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State-of-the-art large language model useful on a variety of language understanding and generation tasks.

Llama 2 is a family of LLMs. The "Chat" at the end indicates that the model is optimized for chatbot-like dialogue. The model is quantized to w4a16(4-bit weights and 16-bit activations) and part of the model is quantized to w8a16(8-bit weights and 16-bit activations) making it suitable for on-device deployment. For Prompt and output length specified below, the time to first token is Llama-PromptProcessor-Quantized's latency and average time per addition token is Llama-TokenGenerator-KVCache-Quantized's latency.

Technical Details

Number of parameters:7B
Precision:w4a16 + w8a16 (few layers)
Model-1 (Prompt Processor):Llama-PromptProcessor-Quantized
Max context length:1024
Prompt processor model size:3.6 GB
Prompt processor input:1024 tokens
Prompt processor output:1024 output tokens + KVCache for token generator
Model-2 (Token Generator):Llama-TokenGenerator-KVCache-Quantized
Token generator model size:3.6 GB
Token generator input:1 input token + past KVCache
Token generator output:1 output token + KVCache for next iteration
Decoding length:1024 (1 output token + 1023 from KVCache)
Use:Initiate conversation with prompt-processor and then token generator for subsequent iterations.

Applicable Scenarios

  • Dialogue
  • Content Generation
  • Customer Support


Source Model:LLAMA2
Deployable Model:LLAMA2


  • llm
    Large language models. Useful for a variety of tasks including language generation, optical character recognition, information retrieval, and more.
  • generative-ai
    Models capable of generating text, images, or other data using generative models, often in response to prompts.
  • quantized
    A “quantized” model can run in low or mixed precision, which can substantially reduce inference latency.

Supported Compute Chipsets

  • Snapdragon® X Elite