Qwen1.5-110B-Chat
110B
Model parameter quantity
Alibaba
Affiliated organization
Open Source
License Type
April 25, 2024
Release time
Related figures
Model Introduction
Qwen1.5 is the beta version of Qwen2, maintaining its architecture as a decoder-only transformer model with SwiGLU activation, RoPE, and multi-head attention mechanisms. It offers nine model sizes and has enhanced multilingual and chat model capabilities, supporting a context length of 32,768 tokens. All models have enabled system prompts for roleplaying, and the code supports native implementation in transformers.
Comprehensive score
Language dialogue
Knowledge reserve
Reasoning association
Mathematical calculation
Code writing
Command following
Swipe left and right to view more
Language comprehension ability
Often makes semantic misjudgments, leading to obvious logical disconnects in responses.
5.3
Knowledge coverage scope
Possesses core knowledge of mainstream disciplines, but has limited coverage of cutting-edge interdisciplinary fields.
7.9
Reasoning ability
Unable to maintain coherent reasoning chains, often causing inverted causality or miscalculations.
4.5
Model comparison
Qwen1.5-110B-Chat vs Qwen2.5-7B-Instruct
Like Qwen2, the Qwen2.5 language models support up to 128K tokens and can generate up to 8K tokens. They also maintain multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.
Qwen1.5-110B-Chat vs GPT-4o-mini-20240718
GPT-4o-mini is an API model produced by OpenAI, with the specific version number being gpt-4o-mini-2024-07-18.
Qwen1.5-110B-Chat vs GPT-4o-mini-20240718
GPT-4o-mini is an API model produced by OpenAI, with the specific version number being gpt-4o-mini-2024-07-18.
Qwen1.5-110B-Chat vs Gemini-2.5-Pro-Preview-05-06
Gemini 2.5 Pro is a model released by Google DeepMind artificial intelligence research team, using version number Gemini-2.5-Pro-Preview-05-06.
Qwen1.5-110B-Chat vs DeepSeek-V2-Chat-0628
DeepSeek-V2 is a strong Mixture-of-Experts (MoE) language model characterized by economical training and efficient inference. It comprises 236B total parameters, of which 21B are activated for each token. Compared with DeepSeek 67B, DeepSeek-V2 achieves stronger performance, and meanwhile saves 42.5% of training costs, reduces the KV cache by 93.3%, and boosts the maximum generation throughput to 5.76 times.
Related model
Qwen3-235B-A22B-Instruct-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.
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.
Qwen2.5-7B-Instruct
Like Qwen2, the Qwen2.5 language models support up to 128K tokens and can generate up to 8K tokens. They also maintain multilingual support for over 29 languages, including Chinese, English, French, Spanish, Portuguese, German, Italian, Russian, Japanese, Korean, Vietnamese, Thai, Arabic, and more.
Qwen3-32B (Thinking)
Qwen3 is the latest generation of large language models in Qwen series, offering a comprehensive suite of dense and mixture-of-experts (MoE) models.
Qwen1.5-72B-Chat
Qwen1.5 is the beta version of Qwen2, maintaining its architecture as a decoder-only transformer model with SwiGLU activation, RoPE, and multi-head attention mechanisms. It offers nine model sizes and has enhanced multilingual and chat model capabilities, supporting a context length of 32,768 tokens. All models have enabled system prompts for roleplaying, and the code supports native implementation in transformers.
Relevant documents
AI Ad Scaling Revolution: Supercharge Creativity by 10X in 2025
The digital advertising landscape continues its rapid evolution, making innovation imperative for competitive success. As we approach 2025, the fusion of artificial intelligence and creative marketing presents groundbreaking opportunities to revoluti
AI Recruitment Systems Expose Hidden Biases Impacting Hiring Decisions
The Hidden Biases in AI Recruitment: Addressing Systemic Discrimination in Hiring AlgorithmsIntroductionAI-powered hiring tools promise to transform recruitment with efficient candidate screening, standardized interview processes, and data-driven sel
Corporate AI Adoption Plateaus, Ramp Data Reveals
Corporate AI Adoption Reaches PlateauWhile businesses initially rushed to implement artificial intelligence solutions, enthusiasm appears to be stabilizing as organizations confront the technology's current limitations.The Adoption SlowdownRamp's AI
Pokemon FireRed Kaizo IronMon Challenge: Essential Rules & Winning Strategies
The Pokemon FireRed Kaizo IronMon challenge stands as one of gaming's ultimate tests of skill—a brutal gauntlet that breaks conventional Pokemon strategies and forces players to rethink every decision. This punishing variant combines ruthless randomi
AI-Driven Task Management Tools Maximize Productivity and Efficiency
The Future of Productivity: AI-Powered Task ManagementIn our constantly accelerating digital landscape, effective task management has become essential for professional success. Artificial intelligence is revolutionizing how we organize workflows, bri
