
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.
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Google AI Studio is an all-in-one environment designed for building AI-first applications with Google’s latest models. It supports Gemini, Imagen, Veo, and Gemma, allowing developers to experiment across multiple modalities in one place. The platform emphasizes vibe coding, enabling users to describe what they want and let AI handle the technical heavy lifting. Developers can generate complete, production-ready apps using natural language instructions. One-click deployment makes it easy to move from prototype to live application. Google AI Studio includes a centralized dashboard for API keys, billing, and usage tracking. Detailed logs and rate-limit insights help teams operate efficiently. SDK support for Python, Node.js, and REST APIs ensures flexibility. Quickstart guides reduce onboarding time to minutes. Overall, Google AI Studio blends experimentation, vibe coding, and scalable production into a single workflow.
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Gemini 3.5 Pro
Gemini 3.5 Pro is Google’s expected flagship Pro model for the Gemini 3.5 generation, built for users who need advanced intelligence across reasoning, coding, multimodal analysis, and agentic execution. The model is positioned as a higher-capability option for complex work that requires stronger planning, deeper instruction following, and more reliable handling of multi-step tasks. It is expected to serve demanding use cases such as software engineering, research synthesis, data analysis, enterprise automation, AI agents, and advanced productivity workflows. Gemini 3.5 Pro will likely expand on the Gemini 3 model family’s focus on state-of-the-art reasoning, tool use, and multimodal understanding. Unlike Flash models, which prioritize speed and cost efficiency, Gemini 3.5 Pro is expected to prioritize maximum capability for more difficult and high-value tasks. Developers may use it to build coding assistants, autonomous agents, technical copilots, business analysis tools, and applications that need to process complex context. Its anticipated strengths include long-horizon task execution, advanced code generation, structured problem solving, and improved performance on workflows that require careful reasoning. Gemini 3.5 Pro is not yet broadly documented as a generally available model, so businesses should treat it as an upcoming release rather than a fully launched product. Once available, it is expected to become a strong option for teams that want Google’s most capable Gemini 3.5 model for serious AI application development.
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Gemini 3.6 Flash
Gemini 3.6 Flash is Google’s workhorse Flash model for developers and enterprises building production AI agents at scale. The model is designed to deliver higher quality than Gemini 3.5 Flash while improving token efficiency, latency, and overall task cost. Google says Gemini 3.6 Flash uses 17% fewer output tokens than 3.5 Flash on the Artificial Analysis Index and can show even larger efficiency gains on certain software engineering benchmarks. It is priced lower than 3.5 Flash at $1.50 per 1 million input tokens and $7.50 per 1 million output tokens. Gemini 3.6 Flash improves performance in coding, ML research, computer use, knowledge work, document parsing, chart analysis, report drafting, and data-heavy workflows. The model also supports built-in computer use through the Gemini API and Gemini Enterprise, making it more useful for agentic systems that need to operate across digital environments. Google highlights customer use cases involving financial transcript analysis, code migrations, visual workflows, and interactive design tools. The model includes enhanced Frontier Safety safeguards for CBRN and cyber offense misuse while aiming to reduce unnecessary refusals for beneficial uses. By combining efficiency, stronger reasoning, multimodal ability, computer use, and enterprise availability, Gemini 3.6 Flash gives teams a practical model for scaling AI agents in production.
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