Qwen2.5-7B-Instruct
7B
Model parameter quantity
Alibaba
Affiliated organization
Open Source
License Type
September 19, 2024
Release time
Related figures
Model Introduction
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.
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.
4.3
Knowledge coverage scope
Has significant knowledge blind spots, often showing factual errors and repeating outdated information.
6.7
Reasoning ability
Unable to maintain coherent reasoning chains, often causing inverted causality or miscalculations.
4.0
Model comparison
Qwen2.5-7B-Instruct 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.
Qwen2.5-7B-Instruct 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.
Qwen2.5-7B-Instruct 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.
Qwen2.5-7B-Instruct 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.
Qwen2.5-7B-Instruct 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.
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