSeek-V3

9.02 Excellent

Model Get DeepSeek-V3 open_in_new

psychology AI Verdict

DeepSeek-V3 edges ahead with a score of 9.0/10 compared to 7.9/10 for Phi-3.5-MoE. While both are highly rated in their respective fields, DeepSeek-V3 demonstrates a slight advantage in our AI ranking criteria. A detailed AI-powered analysis is being prepared for this comparison.

emoji_events Winner: DeepSeek-V3

verified Confidence: Low

Ready to decide? Get DeepSeek-V3 arrow_forward

description Overview

Phi-3.5-MoE

Phi-3.5-MoE is a mixture-of-experts large language model released by Microsoft in August 2024 as part of the Phi-3.5 family. The architecture uses 16 expert modules with 3.8 billion parameters each, of which 2 are activated per token, yielding 6.6 billion active parameters within a total of 42 billion. Microsoft reported that the model achieved competitive reasoning and coding benchmarks relative...

DeepSeek-V3

DeepSeek-V3 is a large language model released by the Chinese AI company DeepSeek in late 2024. It is built as a Mixture-of-Experts (MoE) model with a total of 671 billion parameters, of which only 37 billion are activated per token. The model was trained efficiently using a specialized architecture and has demonstrated benchmark performance competitive with other leading closed and open-weight mo...