HomeQwen2-72B-Instruct
72B
Model parameter quantity
Alibaba
Affiliated organization
Open Source
License Type
June 6, 2024
Release time
Related figures
Model Introduction
Qwen2 is the new series of Qwen large language models.
Comprehensive score
Language dialogue
Knowledge reserve
Reasoning association
Mathematical calculation
Code writing
Command following
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Language comprehension ability
Often makes semantic misjudgments, leading to obvious logical disconnects in responses.
4.5
Knowledge coverage scope
Possesses core knowledge of mainstream disciplines, but has limited coverage of cutting-edge interdisciplinary fields.
8.4
Reasoning ability
Unable to maintain coherent reasoning chains, often causing inverted causality or miscalculations.
4.4
Model comparison
Qwen2-72B-Instruct vs Doubao-Seed-1.6-251015 (Thinking)
The deep reasoning model released by ByteDance, which supports manual switching of deep reasoning, and its performance is significantly improved compared to doubao-1.5.
Qwen2-72B-Instruct vs Doubao-Seed-1.6-thinking-250715
The latest version of the seed series model launched by ByteDance, which supports the thinking mode.
Related model
Qwen3.6-27B
Qwen3.6 is the next-generation open-source model in the Qwen family and an upgraded version of the Qwen3.5 series.
Qwen3.5-397B-A17B
Qwen3.5 is a significant foundation model recently launched by Alibaba, featuring comprehensive upgrades in multimodal fusion, efficient hybrid architecture, scalable reinforcement learning, multilingual coverage and training infrastructure, with greatly improved performance and practicality.
Qwen3.6-Max-Preview
Qwen3.6-Max-Preview is Qwen’s flagship proprietary model, focusing on stronger reasoning, complex task handling, and high-quality conversational performance.
Qwen3-Next-80B-A3B-Thinking
The latest released Qwen3-Next series in Qwen models, improving scaling efficiency through innovative model architecture.
Qwen3-235B-A22B-Thinking-2507
Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models.
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