# Low Latency

Cloudflare AI Agents is a platform built on Cloudflare Workers and Workers AI, designed to help developers build AI agents capable of autonomously executing tasks. The platform provides the `agents-sdk` and other tools enabling developers to quickly create, deploy, and manage AI agents. Key advantages include low latency, high scalability, cost-effectiveness, and support for complex task automation and dynamic decision-making. Cloudflare's globally distributed network and Durable Objects technology provide robust foundational support for AI agents.

DeepEP is a communication library specifically designed for Mixture-of-Experts (MoE) and Expert Parallel (EP) models. It provides high-throughput and low-latency fully connected GPU kernels, supporting low-precision operations (such as FP8). The library is optimized for asymmetric domain bandwidth forwarding, making it suitable for training and inference pre-filling tasks. Furthermore, it supports Stream Multiprocessor (SM) count control and introduces a hook-based communication-computation overlap method that doesn't consume any SM resources. While its implementation differs slightly from the DeepSeek-V3 paper, DeepEP's optimized kernels and low-latency design enable excellent performance in large-scale distributed training and inference tasks.

Hibiki is an advanced model focusing on streaming voice translation. It generates accurate translations in real time by accumulating sufficient contextual information, supporting both voice and text translation, and facilitating voice conversion. The model is based on a multi-stream architecture, capable of simultaneously processing source and target speech, producing continuous audio streams and timestamped text translations. Its main advantages include high-fidelity voice conversion, low-latency real-time translation, and compatibility with complex reasoning strategies. Hibiki currently supports translation from French to English and is suitable for efficient real-time translation scenarios, such as international conferences and multilingual live events. The model is open-source and free, making it ideal for developers and researchers.

Gemini 2.0 signifies a significant advancement in generative AI from Google, representing state-of-the-art artificial intelligence technology. With its robust language generation capabilities, it offers efficient and flexible solutions for developers, suitable for a variety of complex scenarios. Key advantages of Gemini 2.0 include high performance, low latency, and a simplified pricing strategy aimed at reducing development costs and boosting productivity. This model is provided via Google AI Studio and Vertex AI and supports multiple modality inputs, showcasing vast application potential.

Mistral Small 3 is an open-source language model introduced by Mistral AI, featuring 24 billion parameters and operating under the Apache 2.0 license. This model is specifically engineered for low latency and efficient performance, making it suitable for generative AI tasks that require rapid responses. It achieves an accuracy rate of 81% on the Multi-Task Language Understanding (MMLU) benchmark and can generate text at a speed of 150 tokens per second. Mistral Small 3 aims to provide a powerful foundational model for local deployment and customizable development across various industry applications, such as financial services, healthcare, and robotics. The model has not been trained using reinforcement learning (RL) or synthetic data, placing it in the early stages of the production pipeline and making it suitable for building inference capabilities.

SpeechGPT 2.0-preview is an advanced voice interaction model developed by the Natural Language Processing Laboratory at Fudan University. It employs vast amounts of voice data for training, achieving low-latency and highly natural speech interaction capabilities. The model simulates various emotional, stylistic, and role-based voice expressions while supporting tool invocation, online search, and access to external knowledge bases. Key advantages include strong voice style generalization, multi-role simulation, and low-latency interaction experience. Currently, the model supports Chinese voice interaction, with plans to expand to more languages in the future.

Flash is ElevenLabs' latest text-to-speech (TTS) model, generating speech at a speed of 75 milliseconds plus application and network latency, making it the preferred choice for low-latency, conversational voice agents. Flash v2 supports only English, while Flash v2.5 supports 32 languages, consuming 1 credit point for every two characters. In blind tests, Flash consistently outperformed other low-latency models, proving to be the fastest with guaranteed quality.

CosyVoice 2 is a voice synthesis model developed by Alibaba Group's SpeechLab@Tongyi team. It is based on supervised discrete speech labels and combines two popular generative models: language models (LMs) and flow matching, achieving high naturalness, content consistency, and speaker similarity in voice synthesis. This model plays a significant role in multimodal large language models (LLMs), particularly in interactive experiences where response latency and real-time factors are crucial for speech synthesis. CosyVoice 2 enhances the utilization of speech label codebooks through limited scalar quantization, simplifies the text-to-speech language model architecture, and designs a block-aware causal flow matching model to adapt to various synthesis scenarios. It has been trained on large-scale multilingual datasets, achieving human-equivalent synthesis quality with extremely low response latency and real-time performance.

Toolhouse is an efficient one-click deployment platform for AI applications, providing optimized cloud infrastructure to reduce inference time, save token usage, deliver low-latency tools, and offer optimal latency services at the edge. With only 3 lines of code required for integration, Toolhouse's SDK is compatible with all major frameworks and LLMs, saving developers weeks of development time.

The Realtime API, launched by OpenAI, is a low-latency voice interaction API that enables developers to create fast voice-to-voice experiences within their applications. This API supports natural voice-to-voice conversation and can handle interruptions, similar to the advanced voice mode of ChatGPT. It operates through a WebSocket connection and supports function calls, allowing voice assistants to respond to user requests, trigger actions, or introduce new contexts. With this API, developers no longer need to combine multiple models to construct voice experiences; instead, they can achieve natural conversational interactions through a single API call.

Groq is a company that provides high-performance AI chips and cloud services, focusing on ultra-low latency inference for AI models. Since the launch of its product GroqCloud? in February 2024, it has been utilized by over 467,000 developers. The AI chip technology of Groq is supported by Yann LeCun, Chief AI Scientist at Meta, and has secured $640 million in funding led by BlackRock, resulting in a company valuation of $2.8 billion. Groq's technological advantage lies in its seamless migration capability from other providers with just three lines of code modification, and it is compatible with OpenAI's endpoints. Groq's AI chips aim to challenge Nvidia's dominance in the AI chip market by offering faster and more efficient AI inference solutions for developers and businesses.

LLaMA-Omni is a low-latency, high-quality end-to-end speech interaction model built on the Llama-3.1-8B-Instruct architecture, aimed at achieving speech capabilities comparable to GPT-4o. The model supports low-latency speech interactions, generating text and speech responses simultaneously. It completed training in less than 3 days using only 4 GPUs, demonstrating its efficient training capabilities.

Tavus Conversational Video Interface (CVI) is an innovative video conversation platform that provides face-to-face interaction through digital twin technology. The platform features low latency (less than one second) instant response capability, combined with advanced speech recognition, visual processing, and conversational awareness, offering users a rich and natural conversational experience. It is easy to deploy and scale, supporting custom LLM or TTS across multiple industries and scenarios.

Voicechat2 is a fast, fully localized AI voice chat application based on WebSocket, enabling users to achieve voice-to-voice communication in a local environment. It leverages AMD RDNA3 graphics cards and Faster Whisper technology to significantly reduce voice communication latency and enhance communication efficiency. This product is tailored for developers and technical personnel who require quick responses and real-time communication.

SenseVoice is a speech foundation model with multiple speech understanding capabilities, including Automatic Speech Recognition (ASR), Language Identification (LID), Speech Emotion Recognition (SER), and Audio Event Detection (AED). It focuses on high-precision multilingual speech recognition, speech emotion recognition, and audio event detection, supporting over 50 languages and exceeding the recognition performance of the Whisper model. The model uses an autoregressive end-to-end framework, resulting in extremely low inference latency, making it an ideal choice for real-time speech processing.