4.4 out of 5 stars
(182 Ratings)
Most AI video tools hand you a black box: closed weights, a subscription, and no way to see what is happening under the hood. LTX takes the opposite approach. Built by Lightricks, LTX is an open foundation model that generates and simulates across video, audio, and the physical world, and it puts the weights, the code, and the control in your hands.
At the center of the model is LTX-2.5, a 22B-parameter dual-stream diffusion transformer that produces native 4K video at up to 50 frames per second, with audio and video generated together in a single pass rather than stitched together afterward. Artificial Analysis, an independent benchmarking group, currently ranks LTX among the top three AI video models in the world.
You choose how you want to use it. Download the open weights and run LTX-2.5 on your own hardware. License the model for on-premise deployment backed by enterprise support. Or build directly on LTX Studio, the production suite that turns the model into a full creative workflow. Companies like ElevenLabs, Asteria Film Co., Magnopus, and NVIDIA already rely on LTX for their own work.
LTX is not built for one-off social clips. It is infrastructure for teams that generate motion, audio, and physical environments as part of their own products and pipelines.
Learn more about LTX
4.5 out of 5 stars
(446 Ratings)
An API powered by Google's AI technology allows you to accurately convert speech into text. You can accurately caption your content, provide a better user experience with products using voice commands, and gain insight from customer interactions to improve your service. Google's deep learning neural network algorithms are the most advanced in automatic speech recognition (ASR). Speech-to-Text allows for experimentation, creation, management, and customization of custom resources. You can deploy speech recognition wherever you need it, whether it's in the cloud using the API or on-premises using Speech-to-Text O-Prem. You can customize speech recognition to translate domain-specific terms or rare words. Automated conversion of spoken numbers into addresses, years and currencies. Our user interface makes it easy to experiment with your speech audio.
Learn more about Google Cloud Speech-to-Text
Nemotron 3.5 Transcribe
NVIDIA Nemotron 3.5 Transcribe serves as an open-weight model tailored for developers aiming to create transcription and audio-processing systems. This model transforms audio recordings into text, offering options for both verbatim and edited transcripts, along with features like contextual vocabulary, speaker identification, word-level timestamps, speech translation, language detection, and audio question answering. It boasts a language matrix that encompasses 40 different languages, though the extent of task coverage may vary from one language to another. Capable of processing recordings of up to one hour, the model is optimized for offline inference on compatible NVIDIA GPU hardware and supported runtimes. Developers can seamlessly integrate it into a variety of applications, including speech interfaces, media and meeting processing, customer service analytics, translation software, and other audio comprehension tools. Furthermore, the model's weights, alongside a fine-tuning toolkit, are made available under the OpenMDW-1.1 license, with specific hardware and serving requirements contingent upon the nature of the deployment. This flexibility allows teams to adapt the model for diverse use cases in the field of audio processing and transcription.
Learn more about Nemotron 3.5 Transcribe
Muse Spark Open
5.0 out of 5 stars
(1 Rating)
Muse Spark Open is an open-weight foundation model developed by Meta to support multimodal reasoning, autonomous agents, and complex software development tasks. The model features 816 billion total parameters with approximately 42 billion active parameters and a context window supporting up to one million tokens. Its architecture is designed to process multimodal information while maintaining context across lengthy workflows, extensive codebases, and multistep assignments. Muse Spark Open provides capabilities for software engineering, code generation, debugging, application development, and automated testing. Its agentic functionality supports external tool interactions, task planning, computer-based workflows, and execution of complex objectives over extended sessions. The model can run locally using two Apple M5 Ultra Mac Studio systems with the MLX framework, enabling organizations to process information without relying on hosted inference services. Developers can deploy the model through SGLang, vLLM, TensorRT-LLM, Hugging Face Transformers, llama.cpp, and other supported inference engines. Customization is supported through PyTorch and TorchTitan, allowing organizations to adapt the model to specialized applications and workflows. Muse Spark Open is distributed under the Muse Model License and is available through Hugging Face, major cloud model repositories, and hosted API providers including Together AI, Fireworks AI, and OpenRouter.
Learn more about Muse Spark Open