PerfectUsing/llama-3.1-8b-sam-v5-merged
TEXT GENERATIONPricing:Input $0.2 / Cached $0.028 / Output $0.32Concurrent Unit Cost:1Model Size:8BQuant:FP8Context Size:32kTool Calling:SupportedPublished:Sep 12, 2026License:apache-2.0Architecture:Transformer Open Weights Featherless Exclusive Cold
PerfectUsing/llama-3.1-8b-sam-v5-merged is an 8 billion parameter Llama 3.1 model, developed by PerfectUsing and fine-tuned using Unsloth for accelerated training. This model leverages the Llama 3.1 architecture, offering a 32768 token context length. Its primary differentiation lies in its efficient fine-tuning process, making it suitable for applications requiring a performant Llama 3.1 variant with optimized training.
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Model Overview
PerfectUsing/llama-3.1-8b-sam-v5-merged is an 8 billion parameter language model, fine-tuned by PerfectUsing from the unsloth/llama-3.1-8b-unsloth-bnb-4bit base model. This model benefits from being trained with Unsloth and Huggingface's TRL library, which enabled a 2x faster training process.
Key Capabilities
- Llama 3.1 Architecture: Built upon the robust Llama 3.1 foundation, providing strong general language understanding and generation capabilities.
- Efficient Fine-tuning: Utilizes Unsloth for significantly faster training, making it a good choice for developers looking for optimized Llama 3.1 variants.
- Extended Context Window: Supports a context length of 32768 tokens, allowing for processing longer inputs and maintaining coherence over extended conversations or documents.
Good For
- Applications requiring Llama 3.1: Ideal for use cases that benefit from the Llama 3.1 model family's performance.
- Developers prioritizing training efficiency: Suitable for those who need a Llama 3.1 model that has undergone an accelerated fine-tuning process.
- Tasks needing a large context window: Effective for handling complex queries or generating detailed responses that require understanding extensive contextual information.