> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pawa-ai.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Introduction

> Pawa AI model includes powerful small language models in language, voice, audio, multimodal, embeddings, parsing etc... such as Pawa Ember and Pawa Blaze that supports swahili, english and other African languages. Our ecosystem is designed to support innovation at every level, while reduce cost of AI to almost $0.

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      <h2 className="text-3xl font-bold mb-4">Introducing Pawa Blaze</h2>

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        We're thrilled to introduce Pawa Blaze, our latest advanced small language model with reasoning, agentic, multimodal, knowledge-heavy tasks and optimized
        for multilingual understanding and long-context applications.
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          <h3 className="text-lg font-medium text-neutral-400 mb-1">Modalities</h3>
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          <h3 className="text-lg font-medium text-neutral-400 mb-1">Context window</h3>
          <p className="text-sm font-semibold">1M</p>
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            <span className="text-neutral-200 text-sm">Low cost</span>
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      Test model
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Here, you’ll find detailed information about model capabilities, inputs/outputs, supported use cases, and examples to help you get started quickly.

Our model family includes:

* **Pawa Ember** → A smaller, faster small language model(SLM) designed for efficiency, real-time interaction, and lightweight deployments.
* **Pawa Blaze** → A powerful small language model (SLM) optimized for reasoning, complex generation, multimodal, tools understanding, agentic workflow, and advanced knowledge tasks.
* **Pawa Text-to-Speech (TTS)** → Natural and expressive voice generation for conversational AI, narration, and accessibility.
* **Pawa Speech-to-Text (STT)** → Accurate and scalable speech recognition for transcriptions, voice commands, and real-time interaction.
* **Pawa Embeddings** → High-quality vector representations for semantic search, clustering, and personalization.
* **Pawa Parsing** → Structured extraction and data understanding for unstructured text, enabling automation and insights.