papers/hanzo-network-architecture/sections/07-ai-inference-integration.tex

\section{AI Inference Integration}


\subsection{Qwen3 Native Embeddings}

First-class support for Qwen3 models:

\subsubsection{Qwen3-Embedding-8B}

Specifications:
\begin{itemize}
\item Parameters: 8 billion
\item Dimensions: 4096
\item Context: 32,768 tokens
\item MTEB Score: \#1 multilingual (pending)
\item Quantization: Q4K, Q8\_0 (GGUF)
\end{itemize}

\subsubsection{Qwen3-Reranker-4B}

Specifications:
\begin{itemize}
\item Parameters: 4 billion
\item Output: 768-dim relevance scores
\item Context: 8,192 tokens
\item Use case: Two-stage retrieval
\end{itemize}

\subsection{Inference Backends}

\subsubsection{Hanzo Engine}

Custom inference server (mistral.rs fork) on port 36900:

\begin{itemize}
\item OpenAI-compatible API
\item GPU acceleration (CUDA/Metal)
\item GGUF model support
\item ISQ (In-Situ Quantization)
\item Flash Attention support
\end{itemize}

\subsubsection{Multi-Provider Support}

20+ LLM providers via unified interface:
\begin{itemize}
\item OpenAI (GPT-4, GPT-3.5)
\item Anthropic (Claude 3 Opus/Sonnet/Haiku)
\item Google (Gemini Pro/Flash)
\item Ollama (local models)
\item Groq (high-speed inference)
\item DeepSeek (reasoning models)
\item Together AI, OpenRouter, Exo, Grok
\end{itemize}

\subsection{Embedding Pipeline}

\begin{algorithm}
\caption{Native Embedding Generation}
\begin{algorithmic}[1]
\REQUIRE Text input, model type
\ENSURE Embedding vector
\IF{USE\_NATIVE\_EMBEDDINGS $=$ true}
    \STATE Load GGUF model (Qwen3-Embedding-8B)
    \IF{GPU available}
        \STATE Initialize CUDA/Metal backend
    \ENDIF
    \STATE embedding $\leftarrow$ Model.encode(text)
    \IF{encoding fails}
        \STATE Fallback to Ollama server
    \ENDIF
\ELSE
    \STATE embedding $\leftarrow$ OllamaClient.embed(text)
\ENDIF
\RETURN embedding
\end{algorithmic}
\end{algorithm}

Performance:
\begin{itemize}
\item Throughput: 1000+ embeddings/sec (GPU)
\item Latency: $<$10ms per embedding (batch size 32)
\item Memory: 16GB VRAM for 8B model
\end{itemize}