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@@ -25,6 +25,7 @@ accross various devices, can be found [here](https://aihub.qualcomm.com/models/l
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  - **Model Type:** Text generation
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  - **Model Stats:**
 
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  - Context length: 4096
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  - Number of parameters: 8B
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  - Model size: 4.8GB
@@ -37,39 +38,19 @@ accross various devices, can be found [here](https://aihub.qualcomm.com/models/l
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  - Token generator input: 1 input token + position embeddings + attention mask + KV cache inputs
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  - Token generator output: 1 output token + KV cache outputs
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  - Use: Initiate conversation with prompt-processor and then token generator for subsequent iterations.
 
 
 
 
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  | Model | Device | Chipset | Target Runtime | Response Rate (tokens per second) | Time To First Token (range, seconds)
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  |---|---|---|---|---|---|
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- | Llama-v3-8B-Chat | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 66.14 | 0.028 - 0.92 | -- | -- |
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- | Llama-v3-8B-Chat | Samsung Galaxy S24 | Snapdragon® 8 Gen 3 | QNN | 66.14 | 0.028 - 0.92 | -- | -- |
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- | Llama-v3-8B-Chat | Samsung Galaxy S23 Ultra | Snapdragon® 8 Gen 2 | QNN | 66.14 | 0.028 - 0.92 | -- | -- |
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- | Llama-v3-8B-Chat | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 66.14 | 0.028 - 0.92 | -- | -- |
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- | Llama-v3-8B-Chat | QCS8550 (Proxy) | QCS8550 Proxy | QNN | 66.14 | 0.028 - 0.92 | -- | -- |
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  ## Deploying Llama 3 on-device
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- Please follow [this tutorial](https://github.com/quic/ai-hub-apps/tree/main/tutorials/llama)
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- to compile QNN binaries and generate bundle assets to run [ChatApp on Windows](https://github.com/quic/ai-hub-apps/tree/main/apps/windows/cpp/ChatApp) and on Android powered by QNN-Genie.
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-
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- ## Sample output prompts generated on-device
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- 1. --prompt "where is California?"
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- ```
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- ------- Response Summary --------
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- Prompt: where is California?
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- Response: California is a state located on the West Coast of
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- ```
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-
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- 2. --prompt "what is 2+3?" --max-output-tokens 30
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- ```
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- -------- Response Summary --------
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- Prompt: what is 2+3?
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- Response: 2 + 3 = 5
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- ```
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-
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- 3. --prompt "what is superposition in Quantum Physics?" --max-output-tokens 30
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- ```
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- Prompt: what is superposition in Quantum Physics?
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- Response: Superposition is a fundamental concept in quantum mechanics, which is a branch of physics that studies the behavior of matter and energy at a very
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- ```
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  - **Model Type:** Text generation
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  - **Model Stats:**
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+ - Input sequence length for Prompt Processor: 128
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  - Context length: 4096
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  - Number of parameters: 8B
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  - Model size: 4.8GB
 
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  - Token generator input: 1 input token + position embeddings + attention mask + KV cache inputs
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  - Token generator output: 1 output token + KV cache outputs
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  - Use: Initiate conversation with prompt-processor and then token generator for subsequent iterations.
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+ - Minimum QNN SDK version required: 2.27.7
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+ - Supported languages: English.
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+ - TTFT: Time To First Token is the time it takes to generate the first response token. This is expressed as a range because it varies based on the length of the prompt. The lower bound is for a short prompt (up to 128 tokens, i.e., one iteration of the prompt processor) and the upper bound is for a prompt using the full context length (4096 tokens).
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+ - Response Rate: Rate of response generation after the first response token.
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  | Model | Device | Chipset | Target Runtime | Response Rate (tokens per second) | Time To First Token (range, seconds)
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  |---|---|---|---|---|---|
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+ | Llama-v3-8B-Chat | Snapdragon 8 Elite QRD | Snapdragon® 8 Elite | QNN | 12.9262 | 0.159383 - 5.100256 | -- | -- |
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+ | Llama-v3-8B-Chat | Snapdragon X Elite CRD | Snapdragon® X Elite | QNN | 10.0367 | 0.211644 - 6.772608 | -- | -- |
 
 
 
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  ## Deploying Llama 3 on-device
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+
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+ Please follow the [LLM on-device deployment](https://github.com/quic/ai-hub-apps/tree/main/tutorials/llm_on_genie) tutorial.
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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