Zephyr 7B
Zephyr 7B is Hugging Face's entry in a crowded field. Context window: 0.032K tokens.
Context
32K
Input
Free (open)
Key Specifications
Arena Rank
Not disclosed
Context Window
32K
Input Price
per 1M tokens
Free (open)
Output Price
per 1M tokens
Free (open)
Parameters
7B
Open Source
Best For
About Zephyr 7B
Zephyr 7B, developed by Hugging Face, is an open-source instruction-tuned model with 7 billion parameters and a 32K token context window. The model was created using Direct Preference Optimization (DPO) on the Mistral 7B base, demonstrating that efficient alignment techniques could produce strong chat and instruction-following capabilities without expensive RLHF training. Zephyr excels at conversational AI, instruction following, and lightweight deployment tasks. Free and open-source, it runs on a single consumer GPU, making it one of the most accessible capable chat models available. The model is notable for its training methodology rather than raw scale, proving that DPO alignment can be a practical, cost-effective alternative to reinforcement learning from human feedback. Zephyr 7B has been widely studied in the alignment research community and remains popular for edge deployment and educational applications.
Pricing per 1M tokens
Input Tokens
Free (open)
Output Tokens
Free (open)
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