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In recent years, the development of large language models (LLMs) has become one of the key areas in the field of artificial intelligence. From the first experiments with recurrent and convolutional networks, researchers gradually moved to attention-based architectures—the Transformer, proposed in 2017 by Google’s team. This breakthrough paved the way for scaling models capable of processing enormous volumes of textual data and generating coherent, meaningful answers to a wide variety of questions. Against the backdrop of Western dominance, the work of Chinese research groups is attracting more and more attention. The country is investing significant resources into developing its own AI platforms, seeking technological independence and a competitive advantage in the global market. One of the latest embodiments of these efforts is the DeepSeek neural network, which combines both the proven achievements of the Transformer architecture and its own innovative optimization methods. In this article, we will look at how to use DeepSeek for content generation, information retrieval, and problem solving, as well as compare its characteristics with Western and domestic counterparts. What is DeepSeek AI and How It Works DeepSeek is a large language model (LLM) developed and launched by the Chinese hedge fund High-Flyer in January 2025. At its core lies the transformer architecture, distinguished by a special attention mechanism that allows not only analyzing fragments of information in a text but also considering their interconnections. In addition to the transformer foundation, DeepSeek employs several innovations that may be difficult for a non-technical person to grasp, but we can explain them simply: Multi-Head Latent Attention (MLA). Instead of storing complete “maps” of word relationships, the model keeps simplified “sketches”—compact latent vectors. When the model needs details, it quickly “fills in” the necessary parts, as if printing out a fragment of a library plan on demand rather than carrying around the entire heavy blueprint. This greatly saves memory and speeds up processing, while retaining the ability to account for all important word relationships. Mixture-of-Experts (MoE). Instead of a single universal “expert,” the model has a team of virtual specialists, each strong in its own field: linguistics, mathematics, programming, and many others. A special “router” evaluates the incoming task and engages only those experts best suited for solving it. Thanks to this, the model combines enormous computational power with efficient resource usage, activating only the necessary part of the “team” for each request. Thus, DeepSeek combines time-tested transformer blocks with the innovative MLA and MoE mechanisms, ensuring high performance while relatively conserving resources. Key Capabilities of DeepSeek: From Code to Conversations The DeepSeek neural network can generate and process various types of content, from text and images to code and documents: Dialogues. Builds natural human-like conversations with awareness of previous context. Supports many tones of communication, from formal to informal. Manages long-session memory up to 128,000 tokens of context. Exploring specific topics. Instantly responds to queries across a wide range of fields: science, history, culture. Collects information from external sources to provide more accurate data. Creative writing and content generation. Generates ideas and assists in writing articles, stories, scripts, slogans, marketing texts, narratives, poems, and other types of textual content. Code generation and understanding. Performs any code-related tasks in the most popular programming languages: writing, autocompletion, refactoring, optimization, inspection, and vulnerability detection. Moreover, the model can generate unit tests and function documentation. Essentially, DeepSeek can do everything a human programmer can.Supported languages include: C, C++, C#, Rust, Go, D, Objective-C, JavaScript, TypeScript, HTML, CSS, XML, PHP, Ruby, Python, Perl, Lua, Bash/Shell/Zsh, PowerShell, Java, Kotlin, Swift, Dart, Haskell, OCaml, F#, Erlang, Elixir, Scala, Clojure, Lisp/Scheme, SQL, JSON, Markdown, and many more. Document and website analysis. Summarizes the contents of documents, condenses information from external sites, extracts key ideas from large texts. Translation from foreign languages. Translates text into dozens of languages while preserving original terminology and style. In short, anything that can be done with textual data, DeepSeek can do. The only limits are the imagination of the user. DeepSeek Chatbot: Three Key Modes The DeepSeek chatbot offers three core modes, each optimized for different types of tasks and depth of processing: Normal. Fast and lightweight answers to common questions. Has a limited context window but provides relatively high-quality responses with minimal delay. Suitable for direct factual queries: definitions, short explanations, notes. DeepThink. In-depth analytical research with complex reasoning. Has an expanded context window but requires much more time to generate responses. Performs multi-step processing, breaking tasks into sub-tasks. Uses a “chain of thought” method, forming intermediate conclusions for the final answer. Suitable for logic-heavy queries: solving math problems, writing essays, detailed analysis of scientific articles, comprehensive strategic planning. Search. Thorough analysis of external sources to provide up-to-date information. Automatically connects to the internet to search for current data, news, statistics. Uses specialized APIs and search engines, verifies sources, processes results, cross-checks facts, filters out irrelevant information. Suitable for finding fresh data and fact-checking. Comparative Table of Modes Mode Response Speed Context Size Depth of Analysis External Sources Normal high limited low no DeepThink low maximum high no Search medium variable medium yes Thus, if you just need a quick answer, use Normal mode. For deep reasoning and detailed justifications, choose DeepThink. To obtain the latest verified data from external sources, use Search. How to Use DeepSeek: Interface, Access, and Launch Although DeepSeek AI does not exist within a vast ecosystem (like Google’s Gemini), the neural network offers several ways to interact with it. Option 1. Remote Application In the simplest case, there are three ways to interact with the model hosted on DeepSeek’s remote servers: Desktop browser app Android mobile app iOS mobile app All options provide dialogue with the model through a chatbot. In every case, the user interface includes a dialogue window, a message input field, file attachment buttons, and a panel with active sessions. To access the model, you must either register with DeepSeek using an email address or log in through a Google account. After that, a familiar chatbot page opens, where you can converse with the model and manage active sessions, just like with other LLMs such as ChatGPT, Gemini, Claude, etc. Option 2. Local Application A more advanced way is to install DeepSeek on a local machine. This is possible thanks to its open-source code, unlike many other LLM services. DeepSeek can run on Windows, macOS, and Linux. Minimum requirements: 8 GB of RAM and 10 GB of free disk space, plus Python 3.8 or higher. When running locally, there are several interaction methods: Method 1. Web interface.  A graphical UI that allows querying, viewing logs, connecting external storage, monitoring metrics, analyzing performance, and more. The local interface differs from the public one by offering advanced model management tools. It is primarily intended for internal use by individual users or companies and contains parameters that only specialists would understand. Method 2. Console terminal. Method 3. REST API. A full REST interface for sending HTTP requests to the locally installed model. Example with curl: curl -X GET 'http://localhost:8080/api/search?index=my_index&query=search' \   -H "Authorization: Bearer UNIQUE_TOKEN" This universal method does not depend on the client type, whether a console terminal or a complex C++ program. Method 4. Python script. DeepSeek provides a wrapper fully compatible with the OpenAI API, allowing use of the standard OpenAI client with only a URL change. Example: from openai import OpenAI client = OpenAI(api_key="UNIQUE_TOKEN", base_url="http://localhost:8080") response = client.chat.completions.create( model="deepseek-chat", messages=[ {"role": "system", "content": "You are a helpful assistant, DeepSeek."}, {"role": "user", "content": "Hello!"}, ], stream=False ) print(response.choices[0].message.content) Method 5. JavaScript script. Similarly, you can interact with DeepSeek using the OpenAI client in JavaScript. Example (Node.js): import OpenAI from "openai"; const openai = new OpenAI({ baseURL: 'http://localhost:8080', apiKey: 'UNIQUE_TOKEN' }); async function main() { const completion = await openai.chat.completions.create({ messages: [{ role: "system", content: "You are a helpful assistant." }], model: "deepseek-chat", }); console.log(completion.choices[0].message.content); } main(); Notably, it is precisely the open-source nature that made DeepSeek popular and competitive in the LLM market. However, the local version is intended for advanced users with deep ML knowledge and specific tasks requiring local deployment. Detailed information on local installation is available in the official DeepSeek GitHub repository and the HuggingFace page. Specialized DeepSeek Models In addition to the core model, several specialized versions exist: DeepSeek Coder. For working with code (analysis and editing) in multiple programming languages. Available on GitHub. DeepSeek Math. For solving and explaining complex mathematical problems, performing symbolic computations, and constructing formal proofs. Available on GitHub. DeepSeek Prover. For automated theorem proving. Available on HuggingFace. DeepSeek VL. A multimodal model for analyzing and generating both text and images. Available on GitHub. DeepSeek Pricing Plans The DeepSeek service provides completely free access to its core models (DeepSeek-V and DeepSeek-R) through the website and mobile app. At present, there are no limits on the number of queries in the free version. The only paid feature in DeepSeek is the API, intended for application developers. In other words, if someone wants to integrate DeepSeek into their own app, they must pay for API usage, which processes the requests. Payment in DeepSeek follows a pay-as-you-go model with no monthly subscriptions. This means that the user only pays for the actual API usage, measured in tokens. There are no minimum payments. The user simply tops up their balance and spends it as queries are made. The balance does not expire over time. You can find more details on API pricing in the official DeepSeek documentation.   DeepSeek-V DeepSeek-R 1 million tokens (input) $0.27 $0.55 1 million tokens (output) $1.10 $2.19 To control expenses, manage API tokens, and view usage statistics, DeepSeek has DeepSeek Platform. It also provides links to documentation and reference materials that describe the basics of using the model, integrating with external applications, and pricing specifics. Prompts for DeepSeek: How to Give Commands and Get Results Although prompts for DeepSeek can vary, there are several general principles to follow when writing them. Clarity and Specificity It’s important to clearly describe both the details of the request and the desired format of the answer. Avoid vague wording, and provide context if needed. For example, you can specify the target audience and the approximate output format: I’m preparing a school report on history. I need a list of the 5 most important discoveries of the early 20th century, with a short explanation of each in the format of a headline plus a few paragraphs of text. For such queries, you can use Search mode. In this case, DeepSeek will reinforce the response with information from external sources and perform better fact-checking. In some cases, you can describe the format of the response in more detail: I need a list of the 15 most important discoveries of the early 20th century in the form of a table with the following columns: Name of the discovery (column name: “Name”) Authors of the discovery (column name: “Authors”) Date of the discovery (column name: “Date”) Short description of the discovery (column name: “Description”) Hyperlinks to supporting publications (column name: “Sources”, data in the format [1], [2], [3], ... with clickable links, but no more than 5 sources) The table rows must be sorted by date in descending order. The more detail you provide, the better. When writing prompts for DeepSeek, it’s worth taking time to carefully consider what you need and in what format. You can also use text descriptions to set filters: date ranges, geography, language of sources, readability level, and many other parameters. For example: I need a table of the 15 most important discoveries of the early 20th century that were made in the UK between 1910 and 1980. The table rows must be sorted by date in descending order, and the columns should be: Name (column: “Name”) Authors (column: “Authors”) Date (column: “Date”) As you can see, filtering in DeepSeek is done through natural language text rather than the sliders or filters familiar from internet catalogs or UGC platforms. Clear Formalization In addition to detailed text descriptions, you can formalize requests with a structured format, including special symbols: [Task]: Create a table of the 10 most important discoveries of the early 20th century.   [Constraints]:   - Territory: United Kingdom   - Period: 1910–1980   [Structure]:   - Columns: number, name, author, date (day, month, year)   [Context]: For history students specializing in British history.   This creates a clear request structure: Task. What needs to be done. Context. Where to search and for whom. Constraints. What to include or exclude. You can, of course, customize the structure depending on the task. Advanced Techniques LLM-based neural networks are extremely flexible. They support more complex dialogue patterns and information-processing methods. To get more relevant answers, you can use advanced prompting techniques, often mirroring real human dialogue. Option 1. Role-based prompts Explicitly asking the model to take on a role with specific qualities can add depth and define the style of the answer. Imagine you are an expert in English history with more than 30 years of experience studying the nuances of the UK’s scientific context. In your opinion, what 10 discoveries in the UK can be considered the most important of the 20th century? Please provide a brief description of each, just a couple of words. This style of prompt works best with DeepThink mode, which helps the model immerse itself more deeply in the role and context. Option 2. Query chains In most cases, obtaining a comprehensive response requires multiple queries—initial exploratory prompts followed by more specific ones. For example: First, a clarifying question: What sources exist on scientific discoveries in the UK during the 20th century? Then, the main request: Based on these sources, prepare a concise description of 5 scientific discoveries. Format: title + a couple of explanatory paragraphs. The best results often come from combining DeepThink and Search modes. DeepSeek will both gather external information and process it in depth to synthesize a thorough answer. DeepSeek vs. Other AI Models: Comparison and Conclusions Unique Features of DeepSeek Free access. The two main models (one for simpler tasks, one for complex tasks) are available completely free of charge. Only the developer API is paid, and the pricing is usage-based, not subscription-based. No limits. All models are not only free but also unlimited, i.e., users can generate as much content as they want. While generation speed may not be the fastest, unlimited free use outweighs most drawbacks. Open source. Industry experts, AI enthusiasts, and ordinary users can access DeepSeek’s source code on GitHub and HuggingFace. Global availability. The DeepSeek website is accessible in most countries. Comparison with Other LLM Services Platform Generation Speed Free Access Pricing Model Content Types Developer Country Launch Year DeepSeek High Full Pay-as-you-go Text High-Flyer China 2025 ChatGPT High Limited Subscription Text, images OpenAI USA 2022 Gemini High Limited Subscription Text, images, video Google USA 2023 Claude Medium Limited Subscription Text Anthropic USA 2023 Grok Medium Limited Subscription Text, images xAI USA 2023 Meta AI Medium Limited Subscription / Usage Text, images Meta (banned in RF) USA 2023 Qwen Medium Full Pay-as-you-go Text Alibaba China 2024 Mistral High Limited Subscription Text Mistral AI France 2023 Reka High Full Pay-as-you-go Text Reka AI USA 2024 ChatGLM Medium Limited Pay-as-you-go Text Zhipu AI China 2023 Conclusion On one hand, DeepSeek is a fully free service, available without volume or geographic restrictions. On the other hand, it is a powerful and fast model, on par with many industry leaders. The real standout, however, is its open-source code. Anyone can download it from the official repository and run it locally. These features distinguish DeepSeek from competitors, making it not only attractive for content generation but also highly appealing for third-party developers seeking integration into their own applications. That’s why when ChatGPT or Gemini fall short, it’s worth trying DeepSeek. It just might find the right answers faster and more accurately.

Midjourney is one of the most popular AI networks for image generation. The service has established itself as a leader in the field of generative AI. However, the existence of a paid subscription and access limitations (for example, the requirement to use Discord or lack of support in certain regions) increasingly prompts users to consider alternatives. We have compiled the best services that can replace Midjourney,  from simple tools to professional solutions. Why Are Users Looking for a Midjourney Alternative? Midjourney is a powerful tool, but it has its drawbacks: Paid Access: Since March 2023, Midjourney has fully switched to a paid model, with a minimum subscription of $10 per month, which may be expensive for beginner users. Usage Limitations: A Discord account is required, and for users in some countries, access is restricted due to regional limitations. Complex Interface: Beginners may find it difficult to navigate working through the Discord bot. Fortunately, there are many apps like Midjourney that offer similar functionality and more user-friendly interfaces. We will review seven of the best Midjourney alternatives. For all the AI networks considered, we will generate an image using the following prompt: “Generate an image of the Swiss Alps.” Free Alternatives First, let’s look at Midjourney alternatives that can be used for free. Playground AI Playground AI is an AI network that works on modern generative models, including Stable Diffusion XL, and allows generating images from text prompts or editing existing images. A unique feature of Playground AI is the ability not only to generate an image from scratch but also to refine it within the same interface. Users can correct individual details, replace elements (for example, hands), perform upscaling to increase detail, or draw additional parts of the image on a special working field (canvas) with a seamless continuation of the image. Using the free plan, users can generate up to 5 images every 3 hours. Advantages: Work with a library of ready-made images and prompts, and the ability to copy and refine other users’ creations. Built-in canvas tool for extending and editing images while maintaining stylistic consistency. Support for multiple models. Image generated by Playground AI using the prompt “Generate an image of the Swiss Alps” Bing Image Creator Bing Image Creator is an image generation tool from Microsoft, based on the latest version of OpenAI’s DALL·E model. The service works using a diffusion architecture: the AI network analyzes the text prompt and synthesizes a unique image considering specified styles, details, emotions, backgrounds, and objects. Users can describe the desired image in any language, and the AI interprets the prompt to generate multiple options for selection. Advantages: Completely free. Multiple image generation models to choose from. Integration with Microsoft ecosystem: Microsoft Copilot, Bing, Bing Chat, Microsoft Edge. Built-in content filtering and internal security algorithms to prevent illegal or inappropriate image generation. Image generated by Bing Image Creator using the prompt “Generate an image of the Swiss Alps” Paid Alternatives Among the paid Midjourney alternatives, the following stand out. Leonardo AI Leonardo AI functions as a cloud platform for AI-based image generation. Its main function is creating high-quality visual materials from text descriptions. Leonardo AI uses modern image generation algorithms similar to diffusion models, with additional innovative tools to improve quality and flexibility. Users can select from multiple artistic styles and genres, and also use the Image2Image feature to upload a reference image for more precise control. Users can adjust the “weight” of the generated image to balance between strict adherence to the reference and creative interpretation of the text. Advantages: Free access with a limit (up to 150 tokens per day). Ability to train custom AI models. Wide choice of styles and customization tools. Support for generating textures and 3D objects. Convenient prompt handling: a built-in prompt generator helps beginners formulate queries, while experienced users can optimize prompts for better results. Image generated by Leonardo AI using the prompt “Generate an image of the Swiss Alps” Stable Diffusion Stable Diffusion is a modern text-to-image generation model that uses diffusion model technology. Developed by Stability AI in collaboration with researchers from LMU Munich and other organizations, the model was released in 2022 and quickly gained popularity due to its openness and high efficiency. Stable Diffusion can be accessed through many services, including DreamStudio, Stable Diffusion Online, Tensor.Art, and InvokeAI. Advantages: Multiple interfaces available. Flexible settings (Negative Prompt, aspect ratio, generation steps, fine-tuning, service integration, inpainting for parts of an image, outpainting for backgrounds). Numerous custom models (anime, realism, fantasy). Possibility of local deployment on powerful PCs. Open-source code. Unlike many proprietary models (DALL-E, Midjourney), Stable Diffusion can be run, trained, and modified locally. Image generated by Stable Diffusion using the prompt “Generate an image of the Swiss Alps” NightCafe NightCafe is an online platform for generating images from text prompts and images. It uses multiple advanced algorithms and generation models, such as VQGAN+CLIP, DALL·E 2, Stable Diffusion, Neural Style Transfer, and Clip-Guided Diffusion. Users input a text prompt or upload an image, and the AI transforms it into a unique artistic work. Various styles, effects, resolution and detail settings, as well as editing and upscaling options, are available. Advantages: Numerous options for customizing generated images, suitable for digital art, NFTs, and other purposes. Built-in functionality for modifying existing images via text prompts, scaling without quality loss, and object removal. Free access with limited generations. Support for multiple styles and algorithms. User-friendly interface. Image generated by NightCafe using the prompt “Generate an image of the Swiss Alps” Artbreeder Artbreeder operates using generative adversarial networks (GANs). The main principle is creating new images by “crossing” or blending two or more images (“parents”), with fine control over parameters (“genes”) that determine various image traits. Users can interactively control the resulting image with sliders, adjusting characteristics like age, facial expression, body type, hair color, level of detail, and other visual elements. Advantages: Interactive blending allows combining different images to create unique compositions, such as portraits, landscapes, or anime styles. Detailed manual adjustments of each image parameter (brightness, contrast, facial features, accessories, etc.) allow for highly refined results. Image generated by Artbreeder using the prompt “Generate an image of the Swiss Alps” Ideogram  Ideogram is a generative AI model specialized in creating images containing text. It uses advanced deep learning and diffusion algorithms. Unlike many other AI visualization tools, Ideogram can generate clear, readable text within images, making it especially useful for designing logos, posters, advertisements, and other tasks where combining graphics and text is important. Advantages: Free generations with selectable styles. Support for integrating readable and harmonious text into images—convenient for designers, marketing teams, and social media specialists. Built-in social platform with user profiles, sharing capabilities, and community interaction. Image generated by Ideogram using the prompt “Generate an image of the Swiss Alps” Conclusion The choice of a Midjourney alternative depends on your goals and preferences: if you need the highest-quality image generation, consider Ideogram or Stable Diffusion 3. For free solutions, Leonardo AI and Playground AI are suitable, and if speed and simplicity are priorities, Bing Image Creator from Microsoft is a good option. Each service has its own advantages, whether it is accessibility, detail quality, or flexibility of settings. It’s worth trying several options to find the best tool for your needs.

Google AI Studio is a web platform from Google for working with neural networks. At the core of the service is the family of advanced multimodal generative models, Gemini, which can handle text, images, video, and other types of data simultaneously. The platform allows you to prototype applications, answer questions, generate code, and create images and video content. Everything runs directly in the browser—no installation is required. The main feature of Google AI Studio is versatility. Everything you need is in one place and works in the browser: you visit the site, write a query, and within seconds get results. The service allows users to efficiently leverage the power of Google Gemini for rapid idea testing, working with code or text. Additionally, Google AI Studio can be used not only for answering questions but also as a starting point for future projects. The platform provides all the necessary tools, and Google does not claim ownership of the generated content. You have access not only to a standard chat with generative AI but also to specialized models for generating media content, music, and applications. Let’s go through each in detail. Chat This is the primary workspace in Google AI Studio, where you work with prompts and configure the logic and behavior of your model. Chat Options At the top, there are tools for working with the chat itself. System Instruction The main configuration block, which defines the “personality,” role, goal, and limitations for the model. It is processed first and serves as a permanent context for the entire dialogue. The system instruction is the foundation of your chatbot. The field accepts text input. For maximum effectiveness, follow these principles: define the role (clearly state what the model is), define the task (explain exactly what the model should do), set the output format, establish constraints (prevent the model from going beyond its role). Example instruction: "You are a Senior developer who helps other developers understand project code. You provide advice and explain the logic of the code. I am a Junior who will ask for your help. Respond in a way I can understand, point out mistakes and gaps in the code with comments. Do not fully rewrite the code I send you—give advice instead." Show conversation with/without markdown formatting Displays text with or without markdown formatting. Get SDK Provides quick access to API code by copying chat settings into code. All model parameters from the site are automatically included. Share prompt Used to send a link to your dialogue with the AI. You must save the prompt before sharing. Save prompt Saves the prompt to your Google Drive. Compare mode A special interface that allows you to run the same prompt on different language models (or different versions of the same model) simultaneously and instantly see their responses side by side. It’s like parallel execution with a visual comparison. Clear chat Deletes all messages in the chat. Model Parameters In this window, you select the neural network and configure its behavior. Model Select the base language model. AI Studio provides the following options: Gemini 2.5 Pro: a “thinking” model capable of reasoning about complex coding, math, and STEM problems, analyzing large datasets, codebases, and documents using long context. Gemini 2.5 Flash: the best model in terms of price-to-performance, suitable for large-scale processing, low-latency tasks, high-volume reasoning, and agentic scenarios. Gemini 2.5 Flash-Lite: optimized for cost-efficiency and high throughput. Other available models include Gemini 2.0, Gemma 3, and LearnLM 2.0. More details about Gemini Pro, Flash, Flash-Lite, and others can be found in the official guide. Temperature: Controls the degree of randomness and creativity in the model’s responses. Higher values produce more diverse and unexpected answers, usually less precise. Lower values make responses more conservative and predictable. Media resolution: Refers to the level of detail in input media (images and video) that the model processes. Higher resolution allows Gemini to “see” and analyze more details, but requires more tokens for analysis. Thinking mode: Switches the model into a reasoning mode. The AI decomposes tasks and formulates instructions rather than outputting a result immediately. Set thinking budget: Limits the maximum number of tokens for the reasoning mode. Structured output: Allows developers and users to receive AI responses in predefined formats like JSON. You can specify the desired output format manually or via a visual editor. Grounding with Google Search: Enables Gemini to access Google Search in real-time for the most relevant and up-to-date information. Responses are based on search results rather than internal knowledge, reducing “hallucinations.” URL Context: Enhances grounding by allowing users to direct Gemini to specific URLs for context, rather than relying on general search. Stop sequences: Allows up to 5 sequences where the model will immediately stop generating text. Stream The Stream mode is an interactive interface for continuous dialogue with Gemini models. Supports microphone, webcam, and screen sharing. The AI can “see” and “hear” what you provide. Turn coverage: Configures whether the AI continuously considers all input or only during speech, simulating natural conversation including interruptions and interjections. Affective dialog: Enables AI to recognize emotions in your speech and respond accordingly. Proactive audio: When enabled, AI filters out background noise and irrelevant conversations, responding only when appropriate. Generate Media This section on the left panel provides interfaces for generating media: speech, images, music, and video. Gemini Speech Generator Converts text into audio with flexible settings. Use for video voice-overs, audio guides, podcasts, or virtual character dialogues. Tools include Raw Structure (scenario definition), Script Builder, Style Instructions, Add Dialog, Mode (monologue/dialogue), Model Settings, and Voice Settings. Main tools on the control panel: Raw Structure: Defines the scenario—how the request to the model for speech generation will be constructed. Script Builder: Instruction for dialogue with the ability to write lines and pronunciation style for each speaker. Style Instructions: Set the emotional tone and speech pace (for example: friendly, formal, energetic). Add Dialog: Add new lines and speakers. Mode: Choice between monologue and dialogue (up to 2 participants). Model Settings: Adjust model parameters, for example, temperature, which affects the creativity and unpredictability of speech. Voice Settings: Select a voice, adjust speed, pauses, pitch, and other parameters for each speaker. Image Generation A tool for generating images from a text description (prompt). Three models are available: Imagen 4 Imagen 4 Ultra Imagen 3 Imagen 4 and Imagen 4 Ultra can generate only one image at a time, while Imagen 3 can generate up to four images at once. To generate, enter a prompt for the image and specify the aspect ratio.  Music Generation A tool for interactive real-time music creation based on the Lyria RealTime model. The main feature is that you define the sound you want to hear and adjust its proportion. The more you turn up the regulator, the more intense the sound will be in the final track. You can specify the musical instrument, genre, and mood. The music updates in real time. Video Generation A tool for video generation based on Veo 2 and Veo 3 models (API only). Video length up to 8 seconds, 720p quality, 24 frames per second. Supports two resolutions—16:9 and 9:16. Video generation from an image: Upload a file and write a prompt. The resulting video will start from your image. Negative prompt support: Allows specifying what should not appear in the frame. This helps fine-tune the neural network’s output. App Generation Google AI Studio instantly transforms high-level concepts into working prototypes. To do this, go to the Build section. Describe the desired application in the prompt field and click Run. AI Studio will analyze this request and suggest a basic architecture, including necessary API calls, data structures, and interaction logic. This saves the developer from routine setup work on the initial project and allows focusing on unique functionality. The app generation feature relies on an extensive template library. Conclusion Google AI Studio has proven itself as a versatile platform for generative AI. It combines Gemini chat, multimodal text, image, audio, video generation, and app prototyping tools in one interface. The platform is invaluable for both developers and general users. Even the free tier of Google AI Studio covers most tasks—from content generation to MVP prototyping. Recent additions include Thinking Mode, Proactive Audio, and Gemini 2.5 Flash, signaling impressive future prospects.