Nextcloud vs Owncloud: What to Choose and How Much Does It Cost?

OpenAI’s developments are undoubtedly among the best in the generative neural network market. This applies not only to ChatGPT, which generates text, but also to DALL-E, which generates images, and Sora, which generates video. However, there are many other equally effective ChatGPT alternatives, including free ones. This article focuses on them. How to Choose a ChatGPT Alternative It is worth highlighting several general parameters that allow you to clearly see the differences between existing large language model (LLM) platforms: In-depth reasoning: Support for a "Reasoning" or "Deep Thinking" feature, which improves answer accuracy. Interactive interaction: Support for a "Canvas" mode that makes working with content more interactive. Image analysis: Ability to analyze image files. Video analysis: Ability to analyze video files or links. Audio analysis: Ability to analyze audio files with speech or music. Document analysis: Ability to analyze documents in various formats, such as PDF or DOCX. Image generation: Ability to generate images, either using an internal or external model. Video generation: Ability to generate video, usually requiring a separate model. Audio generation: Ability to generate audio, in the form of speech or music. For example, for ChatGPT, depending on the subscription plan, these parameters look as follows: Feature Free Plan Paid Plans In-depth reasoning Yes Yes Interactive interaction Yes Yes Image analysis Yes Yes Video analysis No No Audio analysis No No Document analysis Yes Yes Image generation Yes Yes Video generation No Yes Audio generation Yes Yes Thus, any ChatGPT alternative can be evaluated through the lens of these parameters. 1. Gemini Gemini is a neural network created by Google in 2023. Platform: Gemini Models: Gemini Flash, Imagen, Veo Release: March 21, 2023 Developer: Google DeepMind Country: USA Capabilities The Gemini Flash language model is integrated with two other Google models: Imagen for image generation and Veo for video generation. This allows users to create images and videos directly within the Gemini chat; the results appear in the dialog window, similar to text. Additionally, Gemini is tightly connected with Google’s ecosystem, including browser and mobile applications like Gmail, Google Docs, Google Lens, and more. The experimental Canvas feature enables more interactive model interaction: editing responses, changing tone and length, refining details, and executing code. Feature Free Plan Paid Plans In-depth reasoning Yes Yes Interactive interaction Yes Yes Image analysis Yes Yes Video analysis Yes Yes Audio analysis Yes Yes Document analysis Yes Yes Image generation Yes Yes Video generation No Yes Audio generation No No Pricing Gemini Basic: Free. Provides access to basic Gemini models without deep Google ecosystem integration. Sufficient for most standard tasks. A decent free alternative to ChatGPT. Gemini Advanced: From $20/month. Provides access to the most powerful Gemini models (including experimental ones) with an extended context window for processing large volumes of information—up to 1 million tokens. 2. Claude Claude is a neural network created by Anthropic in 2023. Platform: Claude Models: Claude Release: March 14, 2023 Developer: Anthropic Country: USA Capabilities Claude’s abilities are standard for most platforms using large generative models and it can be considered as one of the best ChatGPT alternatives. However, all of Claude’s functionality is only available via a paid subscription. Unlike other platforms, it is nearly impossible to use Claude effectively for free due to numerous limitations. Feature Free Plan Paid Plans In-depth reasoning No Yes Interactive interaction No Yes Image analysis Yes Yes Video analysis No No Audio analysis No No Document analysis Yes Yes Image generation No No Video generation No No Audio generation No No Pricing Free: Limited token count, enough for 5–10 queries per day. Reduced limits, no external search, no reasoning mode, no integration with external tools. Pro: From $15/month. Increased limits, unlimited projects, external search, advanced reasoning, Google Workspace integration, and access to more Claude models. Max: From $90/month. Increased limits (up to 20x Pro), enhanced external search, access to the Claude Code agent tool, reasoning mode, early access to new features, priority request processing, and external tool integration. 3. Grok Grok is a neural network created by xAI in 2023. Platform: Grok Models: Grok, Aurora Release: November 3, 2023 Developer: xAI Country: USA Capabilities  In addition to the standard query mode, Grok offers specialized modes for specific tasks: Think: Grok spends a few seconds to minutes analyzing a query and provides a precise answer. Ideal for math, philosophy, strategy, coding, and architecture tasks. Relies solely on internal model knowledge. DeepSearch: Uses intelligent agents to search external sources for current information. Suitable for fast-changing topics like news, trends, publications, and events. DeeperSearch: An advanced version of DeepSearch, spending more time analyzing fewer sources but collecting information more thoroughly. Ideal for very narrow queries but may miss key details or focus on irrelevant sources. Grok is deeply integrated with the X platform (formerly Twitter), acting as an AI assistant and enhancing platform functionality: Grok is embedded in X’s interface: users can ask questions, analyze posts, and generate content. Grok analyzes public posts in real-time to provide up-to-date information on news, trends, and public opinion. Grok is trained on X data using xAI’s Colossus supercomputer. The Aurora model integrated into Grok allows generating photorealistic images directly within the chat. Grok also works without authorization, though dialogues are not saved in history in that mode. Feature Free Plan Paid Plans In-depth reasoning Yes Yes Interactive interaction Yes Yes Image analysis Yes Yes Video analysis No No Audio analysis No No Document analysis Yes Yes Image generation Yes Yes Video generation No No Audio generation No No Pricing Grok Basic: Free. Limited queries and images every 2 hours (exact numbers not disclosed), limited access to Thinking, DeepSearch, and DeeperSearch modes, and a limited context window. SuperGrok: From $30/month. 100 queries and images every 2 hours, 30 queries for Thinking, DeepSearch, and DeeperSearch each every 2 hours, extended context window. 4. Qwen Qwen is a neural network created by Alibaba in 2023. Platform: Qwen Models: Qwen Release: August 25, 2023 Developer: Alibaba Country: China Capabilities The Qwen‑Turbo model available on paid plans features a record-long context—up to 1,000,000 tokens. All Qwen models are multimodal, capable of processing text, images, video, and audio as input and output. Qwen’s main strength is its ability to work with a wide variety of multimedia content. Feature Free Plan Paid Plans In-depth reasoning Yes Yes Interactive interaction Yes Yes Image analysis Yes Yes Video analysis Yes Yes Audio analysis Yes Yes Document analysis Yes Yes Image generation Yes Yes Video generation Yes Yes Audio generation Yes Yes Pricing Qwen Basic: Free trial access, 1 million tokens per basic model for 180 days. Qwen Max / Plus / Turbo: Pay-as-you-go via Alibaba Cloud Model Studio. Three models differ in maximum context, quality, and generation speed. Model Context Quality Speed Input Cost Output Cost Qwen-Max 30,000 tokens High Slow $1.6/million tokens $6.4/million tokens Qwen-Plus 130,000 tokens Medium Medium $0.4/million tokens $1.2/million tokens Qwen-Turbo 1,000,000 tokens Low Fast $0.05/million tokens $0.2/million tokens 5. Mistral Mistral is a neural network created by Mistral AI in 2023. Platform: Le Chat Models: Mistral, Flux Release: September 27, 2023 Developer: Mistral AI Country: France Capabilities The first thing that stands out is how fast Mistral generates responses. No other model matches this speed. In this aspect, you could say that Mistral is better than ChatGPT. Additionally, the smooth animation of messages appearing in the chat window provides a genuinely pleasant user experience. Despite the high speed, Mistral’s responses are accurate and relevant, containing only key information without unnecessary filler. Mistral does not allow manually enabling a deep reasoning mode with access to external sources. Instead, the neural network automatically gathers information from the Internet when it deems necessary. In this sense, Mistral works “out of the box”—no additional settings are required. The user writes a query and receives a response almost instantly. For image generation, Mistral uses the Flux model from a third-party developer, Black Forest Labs. Feature Free Plan Paid Plans In-depth reasoning No No Interactive interaction Yes Yes Image analysis Yes Yes Video analysis No No Audio analysis No No Document analysis Yes Yes Image generation Yes Yes Video generation No No Audio generation No No Pricing Free: Access to the latest advanced Mistral models, data collection from external sources, file upload, advanced data analysis, image generation, and fast responses. Pro: From $14/month. Unlimited high-performance Mistral model, unlimited daily messages, advanced external data collection, advanced image generation, and extended fast response limits. Team: From $24/month. Advanced generation and data collection capabilities, centralized management and administration, and a dedicated support channel from Mistral AI. 6. DeepSeek DeepSeek is a neural network created by High-Flyer in 2023. Platform: DeepSeek Models: DeepSeek Release: November 2, 2023 Developer: High-Flyer Country: China Capabilities DeepSeek provides unlimited functionality completely free of charge, reserving the right to charge only for API usage. However, DeepSeek lacks extensive multimodal capabilities: it does not generate images, video, or audio, though it can analyze images and documents. It also does not have a Canvas-like tool for interactive work with responses (and code), common in many LLM platforms. Nevertheless, DeepSeek has standard reasoning (DeepThink) and search (Search) functions. Feature Free Plan Paid Plans In-depth reasoning Yes Yes Interactive interaction No No Image analysis Yes Yes Video analysis No No Audio analysis No No Document analysis Yes Yes Image generation No No Video generation No No Audio generation No No Pricing Browser Access: Free. Normal mode (deepseek-chat) has no limits; DeepThink mode (deepseek-reasoner) allows up to 50 messages per session. API Access: Pay-per-token for input and output; necessary only for API usage. Pricing varies by mode. Mode 1M Tokens Input 1M Tokens Output deepseek-chat $0.27 $1.10 deepseek-reasoner $0.55 $2.19 7. Reka Reka is a neural network created by Reka AI in 2024. Platform: Reka Models: Reka Release: April 18, 2024 Developer: Reka AI Country: USA Capabilities Reka can feel somewhat rough: it occasionally misinterprets context and incorrectly analyzes provided documents and media files. However, for text generation or open-source information retrieval, the model performs reasonably well. Reka’s chat includes integrated agents: Reka Vision Agent: Analyzes images. Reka Research Agent: Searches for information in open sources. Reka Speech Agent: Translates and transcribes audio in real time; a demo version is available. Reka’s main feature is the interactive Space, where texts and images can be placed. While most people interact with LLMs through standard chat, the interactive space adds visual clarity during text generation. Feature Free Plan Paid Plans In-depth reasoning Yes Yes Interactive interaction Yes Yes Image analysis Yes Yes Video analysis Yes Yes Audio analysis Yes Yes Document analysis No No Image generation No No Video generation No No Audio generation No No Pricing Browser Access: Free. Standard capabilities with no restrictions. API Access: Pay-per-token. Three model versions available in ascending power: Spark, Flash, and Core. Version Cost per 1M Input Tokens Cost per 1M Output Tokens Reka Spark $0.05 $0.05 Reka Flash $0.8 $2 Reka Core $2 $6 8. ChatGLM ChatGLM is a neural network created by Zhipu AI in 2023. Platform: ChatGLM Models: ChatGLM, CogView, Ying Release: March 13, 2023 Developer: Zhipu AI Country: China Capabilities In addition to image and document analysis, ChatGLM can generate images with CogView and videos with Ying. Audio transcription and analysis is handled by ChatGLM Voice. Special functions for media work are provided in dedicated chats. Otherwise, ChatGLM functions similarly to other neural networks. Feature Free Plan Paid Plans In-depth reasoning Yes Yes Interactive interaction No No Image analysis Yes Yes Video analysis No Yes Audio analysis No Yes Document analysis Yes Yes Image generation No Yes Video generation No Yes Audio generation No Yes Pricing Trial: Free. Upon initial registration, 1,000,000 tokens for 30 days; after identity verification, an additional 4,000,000 tokens for 30 days. Uses the lightweight ChatGLM Flash model. Paid: Pay-as-you-go. Full multimodal and generative capabilities, with four model versions in ascending power: Lite, Turbo, Std, and Pro. Version Cost per 1M Tokens ChatGLM Lite $0.28 ChatGLM Turbo $0.69 ChatGLM Std $0.69 ChatGLM Pro $1.39 Aggregator Platforms / Intermediaries There is a separate category of content generation platforms, acting as intermediaries or aggregators. Essentially, they are standard chatbots but rely on third-party models mentioned above. Platform Models Release Developer Country Microsoft Copilot GPT Feb 7, 2023 Microsoft USA You.com GPT Nov 9, 2021 YouChat USA Poe GPT, o, Claude, Llama, Gemini, Mistral, Qwen, DeepSeek Dec 21, 2022 Poe USA HuggingChat Llama, DeepSeek, Mistral, Qwen, C4AI Apr 25, 2023 Hugging Face USA Nova GPT, Gemini, Claude, DeepSeek Dec 3, 2024 HUBX USA Duck.ai GPT, o, Llama, Claude, Mistral Mar 10, 2025 DuckDuckGO USA This category also includes specialized external search services using intelligent agents to collect information. They also use third-party generative models, most often OpenAI GPT. Platform Models Release Developer Country Perplexity GPT Dec 7, 2022 Perplexity AI USA Andi GPT Jan 26, 2023 Andi USA Phind Llama Feb 23, 2023 Phind USA How to Choose a Platform AI benchmarks show significant differences in task performance for each model, but these reflect controlled “lab” conditions. In typical tasks, the differences are less noticeable, though they exist. Pricing structures are similar: basic functionality is free, enhanced features require payment, often on a pay-per-token basis. Some platforms are multimodal: they can generate text, images, video, and audio. Others can analyze multimedia data, but only generate text. When looking for an AI tool like ChatGPT, it makes sense to test several platforms for a given task and then select one or two. Suggested approach: Define requirements clearly. Identify key requirements based on the project and its tasks. Evaluate core platform parameters. Compare the requirements against the platform’s capabilities, especially generative features and ecosystem integration. Compare platforms. Select the most suitable platforms based on how well their characteristics align with project needs. Test selected platforms. Evaluate performance in real tasks to determine the best fit. Choose the most suitable platform. You don’t have to pick only one. Keep a couple of backups for tasks where they might outperform the main platform.

In mid-2025, Google introduced the third version of its proprietary video generator: Veo. The new model not only creates high-quality visuals but also provides realistic audio tracks, including environmental sounds and character dialogues. In a sense, Google has created something entirely new—something revolutionary—a technology capable of making a quantum leap in video generation. Thanks to this, distinguishing real videos from AI-generated ones will soon become much more difficult. That’s why it’s important to understand what the new Veo 3 neural network is and which special tools Google provides for working with it. Let’s explore this in detail. What Is Google Veo 3 Google Veo is a generative model for creating videos, developed and released by Google in mid-2024. Its main innovation is the native ability to generate audio: sound effects, background music, and dialogues synchronized with lip movements. A frame from one of the official videos generated using Google Veo 3 The audio track of generated videos automatically adapts to the context of the scene, adding appropriate effects as needed: natural sounds, urban ambiance, musical accompaniment, and even human speech with dialects and accents specific to the characters. Thus, the Veo 3 artificial intelligence combines high-quality visuals, realistic physics, and synchronized audio. Features of Veo 3 The updated Veo 3 model has a number of features that distinguish it from other AI video generation services: Longer duration. The duration of generated videos can exceed the standard five seconds common for many AI video generators. The maximum video length is eight seconds. Synchronized audio support. Video is accompanied by environmental sounds, music, and speech, all realistically synchronized with the visuals. Physical accuracy. Hyper-realistic motion of objects, materials, characters, and light throughout the video. This combination of exceptional characteristics makes Google Veo 3 an ideal tool for generating cinematic, animated, or any other videos with high visual dynamics and deep storylines. Thanks to these features, Veo 3 can already be used in professional settings: for UGC content (for example, YouTube), short ads, or even full-length films. Another frame from one of the official videos generated using Google Veo 3 For instance, filmmaker Dave Clark has already used Veo 2 and Veo 3 in several of his short films. Another director, June Lau, also places great hopes on Google’s cutting-edge model, using Veo 3 to create a short film titled Dear Strangers. Filmmaker Yonatan Dor created his own short film, The History of Influencers, using Veo 3, featuring fictional influencers from different eras. In general, the number of directors and artists integrating Google’s AI tools into their content creation process is growing rapidly. However, it’s worth noting that Veo 3 is still not enough to create a full-fledged movie; it serves best as an auxiliary tool. Capabilities of Veo 3 The new version of Veo includes several ways to generate video using different types of input data: Text-to-video. The primary method of video generation in Veo 3 is based on a detailed (preferably very detailed) text description. Image-to-video. Veo 3 can generate videos based on text or images. Moreover, any image used as input can be enhanced with a textual description that clarifies the scene’s behavior. Video-to-video. Using additional tools (Flow), users can upload existing videos and apply modifications with Veo 3: adding or removing objects, changing visual styles, adjusting camera behavior, editing object movement, and their accompanying sounds. As previously noted, Veo 3 videos integrate all attributes of traditional, non-computer-generated footage. The standard output resolution is 720p, but the upscaling feature allows increasing it up to 4K. Veo 3 Tools It’s important to note that Veo 3 cannot be used “as is”—additional Google tools are required. Flow Google offers a special tool that combines Veo (video), Imagen (images), and Gemini (text) models in a single director-style interface called Flow. Essentially, it’s Google’s central content creation platform. With Flow, users can precisely edit videos: extend frames, add new details, animate specific elements, adjust camera movement, store styles, and more. This editor is ideal for solo and manual work as it allows quick creation of short clips with instant preview and fine-tuning. Everything happens in a single window. At the same time, Flow requires minimal technical setup: no cloud account, billing, or SDK is needed; video generation happens directly within the visual interface. Demonstration of the Flow graphical interface at the Google I/O 2025 presentation (Kerry Wan/ZDNET) Gemini With the Gemini LLM neural network, users can generate precise prompts for video generation via Flow. In simple terms, Gemini serves as a converter that transforms more human-style text descriptions into more machine-readable ones, though both are still in natural language and easy to understand. For example, you can find an image online or generate one using another AI tool (e.g., Midjourney), attach it to a message in the Gemini chatbot (or any other LLM), and provide an additional description: “I need precise prompt is needed for Google Veo 3 to generate a short video from this image, where three men are pushing a banana-shaped car with a driver at the wheel, and as the car gains speed, it gradually turns yellow.” Gemini will then generate a complete prompt for video generation and include explanatory comments, for example: “A vintage car, half-peeled banana, driven by a man in a hat, is being pushed by three other men from behind. The car is initially in black and white, but as it gains momentum and the men push harder, the banana part of the car gradually becomes fully ripe yellow. The background shows a field with trees in the distance, also in black and white. Dynamic camera movement, tracking the car as it accelerates.” This way, you can generate a video based on a reference image by following a simple sequence of steps: Generate a prompt for image generation using an LLM (based on a description). Generate the image (based on the prompt). Generate a prompt for video generation (based on the description and image). Generate the video (based on the prompt). Alternatively, you can use a ready-made reference image from the Internet: Generate a prompt for video generation (based on the description and image). Generate the video (based on the prompt). In a simplified version, you can also generate a video without using any reference images: Generate a prompt for video generation (based on the description). Generate the video (based on the prompt). Or, you can manually write the prompt for video generation from scratch :) Nevertheless, Gemini (naturally, in paid tiers) also allows generating videos using Veo 3. However, in most cases, Flow is used for video creation as it’s more convenient and visually intuitive. After all, Gemini is primarily designed for working with text rather than video. Vertex AI The Vertex AI platform represents an enterprise solution for large-scale cloud-based content generation and asset storage, that is, various media files needed for creating images and videos. In essence, it’s a fully managed platform for developing, training, deploying, and maintaining AI models. It brings together all the tools needed for every stage of the machine learning cycle, from data preparation to model performance monitoring. Thus: Flow provides a convenient and visual approach. Gemini delivers accurate and relevant prompts. Vertex AI ensures a reliable and scalable infrastructure. Together, they turn Veo 3 from an experimental service into a professional tool capable of solving real-world challenges across a wide variety of projects. How to Use Veo 3: Step-by-Step Guide After understanding the main tools, we can now look at how to generate a video using Veo 3. First of all, it’s important to note that to use Google Veo 3, you must have one of Google AI’s paid subscriptions: Google AI Pro. Expands the basic functionality of Google’s AI tools. Starting at $19 per month. Google AI Ultra. Offers maximum, virtually unlimited content-generation capabilities. Starting at $249 per month. There’s no other official way to use Veo 3 within the Google ecosystem. A paid subscription is required. The only exceptions are third-party intermediary services or Telegram bots that provide Veo 3 video generation on a pay-per-video basis. Another important detail: the Flow editor is only available in English. Moreover, prompts for Veo 3 must be written in English. The only exception is dialogue lines: they can be written in any other language, and Veo 3 will perfectly reproduce the described characters’ dialects. Such a level of synchronization between sound and video, with extraordinary precision, amazes (and sometimes even frightens) people well-acquainted with modern technology. Working with such a powerful generative model usually requires additional tools for convenient use. Therefore, Google offers several ways to interact with Veo 3, differing in their complexity. Using Flow Flow allows you to create scenes, control camera movement, manage assets, and edit clips, all without third-party tools. Essentially, it’s an intuitive visual editor for creating videos with Veo 3. Using it is simple: Sign in. On the Flow homepage, log in with your Google account. Create a project. Click the New project button. A page will open where you can enter a text prompt describing the desired video and its audio track. Choose input type. On the prompt input page, select the source type for your video: Text to Video, Frames to Video, or Ingredients to Video. Choosing the latter two enables extra settings for camera behavior and frame composition. Configure settings. On the same page, you can set generation parameters: the number of variants per prompt (1–4) and the model used (Veo 2 Fast, Veo 2 Quality, Veo 3 Highest Quality). Depending on the settings, each generation consumes 10–100 Flow credits. Enter the prompt. Type your text prompt in the input field. Generate. After entering the prompt, click the arrow button and wait 2–7 minutes. The generated videos and prompts will appear in the request history above the input field. This is Flow’s basic functionality. In many ways, it resembles LLM chatbots, only instead of text, it produces video. Naturally, Flow also includes advanced tools for composing and editing video clips. Using Gemini To generate a video directly in the Gemini chatbot, follow these simple steps: Sign in. Log in to Gemini with your Google account. After successful sign-in, the chat interface opens. Activate video mode. Click the Video button next to the message input field to switch to video generation mode. This button is only available to users with a paid plan. Enter the prompt. In the input field, describe the desired video in detail: environment, characters, lighting, camera behavior, style, and other details. Generate. Click the arrow button or press Enter. The generation process takes 2–7 minutes, and the finished video will appear directly in the chat window. Thus, Gemini unifies the generation of text (Gemini), images (Imagen), and video (Veo) in a single interface, which is quite convenient. Of course, Gemini alone isn’t enough for professional video work—you’ll also need Flow and dedicated video-editing software. However, for presentations or idea visualization, Gemini is more than sufficient. Using Vertex AI Another way to use the Veo 3 model is through Vertex AI. Unlike Flow, which is built for creative work, Vertex AI is designed for professional, large-scale, and automated content creation. Here’s a short sequence for generating videos with Vertex AI: Sign in. Log in to Google Cloud Console with your Google account, then navigate to the Vertex AI section. Open Media Studio. From the left sidebar, select Media Studio, and the page for choosing media generation models will open. Choose Veo. Enter the prompt. On the next page, enter the text description of your video and configure the main parameters. Generate. Click Generate and wait a few minutes for the video to appear in the interface. Vertex AI provides distributed computing, cost monitoring, asset storage, and ML-process management, all centralized in Google Cloud. Thanks to the REST API, the platform also allows programmatically launching hundreds of video generations, integrating Veo 3 into third-party applications. Pros and Cons of Veo 3 Google Veo 3 opens new horizons for automated video production, combining advanced audio generation with high-quality visualization. Understanding its strengths and weaknesses helps identify optimal use cases. Advantages: Visual and physical realism. Beyond realistic lighting, shadows, textures, and details, the model simulates accurate physical behavior of objects, substances, and characters. Audio-video synchronization. Native audio generation (sound effects, music, dialogues) is tightly synchronized with the visuals. Advanced prompt interpretation. Deep understanding of complex queries: mood, style, camera perspective (panning, zoom). Extensive creative control enables frame-to-frame consistency, maintaining stable characters and environments across angles. Extended toolset. Integration with tools like Flow, Vertex AI, and Gemini provides a unified environment for generation, editing, and scene management. Disadvantages: Limited duration. The maximum video length (8 seconds at 24 fps) is independent of resolution. This is still short for production-scale work. Synchronization artifacts. While lip-sync accuracy is high, minor artifacts can appear, especially with background characters (unnatural lip movement or blurring). Small body parts like hands, elbows, or feet may occasionally deform. Prompt interpretation errors. The model sometimes overlooks details, misreads subtle emotions, or ignores secondary characters. High cost. Subscription plans are expensive, mostly suitable for professional studios but less accessible for students, freelancers, or solo creators. AI watermarking. Every video carries an invisible SynthID marker that can be detected via a special app. Misinformation risks. The exceptional realism of Veo 3 could enable convincing deepfakes or spread fake news, raising ethical concerns. Although Veo 3’s strengths outweigh its drawbacks, it can’t yet fully replace traditional video production. Still, it can easily serve as a powerful supplementary tool alongside classic video and graphics software. Conclusion It’s safe to say that Google Veo 3 is an innovative model that elevates AI-driven video generation to an astonishing new level. It combines realistic graphics, precise audio synchronization, and a robust physics engine. The generated videos are so realistic and coherent that untrained viewers may not notice they’re artificial—and sometimes can’t tell at all. The new version is perfect for those who need fast, high-quality short clips, from marketers and content creators to artists and filmmakers.

A hybrid cloud is an infrastructure model that combines private and public cloud services. Private clouds are owned by the company, while public clouds rely on provider resources, such as Amazon Web Services (AWS), Microsoft Azure, or Hostman. Hybrid Cloud Architecture The architecture of a hybrid cloud consists of the company’s own data center, external resources, and private hosting. These components are connected through a unified management process. The key feature of the hybrid approach is the ability to connect systems that handle business-critical data, which cannot be placed on public infrastructure, while still leveraging the advantages of external hosting, such as on-demand scaling. Hybrid Cloud Advantages Hybrid cloud addresses the limitations of both public and private cloud services. It is a compromise solution with several important benefits: Reduced computing costs compared to relying solely on in-house hardware. Flexible management: critical data can remain on private infrastructure, while less sensitive workloads can be handled by the provider. Easy scalability by using resources offered by cloud providers. Disadvantages Some drawbacks of hybrid cloud include: Integration complexity: establishing a reliable connection between private and public environments can be challenging. Risk of failure: if resources are poorly distributed or one segment fails, the entire system may be affected. Oversubscription: some providers may allocate the same resources to multiple clients. Such issues can be avoided by carefully selecting a provider. For instance, when configuring a hybrid cloud on Hostman, you can rely on expert support and guaranteed access to the resources you pay for. Use Cases Here are several examples of situations where hybrid cloud infrastructure is particularly useful: Rapid Project Scaling Suppose you run an online store. During high-traffic events like Black Friday, website traffic spikes dramatically. Cloud architecture reduces the risk of server crashes during peak loads. Additional resources can be deployed in the cloud as needed and removed once demand decreases, preventing unnecessary costs. Scalability is also crucial for big data processing. Using cloud resources is more cost-effective than maintaining a large in-house data center. Data Segregation Confidential client information can be stored in a private cloud, while corporate applications run on public cloud infrastructure. Public hosting is also suitable for storing backup copies, ensuring business continuity if the primary system encounters problems. Development and Testing External cloud resources can be used for deployment and testing, allowing teams to simulate workloads and identify bugs not visible in local environments. After validation, the new version can be deployed to the main infrastructure. Conclusion Hybrid cloud is a practical approach for companies that value flexibility and aim for rapid growth. It combines the advantages of private and public hosting, enabling multiple use cases, from quickly deploying additional resources to securely storing sensitive data and testing new products.