RapidS0C/QFT3-V2-seneca-x-deepseek-r1-distill-qwen-32b-v1.3-safe-merged

TEXT GENERATIONPricing:Input $2.72 / Output $4.8Concurrent Unit Cost:2Model Size:32.8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:May 12, 2025Architecture:Transformer0.0K Featherless Exclusive Cold

The RapidS0C/QFT3-V2-seneca-x-deepseek-r1-distill-qwen-32b-v1.3-safe-merged model is a 32.8 billion parameter language model. This model is a merged and distilled variant, indicating a focus on combining capabilities from different base models like DeepSeek and Qwen. Its specific differentiators and primary use cases are not detailed in the provided information, suggesting it may be a general-purpose model or one with specialized but undisclosed optimizations.

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Model Overview

This model, named RapidS0C/QFT3-V2-seneca-x-deepseek-r1-distill-qwen-32b-v1.3-safe-merged, is a 32.8 billion parameter language model. It is identified as a merged and distilled model, suggesting it integrates characteristics from underlying architectures such as DeepSeek and Qwen. The specific methodologies for merging and distillation, or the particular strengths derived from this process, are not detailed in the provided model card.

Key Characteristics

  • Parameter Count: 32.8 billion parameters.
  • Context Length: Supports a context length of 32,768 tokens.
  • Model Type: A merged and distilled model, implying a combination of features from its constituent base models.

Intended Use Cases

The provided model card does not specify direct or downstream use cases, nor does it detail particular strengths or optimizations for specific tasks. Users should exercise caution and conduct their own evaluations to determine suitability for their applications. The model card also notes that more information is needed regarding its development, funding, specific model type, language support, license, and finetuning origins.

Limitations and Recommendations

As with many large language models, users should be aware of potential biases, risks, and technical limitations. The model card explicitly states that more information is needed to provide further recommendations regarding these aspects. It is recommended that both direct and downstream users understand these inherent risks before deployment.

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2 models