Comprehensive side-by-side LLM comparison
. Both models have their strengths depending on your specific coding needs.
DeepSeek
DeepSeek-V3 was introduced as a major architectural advancement, developed with 671B mixture-of-experts parameters and trained on 14.8 trillion tokens. Built to be three times faster than V2 while maintaining open-source availability, it demonstrates competitive performance against frontier closed-source models and represents a significant leap in efficient large-scale model design.
Alibaba Cloud / Qwen Team
Qwen3-Next 80B Base was introduced as an experimental base model with 80 billion total parameters and 3 billion active parameters. Built to explore advanced mixture-of-experts architectures, it provides a foundation for fine-tuning and research into efficient large-scale model design.
8 months newer

DeepSeek-V3
DeepSeek
2024-12-25

Qwen3-Next-80B-A3B-Base
Alibaba Cloud / Qwen Team
2025-09-10
Context window and performance specifications
Available providers and their performance metrics

DeepSeek-V3
DeepSeek

Qwen3-Next-80B-A3B-Base

DeepSeek-V3

Qwen3-Next-80B-A3B-Base

DeepSeek-V3

Qwen3-Next-80B-A3B-Base