deepseek-ai/DeepSeek-V3.2-Speciale
DeepSeek-V3.2-Speciale is a 685 billion parameter language model developed by DeepSeek-AI, featuring a 32768 token context length. It utilizes DeepSeek Sparse Attention (DSA) for computational efficiency in long contexts and a scalable reinforcement learning framework. This high-compute variant is specifically optimized for deep reasoning tasks and agentic AI, demonstrating proficiency comparable to or surpassing models like GPT-5 and Gemini-3.0-Pro in complex problem-solving scenarios, including mathematical and informatics olympiads.
Popular Sampler Settings
Most commonly used values from Featherless users
temperature
This setting influences the sampling randomness. Lower values make the model more deterministic; higher values introduce randomness. Zero is greedy sampling.
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top_p
This setting controls the cumulative probability of considered top tokens. Must be in (0, 1]. Set to 1 to consider all tokens.
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top_k
This limits the number of top tokens to consider. Set to -1 to consider all tokens.
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frequency_penalty
This setting penalizes new tokens based on their frequency in the generated text. Values > 0 encourage new tokens; < 0 encourages repetition.
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presence_penalty
This setting penalizes new tokens based on their presence in the generated text so far. Values > 0 encourage new tokens; < 0 encourages repetition.
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repetition_penalty
This setting penalizes new tokens based on their appearance in the prompt and generated text. Values > 1 encourage new tokens; < 1 encourages repetition.
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min_p
This setting representing the minimum probability for a token to be considered relative to the most likely token. Must be in [0, 1]. Set to 0 to disable.
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