How to Analyze Data with Metabase? A Comparison To 5 Most Popular Analytical Services

Choosing an operating system is not just a matter of taste. In 2025, Windows and Linux are diverging more than ever: one offers a predictable experience with minimal configuration, the other—full flexibility, but depending on your knowledge and involvement. Windows has a familiar interface, built-in drivers, support for QuickDocs and Photoshop, but you’ll pay for it: with money and with restrictions. Linux offers a system you can fully customize for yourself and use for free, but not everything works “out of the box.” In this article, we compare Linux and Windows on key points: installation complexity, hardware support, running programs and games, long-term performance, privacy and data collection, choice depending on tasks. Installation and What You Get After Windows and Linux install in a similar way: download the image, write it to a USB drive, and start the installation. But then the differences begin. Windows 11 already requires an internet connection and a Microsoft account from the start. Without this, the installation won’t continue. In addition, older computers face another restriction: the system requires a TPM chip and will stop installation if it’s missing. This is a special security module on the motherboard that ensures system integrity checks and is required to install Windows 11. After installation, the user doesn’t get a “clean” desktop, but a preloaded set of apps—App Store, widgets, Copilot, Xbox, OneDrive—some of which cannot be removed with standard tools. The system can also automatically update or download data in the background. Linux (for example, Ubuntu or Linux Mint) works differently. Hardware requirements are usually lower and less strict, allowing installation even on relatively old computers. An account is not required, and an internet connection is often unnecessary for basic installation, although some distributions may offer to download updates during setup. The installation interface is also simple: choose language, time zone, and target disk. After startup, the user gets a minimally configured system: desktop, browser, file manager. Everything else can be installed later at your choice and convenience. The system does not take action without the user’s request. And an important point: Windows requires a paid license. Without it, you face personalization restrictions and a watermark on the screen. Most Linux distributions are free and have no such restrictions, although some professional or enterprise versions may require a paid subscription or license. Hardware Compatibility: Sound, Wi-Fi, Video This is one of the main questions before switching to Linux: will everything work? The answer, in most cases, is yes, but with nuances. With Windows, it’s simple: install, and almost everything works. If something doesn’t, go to the manufacturer’s website, download and install the driver. Manufacturers officially support Windows, which is convenient. In Linux, most devices usually work right after installation. Wi-Fi, sound, display, USB drives, mouse, keyboard, and even Bluetooth—all this will most likely work without extra configuration, especially if the computer isn’t brand new or built with rare components. But sometimes there are issues: for example, on some laptops, the Wi-Fi module may not be detected automatically; in that case, you need to install a driver via terminal. For NVIDIA video cards, it’s recommended to manually install the proprietary driver for full support and performance. Fingerprint scanners on new laptops often lack official support, and enthusiasts write drivers for them. With printers and scanners, results vary: some work immediately, others require manual fixes. The advantage of Linux is that it’s not tied to new hardware. If you have an old laptop or PC that Windows 11 refuses to run on, Linux will most likely give it a second life. It doesn’t require TPM, doesn’t complain about a “too old processor,” and doesn’t force BIOS updates. The downside is that not everything always works right away. Sometimes you need to read a short guide. Sometimes, type a command in the terminal. If you’re not afraid to spend 15 minutes fixing something, it’ll work out. Programs and Games This is probably the main fear when switching to Linux: Can I still do what I used to do? The answer depends on what you use. Everyday Tasks For everyday tasks, such as the internet, email, video, music, and documents, Linux poses almost no problems. Most distributions include everything you need: Firefox and Chrome, Telegram and WhatsApp, Zoom and OBS, VLC and Spotify, and office suites like LibreOffice. These apps work quickly and install through built-in stores. Professional Tasks Things get trickier with professional software. Programs like Photoshop, AutoCAD, QuickBooks, or CorelDRAW are made for Windows and don’t install directly on Linux. There are workarounds—emulators like Wine or alternatives (e.g., GIMP instead of Photoshop)—but they don’t always offer the same capabilities. If you work with QuickBooks or file tax reports through services like TurboTax, it often makes sense to use a second machine or a virtual Windows machine. Games A few years ago, Linux was nearly unusable for gaming. Today, the situation is much better. Steam works great, and Valve actively develops Proton technology, which allows many games to run without extra setup. In ProtonDB’s compatibility database, many popular games are rated “Gold” or “Platinum.” Titles like Baldur’s Gate 3, Cyberpunk 2077, Elden Ring, The Witcher 3 run successfully. However, there’s an important limitation: games using incompatible anti-cheat systems (e.g., Easy Anti-Cheat) may not run on Linux. Fortnite and Valorant are the most well-known examples. Also, some launchers like Battle.net or Rockstar Games Launcher may work unstably or require extra setup. In short: for everyday work, Linux fits without major restrictions. But if you depend heavily on specific Windows software or often play multiplayer games with anti-cheat, check compatibility beforehand or consider dual-boot. Long-Term Performance Many Windows users notice performance degradation over time. This happens due to the accumulation of temporary files, updates, hidden services, and background processes. Some things install automatically, some remain after uninstalled programs. Constantly running services like antivirus, OneDrive, or Cortana also increases resource load, especially on older or weaker devices. Linux has similar mechanisms—temporary files, background processes, and updates exist in any OS. But they are fewer, and management is more transparent and predictable. The system doesn’t launch extra services without user request and doesn’t install new components without explicit consent. This helps maintain stable performance even after long-term use. Important: Linux has no mandatory built-in antivirus, no ads, and no intrusive services. Users can always check which processes consume resources and disable them if needed. The system stays transparent and manageable, without hidden background tasks that can’t be disabled through standard tools. Directly compared, Windows needs more regular optimization and maintenance to keep performance, while Linux tends to stay stable longer with minimal user effort. Privacy and Security Windows knows a lot about you. Even without extra configuration, the system by default sends telemetry data on how the device is used, which apps are launched, how often certain features are accessed. This is “to improve quality,” but it cannot be fully disabled with standard tools. Additionally, Windows requires Microsoft account binding, integrates with OneDrive, and shows personalized ads in the Start menu. Updates may download and install automatically without explicit user consent. Linux usually offers a more transparent approach to data collection. Many distributions don’t collect telemetry by default and don’t require an account. Some systems, like Ubuntu-based ones, may enable anonymous stats collection, but usually this can be disabled during installation. In most popular distributions, users themselves decide what data to send and when, and updates only install with explicit request. Security is also important. Because of Windows’ popularity, there’s a significant amount of malware. If users are careless or fail to update the system, the infection risk increases. Built-in antivirus helps, but doesn’t eliminate the threat. Linux has a different security architecture. Installing programs requires superuser rights and explicit approval. Malware is much less widespread, and vulnerabilities are usually patched quickly. Installing from official repositories is like downloading from a verified app store, reducing infection risk. In summary, Windows is integrated into Microsoft’s ecosystem and collects detailed usage data by default for analytics and personalization. Linux usually gives users more control over privacy and updates. Flexibility and Customization Windows allows customization within limits: change wallpaper and theme, move the taskbar, add icons, enable dark mode. But removing preinstalled components, disabling background services, or deeper interface changes often requires third-party apps or registry edits. Some elements can’t be changed at all with standard tools, like the Start menu, OneDrive integration, or built-in widgets. The result is an environment designed and tightly controlled by the developer. Linux follows another philosophy. You can change literally everything. Users can choose between different desktop environments—from minimalist XFCE to visually rich KDE. You can even configure the system to boot without a graphical interface, keeping only essential components. Want a macOS-style desktop? No problem. In Linux, you can customize not just appearance, but behavior: how the network works, how drives connect, which services run, which commands are available. Example: if you don’t want a file manager to auto-open when plugging in a USB drive, find the relevant setting or disable automount. In a minimal installation, you can simply skip unnecessary packages and services, leaving only what you need. In conclusion, Windows offers a ready-made solution with limited customization, while Linux lets you build a fully individual environment tailored to your tasks and preferences. Learning and Migration Switching from Windows to Linux is like moving to another country. The basics are familiar: desktop, icons, folders, browser. But many things work differently. Programs aren’t installed via .exe files, but through a package manager, like an integrated app store. Settings may be scattered across different menus. Sometimes solving issues requires opening a terminal and entering a command, which may feel unusual at first. But it’s not that scary. Most popular distributions have simple interfaces and large communities. Almost any question is already discussed in detail and documented. Just search for it and you’ll find step-by-step instructions. On Telegram chats and forums, you can get help and advice from experienced users. Linux doesn’t demand deep admin knowledge from beginners. You can use it like a normal user: install a browser, office apps, media players, and work without complex settings. But if you want, you can learn more: scripting, system administration through terminal, automating tasks. This flexibility is like having a toolbox: you don’t need to use everything at once, but it’s good that they’re available. In summary, Linux takes a bit more time to get used to, but in return offers more possibilities. Learning is not hard—especially if you have some patience. Windows vs Linux: Quick Summary by User Type For internet, movies, and documents: Both systems work. Linux provides all the necessary functions, doesn’t need a license fee, and usually runs faster on old hardware. Windows is more familiar, especially if you just want everything to work without tweaks. For gamers: Depends on games. Many titles, including Baldur’s Gate 3, The Witcher, Elden Ring, Cyberpunk 2077, run great on Linux. However, for games with strict/incompatible anti-cheat systems, such as Valorant, Fortnite, and GTA Online, choose Windows or consider setting it up as a secondary OS. For office and communication: Linux fully covers documents, video calls (Zoom), browser, email. Often more convenient due to fewer ads and notifications. For specialized software: If you use QuickBooks, AutoCAD, Photoshop, or submit reports via services like TurboTax, Windows is preferable. Such programs don’t always work properly in Linux, even with emulators. For developers: Linux offers a very comfortable environment: tools like Git, SSH, Docker, Python, and web servers work out of the box. For those who want stability without forced background services/updates: Linux is worth considering as your main system. Which Linux Distributions to Try If you’ve never used Linux, start with a simple distribution. Here are good options: Linux Mint: One of the most beginner-friendly options. An interface similar to Windows 7, everything works “out of the box,” and a convenient app store is available. Ubuntu: The most well-known distro. Good balance of simplicity and modern solutions. Fits both beginners and developers. Zorin OS: Great for those switching from Windows. The interface is very similar, and there’s a Lite version for weak computers. Fedora: A modern distribution with great support for new hardware and advanced technologies Popular among advanced users. Arch Linux or EndeavourOS: For those who want full control and aren’t afraid to learn. Everything is built manually, but in return, you fully understand the system. You can try any of them in Live mode. Boot from a USB drive and test without installing. This helps you see if Linux suits you and which flavor feels right. What’s Next: The Future of Windows and Linux By 2025, it’s clear that Microsoft focuses on cloud integration, AI technologies, and creating a unified device ecosystem. Windows is gradually turning from a traditional OS into a service with subscriptions, regular updates, and features like Copilot. All this pushes users deeper into Microsoft’s ecosystem. At the same time, the system increasingly depends on online functions and accounts—without them, full use is difficult. Linux is evolving differently, focusing on autonomy, minimalism, and privacy. Many users choose lightweight, control-oriented distros, including non-systemd options. The community doesn’t aim to create a universal “desktop for everyone”. Instead, it supports variety: from ready-to-use systems like Ubuntu and Linux Mint to highly customizable solutions like Arch Linux or NixOS. This lets users choose what best fits their needs: simplicity or full control. In the end, the choice between Windows and Linux depends on user priorities. Those who value a familiar interface, ready-to-use apps, and Microsoft service integration will prefer Windows. Those who want control, transparency, and flexible customization may consider Linux as a full alternative.

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.