abab7-chat-preview
N/A
Model parameter quantity
MiniMax
Affiliated organization
Closed Source
License Type
November 6, 2024
Release time
Model Introduction
The abab7-preview model, produced by MiniMax, is an API model that shows significant improvements over the abab6.5 series in capabilities such as handling long texts, mathematics, and writing.
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.
5.0
Knowledge coverage scope
Possesses core knowledge of mainstream disciplines, but has limited coverage of cutting-edge interdisciplinary fields.
7.3
Reasoning ability
Unable to maintain coherent reasoning chains, often causing inverted causality or miscalculations.
5.5
Model comparison
abab7-chat-preview 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.
abab7-chat-preview 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.
abab7-chat-preview 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.
abab7-chat-preview 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.
abab7-chat-preview 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
MiniMax-Text-01
MiniMax-Text-01 is a powerful language model with 456 billion total parameters, of which 45.9 billion are activated per token. To better unlock the long context capabilities of the model, MiniMax-Text-01 adopts a hybrid architecture that combines Lightning Attention, Softmax Attention and Mixture-of-Experts (MoE).
MiniMax-M1-80k
The world's first open-weight, large-scale hybrid-attention reasoning model released by Minimax
abab6.5
abab6.5 is an API model produced by MiniMax, with the version number being abab6.5. The abab6.5 serie is a trillion-parameter Mixture of Experts (MoE) large language model. The abab6.5 is suitable for complex scenarios, such as application problem calculations, scientific computations, and other similar scenarios. The abab6.5s is suitable for general scenarios.
abab6.5s-chat
abab6.5 is an API model produced by MiniMax, with the version number being abab6.5. The abab6.5 serie is a trillion-parameter Mixture of Experts (MoE) large language model. The abab6.5 is suitable for complex scenarios, such as application problem calculations, scientific computations, and other similar scenarios. The abab6.5s is suitable for general scenarios.
MiniMax-Text-01
MiniMax-Text-01 is a powerful language model with 456 billion total parameters, of which 45.9 billion are activated per token. To better unlock the long context capabilities of the model, MiniMax-Text-01 adopts a hybrid architecture that combines Lightning Attention, Softmax Attention and Mixture-of-Experts (MoE).
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