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What Is a Virtual Server?

What Is a Virtual Server?
Hostman Team
Technical writer
Infrastructure

Let’s talk about virtual servers. About powerful PC’s with "hardware" shared between many users who want to create their own site or application.

We will get deeper into how these servers work, what they are capable of, how they are different from regular servers, and how to choose the best one.

The idea behind a virtual server is the same as the one behind an ordinary physical server. It is a place somewhere in the data centers around the world where webmasters and developers store files of their websites and applications.

In general, servers are a 24/7 working PC with all the data necessary data to maintain a website or another project that needs to be accessible by users around the world.

The main distinctive feature of virtual servers lies in their implementation. It uses so-called virtualization technology that makes possible the emulation of many computers on one physical machine. That way we have one powerful PC but a lot of space to create virtual ones within it, so hosting providers (who maintain servers in datacenters) don’t have to buy more hardware to extend the service to other users.

How do virtual servers work?

As we mentioned earlier — in the core of virtual servers sits technology called "virtualization". There are various types which differ in technical specifications but mainly perform the same tasks.

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This virtual server is a complex program (hypervisor) imitating a full-fledged OS with BIOS and other low-level stuff. Practically, it gives users fully functional "hardware" that they can use as their own computer. But the "hardware" is not actually hardware in a real sense. It is merely equipment virtualized into a PC and shared between many webmasters and developers using the same hosting provider.

What are virtual servers used for?

Like any server, virtual servers are used to store data from different projects such as:

  • Informational platforms and online stores (most of them have to have a database that also needs a server).

  • Databases with private information to be used inside a company making it possible to share some data and keep it hidden from the outside.

  • Platforms created to test software within the team or in person (when the local machine is not powerful enough).

  • Setups that are made to work with complex systems like Odoo.

  • Gaming servers (like ones used to host Minecraft personal playable worlds) and mail servers (to obtain full control on sent and received email).

  • Systems to implement CCTV (to store a lot of GB’s of recorded videos).

  • And of course personal cloud storages. You can use a virtual server as a remote hard disk to store images, videos, audio files, etc.

And yes, even virtualized hardware can deal with everything listed above. Even if a server is being used to the maximum.

What are the benefits of virtual servers?

Talking about the advantages of virtual servers… 

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  1. One of the main benefits of virtual servers is that such servers are not as pricey as real physical servers. Logically, virtual PCs cost less than tangible ones. And this is quite an important characteristic of the server because they usually cost a lot of money over the long term. Especially when the site or application is gaining popularity.

  2. Virtualization brings independence from the physical world. Users have something like an image of a computer that can be seamlessly transported to another hardware platform. It means that even if the hardware part fails it will take a matter of minutes to relaunch your "PC" using another physical server.

  3. The hosting provider will take care of your virtual server, doing routine stuff like monitoring system conditions and preventing any failures. There’s no need to hire a separate audition team.

  4. It is a computer with everything you need such as a Firewall, real IP-address, etc.

Disadvantages of virtual server

There are some shortcomings too…

  1. The performance of a virtual server would be worse than the performance of the same hardware configuration but for factual implementation. In fact, users of VS will get only part of the PC’s equipment; other webmasters and developers will get the rest.

  2. Even though you have access to many segments of the actual OS, you don’t have an opportunity to interact with the actual hard disc or CPU of the PC. That’s why some functions might be unsupported or inaccessible.

  3. Usually, hosts revoke some administrator’s permissions from users of a virtual server. So you’ll lose the opportunity to edit any of the system files or any low-level components.

VPS and VDS

We have two abbreviations: VPS and VDS. The first one stands for Virtual Private Server and the second one for Virtual Dedicated Server. Both are the same technologies in general. Both terms mean one of the ways to rent and use a server. But some users see a slight difference in these. So, dedicated server vs the virtual server, which is better?

You might stumble upon the opinion that VPS is a server that works with OpenVZ-technology and VDS with KVM.

OpenVZ — is a software virtualization layer which is installed on Linux Kernel and functions as a copy of that Linux system. You have a lot of virtual PCs but all of them are actually based on one kernel. That brings shortfalls such as an inability to install an OS other than Linux, no way to change the filesystem (ext4 only), software components like PPTP and OpenVPN are restricted, no privacy (the PC administrator has access to your data). But virtual private servers with OpenVZ are ordinarily cheaper.

KVM — is software virtualization implemented by a specific application called hypervisor. This app creates an isolated copy of the system that transforms into your own fully functional PC. This approach brings many privileges: you choose what OS to install, what filesystem to use, you can even control BIOS, and interact with low-level components like sockets and the kernel. But the most important part is security. Only the renter has access to the KVM server. A virtual dedicated server with this technology would be more expensive.

Windows-based virtual servers

You can rent a virtual server with preinstalled Windows Server OS. It will certainly be a KVM-one with almost uncompromising access to any component or chosen virtual PC.

We would recommend this type of VDS for those who for some reason want to or already work with Microsoft’s software:

  • You are acquainted with applications like Outlook and Office so you want to continue using them while developing an online working environment for your team or maybe yourself.

  • You work with a team that strongly relies on Microsoft’s ecosystem and are used to working with Windows-connected applications only.

  • You want to set up a remote working space with a graphical interface.

Also, a virtual server for Windows is a great place to cooperatively develop products with Microsoft’s proprietary technologies like .NET or using specialized applications like Microsoft Visual Studio.

To create a virtual server with Windows you should either rent an "empty" VPS and manually install Windows there as you would do with a regular PC or choose a plan with Windows preinstalled on your host’s website.

Linux-based virtual servers

This one could be using two different technologies: OpenVZ and KVM. You choose.

We would recommend a virtual server with Linux for those who don’t really need any Microsoft software and at the same time want to have a functional and performing platform:

  • Those who want to gain more control over the used system.

  • Who want to save on renting an expensive and overperforming server using a lightweight Linux-based system with no interface and other "resource hogs".

  • Who would like to use VDS to develop or host projects made using web technologies such as Node.js, JavaScript, etc.

Furthermore, Linux is a safer place to store different kinds of data.

To create a Linux virtual server you usually just need to buy a VPS and that’s it. Ubuntu (Linux distributive) is the number one OS pre-installed on servers. So there’s a 99% chance you won’t spend time installing or reinstalling OSes.

Virtual machine vs virtual server

Both are great tools to develop and test software products but in different ways.

A virtual machine is a virtual PC inside your PC. So it is installed locally via a hypervisor that is included with your motherboard and OS. Basically, it is similar to VDS but you’re the host. It uses your machine’s resources and you decide how many resources the server should take.

Why might you want to use a virtual machine instead of a virtual server? For example:

  1. You have an outstandingly performant computer and a VM would just be a more reliable platform to develop and test your applications.

  2. You want to save money on renting a VDS.

  3. Have poor internet connection and in any case, the VM does its job faster.

  4. Going to work with some confidential data that shouldn’t be stored somewhere on the web.

If that’s not you, a VDS might be a more reliable platform to work with.

Physical servers vs virtual servers

This is fairly straightforward. A physical server is a regular PC that stays somewhere in a data center and never in theory turns off.

Is there a big difference between virtual and actual ones? Not really. Generally, you can use VDS to do all the stuff you can do on a dedicated server. There would be almost no drawbacks. Because, as we pointed out earlier, KVM-technology makes it possible for users of VDS to access even things like BIOS.

The only reason you might want to go with a dedicated server is performance. It will be fast enough to deploy some complex and resource-intensive projects like gaming worlds where it is absolutely necessary to keep things going fast (in terms of CPU and RAM capability and internet connection capability too).

Are there free virtual servers?

Yes, but we wouldn’t recommend using them. Moreover, we would recommend avoiding them.

It seems a great opportunity to host your project on a free server. Nothing to give and a lot to get. But that’s not really true.

Free virtual server hosts will negatively affect your app or website because its hardware and software are usually quite slow. There’s no incentive for such servers to provide adequate speed of loading and operating.

Free servers give you only third-level domains. So you’d have to forget about good SEO scores.

A host would severely limit the amount of free space for your files. Of course, you would never have any control over the server.

The free server is free for you but not for the provider, so don’t be fooled by the "price". The provider will definitely try to make money out of you. For example, he might put an ad on your site or in your app without your consent. Or secretly will sell your confidential data to advertisers.

By using a free server you should be prepared to lose all of your content at any moment without any warning. So, as you can see, the price is high.

How to choose a virtual server?

In choosing a virtual server you must consider 5 key criteria:

Linux or Windows

We discussed it above, so reread that part and decide what OS do you want (or need) to use on your VDS.

Hardware

Modern technologies give hosting providers the ability to serve developers and webmasters with a certain performance level. You may without any hesitation choose VDS based on this information. For small apps and sites, you don’t need a superpowerful PC but you should definitely consider an option with SSD storage.

Geolocation

The closer the server to a user of an app or site the faster it works for him. Try to choose one that will be fast enough for everyone.

Control Panel

Besides the command line, you will sometimes use the Control Panel to interact with the server. So it should be user-friendly and functional enough to fulfil your needs.

Best virtual servers

You can find thousands of hosts around the web, but there are some big names you must consider as the best solution. For example Digital Ocean. One of the most modern and reliable providers that are quite popular and relatively inexpensive. Additionally, you might consider the IBM platform and rent VDS there.

If you don’t really need to control your server but want to host an app or website in a few clicks with the power and quality of Microsoft’s and Amazon’s ecosystems, you might want to consider Hostman as your provider.

It makes managing any web project or application a breeze, so you can concentrate on the creative part of your work while delegating all routine tasks to the Hostman’s professional administrators.

You can try with free7 days trial. Create your virtual server here.

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Top AI Coding Tools in 2025: Best Models for Developers & Programmers

In the early days of computing, programmers wrote code entirely on their own, from scratch and solo. Hardcore mode! The only help they had was paper reference books describing the syntax of specific languages. Today, things are very different. In addition to countless electronic manuals, guides, articles, videos, and forums, we now have neural networks, arguably one of the most groundbreaking technologies of the early 21st century. Trained on massive datasets, these AI models have become the primary source of coding assistance. The advantages are obvious. AI coding tools speed up the development process by taking on much of the routine work involved in writing code. This allows developers to focus on architecture and logic instead of syntax errors and inefficient constructs. Some tools generate code from scratch, and others analyze and complete already-written code. However, in recent years, so many AI-powered projects have emerged that it can be difficult for the average person to figure out which AI is actually the best for programming. There are both specialized and general-purpose models. Some only generate specific types of data (like code), while others handle all kinds (text, code, images). Some are free, others paid. To determine which AI is the best for programming (and why), we first need to create a list of the top coding AIs, and then analyze the pros and cons of each one. 1. GitHub Copilot Copilot is arguably the best AI coding assistant, developed by GitHub in collaboration with OpenAI. It’s positioned as an AI co-programmer trained on millions of open-source GitHub repositories. Features Developed by the largest cloud-based code hosting platform, Copilot leads the list of neural networks for programming, offering a wide range of capabilities: Code Generation: Produces ready-to-use code snippets in all major languages based on text descriptions: scripts, functions, classes, even entire files. While the AI sometimes generates imperfect results, this can be resolved by making the user’s request more specific. Code Translation: Converts code written in one programming language into logically equivalent code in another. This feature alone puts Copilot ahead of many other coding AIs, as not all models can do this effectively. Code Autocompletion: Suggests autocompletion based on the overall context of the codebase. Refactoring: Enhances code structure, optimizes algorithms, and fixes errors. It can also suggest alternative, more efficient solutions that a developer might not have initially considered. Editor Integration: Integrates via plugins into popular text editors and IDEs like Visual Studio Code, Neovim, JetBrains IDEs, and others. These features help automate routine coding tasks. A lesser-known use case of Copilot is learning programming languages. The AI can generate simple code snippets that demonstrate the syntax and mechanics of a specific language. Interestingly, this teaching method aligns with Stephen Krashen’s Comprehensible Input Hypothesis, which states that language acquisition is driven by understandable input, i.e., the material that the learner can interpret with explanation. Similarly, Copilot can be used as an interactive reference, potentially replacing resources like Stack Overflow. Languages Supported Copilot supports all major programming languages: C, C++, C#, Go, Java, JavaScript, Kotlin, PHP, Python, Ruby, Rust, Scala, Swift, and TypeScript. It can also generate code using popular frameworks and libraries like React, Angular, Vue.js, Node.js, Django, Flask, and Ruby on Rails. Pricing Plans Naturally, GitHub offers only a limited set of Copilot features for free. The free version also has monthly limits on code generations. The full version is available through subscriptions for individuals, teams, and enterprises. Pricing starts at $4/month, with a 30-day free trial. In return, users get a powerful tool for faster coding. Despite requiring a subscription, many developers consider Copilot the best AI coding assistant, especially when compared to general-purpose models like ChatGPT, which aren't primarily designed for code generation. 2. Tabnine Tabnine is an AI that generates code snippets not based on explicit prompts but on the development context formed by the programmer’s current work. Features Unlike Copilot, Tabnine primarily focuses on code autocompletion. However, it also offers several distinctive features: Offline Mode: The Enterprise version of Tabnine can run entirely offline, generating code without internet access. This improves data privacy, as code is processed locally and not sent to the cloud; however, it does require more system resources. Personalized Generation: Tabnine learns from a specific developer’s codebase, mimicking their unique style and preferences. This results in personalized suggestions that feel as if the code were written by the developers themselves, in contrast to Copilot, which was trained on public GitHub repositories. IDE Integration: Since Tabnine is not a standalone application but a smart autocompletion engine, it integrates with virtually all major IDEs through plugins, including VS Code, IntelliJ, Visual Studio, Eclipse, Android Studio, AppCode, CLion, GoLand, Neovim, PhpStorm, PyCharm, Rider, RubyMine, WebStorm. Interactive AI Chat: Tabnine also offers a built-in chat interface for personalized communication with the AI. Users can ask questions related to the code in their current editor tab. All in all, Tabnine is geared more toward typing speed and efficiency rather than generating large chunks of code from scratch. Think of it as classic autocompletion but supercharged with AI. Languages Supported Like Copilot, Tabnine supports autocompletion for all major programming languages: Python, JavaScript, TypeScript, Java, C/C++, C#, Go, Ruby, Swift, PHP, Rust, Kotlin, Perl, Dart, Scala. Pricing Plans Tabnine is available under two subscription plans: Dev – from $9/month for individual developers. Enterprise – from $39/month for teams and companies. The Enterprise plan offers advanced customization options, enhanced security, and on-premise deployment for maximum privacy. 3. ChatGPT ChatGPT is a generative AI developed by OpenAI, based on the GPT (Generative Pre-trained Transformer) architecture. Unlike Copilot and Tabnine, ChatGPT can generate not just code but also various forms of text content. That makes it a general-purpose neural network—a versatile tool for generating any data based on a user's prompt. Some might argue that ChatGPT is more text-oriented than code-focused. However, it remains one of the best free AI for coding, as its basic version is available to everyone without a paid subscription. Features ChatGPT operates through a chat interface, where prompts are entered as natural language messages. That’s why its name consists of Chat and GPT: Chat: its ability to hold conversations, answer questions, and maintain real-time dialogue. GPT: short for Generative Pre-trained Transformer: Generative: creates original text rather than copying answers, Pre-trained: trained on vast data corpora, Transformer: refers to the model’s architecture, which uses attention mechanisms to understand and generate contextually accurate responses. In short, ChatGPT is a conversational AI capable of tackling almost any language-based task — including code generation. Here’s what it can do: Conversational Interaction: The AI responds as if you were chatting with another person. You can ask it to use a certain tone, generate text, tables, code, and even simple images. This makes ChatGPT a virtual assistant, coworker, or advisor. Free Code Generation: The base model is completely free to use. More advanced versions offer improved performance but require a subscription. Multi-Format Output: It can create more than just code. You can generate any language-based content based on a clear prompt and adapt it to the ongoing context of the conversation. For example, you could write this fun prompt: “Give me an example of Python code with a helicopter and a car class. Each should have a fuel variable initialized to 100. Then create objects of each class and have the helicopter hook the car with a cable.” ChatGPT would generate something like this: class Helicopter: def __init__(self): self.fuel = 100 self.hooked_car = None def hook_car(self, car): self.hooked_car = car print("The helicopter has hooked the car with a cable.") class Car: def __init__(self): self.fuel = 100 helicopter = Helicopter() car = Car() helicopter.hook_car(car) You can check this code in any online Python interpreter and get the expected output: The helicopter has hooked the car with a cable. So, if you're working late at night and wondering which neural network is best for hands-off code generation, ChatGPT is worth considering. After all, OpenAI is a global leader in machine learning. At the very least, ChatGPT is the best conversational AI for code creation, capable of generating not only code but also full documents, tables, and even basic images. Languages Supported Since it was trained on a vast linguistic dataset, ChatGPT can generate code in nearly any language and not just general-purpose ones. It supports all major programming languages, including Python, JavaScript, TypeScript, Java, C, C++, C#, Go, PHP, Swift, Kotlin, Ruby, Rust, Haskell, Lisp, Elixir, Erlang, and F#. It also understands domain-specific languages: HTML, CSS, SASS/SCSS, SQL, GraphQL, Shell, PowerShell, Lua, Perl, YAML, and JSON. Listing them all would be pointless, as ChatGPT can understand and generate code or text in virtually any format. That's its defining strength. Pricing Plans OpenAI offers four subscription tiers for ChatGPT, each expanding the capabilities of the last: Free – All basic features. No cost. Plus – Enhanced performance and access to newer models with better contextual understanding and faster responses. Starts at $20/month. Pro – Full access with no usage limits. Starts at $200/month. Team – Adds collaborative tools, custom roles, and enhanced security for data sharing and storage. Team data is excluded from AI training — ensuring full confidentiality. Starts at $25/month. Paid plans provide higher accuracy, better performance, and more stability. Still, the free version offers nearly identical functionality — the difference lies in the fine details. 4. Claude Claude is another natural language processing AI developed by Anthropic. According to its creators, Claude is a safer, more ethical, and more predictable alternative to ChatGPT. Features Overall, Claude's capabilities are similar to ChatGPT’s, with a few notable distinctions: Image and Document Analysis: Claude can interpret the contents of images and documents in detail, recognizing real-world objects, diagrams, graphs, numbers, and text. ChatGPT is also capable of this, but only in its paid version. Claude offers it natively. Massive Context Window: Claude supports up to 200,000 tokens, which allows it to analyze large volumes of data. By comparison, ChatGPT maxes out at around 128,000 tokens. One token is roughly 5 characters of English text. High Ethical Standards: Thanks to built-in ethical constraints, Claude is less likely to generate inappropriate content, making its responses more conservative. While this may not matter to some users, from a broader perspective, output filtering is a key trait that separates the best AI coding tools from the rest, especially as AI tools become mainstream. In short, Claude offers high factual accuracy, which is crucial for generating reliable code based on user instructions. Languages Supported According to Anthropic, Claude performs best when generating Python code. However, it also supports other popular languages: JavaScript, Java, C++, Go, PHP, Ruby, C#, Swift, TypeScript, Kotlin, and Rust. Of course, the full list of supported languages isn’t publicly available, as the model was trained on diverse datasets. Practical testing is the best way to determine support. Pricing Plans Claude offers several pricing tiers: Free – Standard chat access via browser or mobile app (iOS/Android). No cost. Pro – Enables structured chats, document analysis, and access to additional Claude models and features. Starts at $18/month. Team – Adds collaboration features for group work. Starts at $25/month. Enterprise – Provides deeper control over generation processes, user role management, and enhanced data privacy. Custom pricing. Despite Claude being one of the top free AI for coding, it can’t be considered a full competitor to ChatGPT. Here’s why: Smaller Knowledge Base: ChatGPT was trained on more data, producing more accurate and diverse responses. Limited Availability: Claude is not as widely accessible as ChatGPT and is available in fewer countries. Few Integrations: ChatGPT is integrated into many products (e.g., Office, Azure), while Claude is not. Slower Development: ChatGPT evolves rapidly, releasing updates and features faster than Claude. Still, Claude is worth trying for anyone who regularly uses AI in programming or text generation tasks. 5. Snyk Code Snyk Code is an AI-powered static analysis tool for detecting vulnerabilities and errors, part of the broader Snyk ecosystem. Features Trained on a database of known vulnerabilities (updated regularly), Snyk Code focuses on secure development: Vulnerability Detection: Performs real-time code analysis during development and commits to catch threats before they reach production. Development Tool Integration: Works with GitHub, GitLab, Bitbucket, and Azure Repos, and is compatible with popular IDEs: VS Code, IntelliJ IDEA, PyCharm, WebStorm, Eclipse. Contextual Fix Recommendations: For every issue found, it provides an explanation and sample fixes, helping developers patch their code quickly and securely. In essence, Snyk Code is best used after you have written the code as an added security layer before deployment. Languages Supported Snyk Code supports major programming languages only: Apex, C, C++, Go, Groovy, Java, Kotlin, JavaScript, .NET, PHP, Python, Ruby, Scala, Swift, Objective-C, TypeScript, VB.NET. Pricing Plans Snyk Code is free for individual use, but teams and companies can choose from the following: Free – Basic analysis with a limit of up to 200 scans per month. Team – Adds support for private repos, CI/CD integration, and advanced security features. Starts at $25/month. Enterprise – Includes local deployment, advanced analytics, and enterprise-level controls. Custom pricing. While Snyk Code doesn’t generate code, its powerful analysis tools and free tier perfectly justify its inclusion in any list of the best free AI tools for coding. 6. Documatic Documatic is an AI that automatically generates documentation and enables codebase exploration. It analyzes the project, extracts key information, and structures it for easy reference. Features Documatic is designed for codebase analysis; all other functionality stems from this core: Automatic Documentation Generation: Produces detailed code explanations, reducing the need for manual comments. Code Search and Navigation: Responds to developer queries with relevant code snippets and context. Project Structure Visualization: Displays project components (dependencies, microservices, repos) as interactive graph nodes, useful for understanding complex architectures. Code Explanation: Clarifies algorithms and logic, making unfamiliar projects easier to understand. Documatic is passive: it doesn’t generate code, only analyzes and documents it. Languages Supported It supports modern interpreted and compiled languages: Python, Java, JavaScript, TypeScript, Go, C#, PHP. Pricing Plans Documatic keeps things simple with just two tiers: Free – Full basic functionality for solo developers, including auto-documentation. No cost. Team / Enterprise – A combined tier for corporate use, offering unlimited analysis, integrations, reporting, and collaboration tools. Custom pricing. While it’s easy to chase the best AI coding tools, it’s crucial to remember: the developer matters more than the AI. Skills, logic, creativity, and experience outweigh any neural network’s output. You should only upgrade to premium tools when free features no longer meet your needs. 7. Mintlify Mintlify is a comprehensive online platform for automating code documentation with AI. Unlike Documatic, Mintlify offers cloud hosting with visually styled, user-accessible documentation sites. For instance, a developer or team building a JavaScript library can generate full documentation from a GitHub repo, resulting in a live, multi-page site with API references. These pages are editable using a WYSIWYG editor. Fun fact: Anthropic uses Mintlify to power the documentation for Claude. Features Mintlify connects the project’s codebase to a public-facing documentation site, offering: Automated Documentation Generation: Generates detailed documentation (including API references) directly from your codebase. Version Control Integration: Syncs with GitHub and GitLab, ensuring documentation updates automatically when the code changes, which makes it perfect for CI/CD pipelines. Documentation Site Hosting: Creates a stylish, SEO-optimized site with editable sections. Analytics & Feedback: Provides user analytics and supports direct feedback collection to improve documentation quality. While powerful, Mintlify has a learning curve as its feature-rich interface takes time to master. Languages Supported Supports 12 modern languages: Python, JavaScript, TypeScript, C, C++, PHP, Java, C#, Ruby, Rust, Dart, Go. Pricing Plans Mintlify offers four plans: Hobby – Free plan for individuals with full standard functionality. Pro – Advanced configuration and analytics. Starts at $150/month. Growth – Allows full customization, branding removal, and other perks. Starts at $550/month. Enterprise – Full configuration control and dedicated support. Custom pricing. Where other AI coding tools show their intelligence directly, Mintlify’s AI works silently in the background. At first glance, it may seem like a manual documentation editor; however, over time, it reveals itself as an automation powerhouse, seamlessly connecting code to documentation. 8. Codeium Codeium is an AI-powered coding assistant that consists of several products built on artificial intelligence: Windsurf Editor – an integrated development environment (IDE) with built-in AI. Forge – an AI assistant for code analysis and review. In addition to these, there’s a browser-based chat called Live, as well as numerous IDE extensions – Codeium Extensions. The Codeium Windsurf Editor integrated development environment, with the code editor on the left and the AI chat on the right. Source: codioailab.com Features Codeium offers a wide range of features that assist during coding and code editing: Code Autocompletion: Provides intelligent suggestions as you type. Chat Assistant: A built-in AI chat can explain code snippets in detail, offer refactoring suggestions (passively while you write), and answer programming questions directly within the development environment. It can also advise on build commands and configuration. Intelligent Search: Ensures quick access to classes, methods, functions, and code fragments, streamlining navigation in large codebases. Essentially, Codeium aims to provide a comprehensive suite of tools for virtually all coding scenarios – all powered by AI. Languages Supported Supports all popular programming languages, including: Python, JavaScript, TypeScript, Go, Java, C#, PHP, Ruby, Kotlin, Swift. Pricing Plans Codeium offers several pricing plans for both individual developers and entire teams: Free – All standard features. Free of charge. Pro – Expanded context and deeper AI understanding, faster autocompletion, and other advanced features. Starting at $15/month. Pro Ultimate – Even more useful tools and priority support. Starting at $60/month. Teams – Collaboration and analytics tools for teams. Starting at $35/month. Teams Ultimate – Enhanced AI model access. Starting at $90/month. Enterprise SaaS – Custom pricing upon request. 9. Gemini Gemini is a versatile AI developed by Google. Despite being relatively new, it rounds out our list of the top AI coding assistants in 2025. Unsurprisingly, it’s a direct competitor to both ChatGPT and Claude.  Features It’s important to recognize that Google is a major player (arguably a monopolist) in the software market. With vast cloud infrastructure, massive data resources, and many popular services (plus its own OS, Android), Gemini offers a broad array of capabilities for working with both text and visual data: Text Generation, Analysis, and Translation. Image Generation and Analysis: Generates images from text prompts and can also analyze images and describe their contents. Code Generation and Analysis: Generates code snippets in any language and format. Also understands and analyzes code, providing suggestions for improvement. Google also offers the Gemini Code Assist extension for popular IDEs. Integration with Google Services: Integrated with many Google apps and Android tools. Fast Response Generation: Provides answers faster than ChatGPT and generally operates at a higher speed. Large Context Window: Can handle up to 1 million tokens. Notably, the advanced capabilities of Gemini’s language model are available through a special AI Studio for developers. This environment allows not only text-based interaction but also screen sharing for more detailed feedback. AI Studio is designed for app developers who want to test Gemini integration with their products. Languages Supported Gemini supports the following major programming languages: Python, Java, C++, JavaScript, Go, TypeScript, C#, Ruby, PHP, Swift, Kotlin, Rust, SQL, HTML, CSS, Bash, Perl, Lua, R, Dart, Scala, Julia, Fortran. Pricing Plans Google offers a fairly straightforward pricing structure for Gemini: Free – Standard model access. Advanced – Enhanced performance, accuracy, and multimodal capabilities. Starting at $22/month. Thus, just like ChatGPT, Gemini is another great free AI for programming, particularly when it comes to working with general-purpose data. The ability to generate not only code but also supporting text is an important asset in development. Conclusion So, what is the best AI for coding? That’s for each user to decide. Some may be satisfied with intelligent autocompletion, while others may require the generation of large code fragments across multiple languages – complete with detailed explanations. Model Type Features Pricing Copilot Specialized Code generation, autocompletion Subscription Tabnine Specialized Autocompletion Subscription ChatGPT General Generation, analysis Free, subscription Claude General Generation, analysis Free, subscription Snyk Code Specialized Analysis Free, subscription Documatic Specialized Documentation Free, subscription Mintlify Specialized Documentation, hosting Free, subscription Codeium Specialized Generation, analysis Free, subscription Gemini General Generation, analysis Free, subscription Ultimately, the most important factor is not the tool itself, but the developer using it. Skills, experience, logic, critical thinking, and creativity all outweigh the capabilities of any neural network. So, switching to paid versions of AI products – whether they’re code generators or analyzers – only makes sense when the free version clearly falls short for your needs.
03 June 2025 · 19 min to read
Infrastructure

Top AI Models in 2025: Features, Use Cases & Full Comparison

Artificial intelligence and neural networks are used not only for generating texts and solving mathematical problems. They are also widely applied in medicine, scientific research, finance, marketing, and advertising. There are many different neural networks — some generate only textual data, others create images and videos, and some work with vector graphics.  Today, we will take a detailed look at the 8 best AI apps to use in 2025: Grok, ChatGPT, Gemini Ultra, DeepSeek, MidJourney, Claude, Sora, and Recraft. Grok 3 Our list of the best AI applications in 2025 opens with the AI from xAI called Grok. Grok was designed with a focus on processing and analyzing complex queries. The AI can not only generate text but also, for example, explore social media user profiles, verify links, and analyze uploaded files (including images and PDF documents). The third version of the AI differs from the previous versions (Grok 1 and Grok 2) by improved performance, extended functionality, and a changed approach to training. Key features of Grok 3 include: Increased computational power. The model was trained on the Colossus supercomputer equipped with approximately 200,000 Nvidia GPUs, which significantly increased accuracy and depth of data processing. New versions of built-in models. Grok 3 introduced new models — Grok 3 Reasoning and Grok 3 mini Reasoning. These models use a “chain of thought” approach that allows them to analyze tasks step-by-step, verify their conclusions, and correct mistakes. Information retrieval from various external sources. Grok 3 has introduced a new feature called DeepSearch, which searches the internet and social media, providing the AI with more flexibility in information retrieval and response generation. Use of synthetic data. Earlier Grok versions primarily used human-created data. Grok 3 actively incorporates synthetic data in training, increasing model adaptability and reducing bias. New functionality. Grok 3 includes new modes — Think and Big Brain — which enhance the response generation process for complex queries. Image generated by Grok from the prompt 'Draw Dubai city at night' ChatGPT-4.5 No list of the best AI applications would be complete without mentioning ChatGPT. The flagship product of OpenAI, released in late November 2022, caused a sensation worldwide. ChatGPT can be used for a wide range of tasks, from creating texts of any complexity to use in medicine and scientific research. As of May 2025, the latest version is ChatGPT-4.5, which offers the following features: Multimodal support. This means the model can analyze images along with text. For example, a user can upload an image and ask the AI to describe it or answer questions about its content. Improved accuracy in responses. ChatGPT 4.5 significantly improves fact-checking and generates more accurate answers compared to versions 3.5 and 4, which sometimes provide unverified or false information. Enhanced safety mechanisms. Version 4.5 features stronger filters to reduce bias and improve safety, resulting in fewer inappropriate or offensive responses. Image generated by ChatGPT from the prompt 'Draw Dubai city at night' Gemini Ultra Search giant Google also contributed to the development of neural networks by releasing Gemini Ultra in December 2023. As a multimodal neural network, Gemini Ultra is integrated into Google’s ecosystem. It processes not only text data but multimedia, including images and videos. The AI’s applications range from search and data analysis to creative content generation. Gemini Ultra is considered a serious competitor to ChatGPT. Key features include: Support for multiple data formats. Unlike most other models, Gemini Ultra was built to handle various data types (text, images, audio), enabling it to analyze images or generate code from text prompts. High performance in query processing. Based on a multimodal architecture, Gemini Ultra shows impressive results in tasks requiring cross-modal reasoning. Image generated by Gemini from the prompt 'Draw Dubai city at night' DeepSeek R1 Chinese company DeepSeek, developer of the AI of the same name, caused a sensation in the AI world. On January 27, 2025, when DeepSeek R1 was released, it became the most downloaded AI app worldwide and caused market excitement, affecting stock prices of global tech firms (Nvidia, Advantest, Tokyo Electron, Renesas Electronics, SoftBank Group). This was preceded by news that DeepSeek R1’s development cost was much lower than competitors. It also used fewer chips and had an optimized architecture. Communication between chips was enhanced to reduce data volume for memory saving and implement the Mix-of-Models method. DeepSeek R1 positions itself as a competitor to ChatGPT and other language models. Its applications range from solving math problems and learning programming to composing complex texts and writing scientific articles. Main advantages of DeepSeek R1: Architecture. It uses a Mixture-of-Experts architecture, consisting of many specialized subnetworks, each handling specific data types or tasks, providing high performance with less computational cost compared to similar-sized models. Open source. Unlike most AI models, DeepSeek R1 is open source, allowing users to view, improve, and modify the AI code. Training process. Training uses Reinforcement Learning, a method where the AI learns by trial and error to optimize its decisions and become smarter. Text generated by DeepSeek from the prompt 'Tell me 5 reasons to visit Dubai' Midjourney V6.1 While many neural networks focus on text, the popular Midjourney AI changes the interaction by generating images from text prompts. Version V6.1, released in July 2024, has the following features: Improved image quality. Generated images look much better—more detailed, realistic, and with natural textures. Better handling of complex requests. It processes complex prompts more effectively, reducing the need for repeated clarifications. New upscaling modes. Two new upscaling modes were added: Upscale Subtle (doubles resolution without altering the image) and Upscale Creative (also doubles resolution but adds creative changes). Both enlarge images up to 2048x2048 pixels. Faster image generation. A Turbo mode introduced in March 2024 speeds up generation by 3.5 times. Claude 3 Claude 3 is a neural network and family of language models released in March 2024 by Anthropic. It is positioned as a versatile solution for a wide range of tasks and an alternative to other neural networks such as ChatGPT, Grok, Gemini Ultra, etc. Claude 3 is trained on a variety of internet text data and incorporates extensive user feedback to improve response accuracy. Features: Three distinct models: Claude 3 Haiku: Basic model for short texts, translation, and data structuring. Claude 3 Sonnet: Standard model balancing speed and quality, suited for large and analytical data. Claude 3 Opus: Advanced model for complex tasks like forecasting, process automation, and scientific data processing. Enhanced context understanding. Uses advanced algorithms and can handle large volumes of text and images. Text generated by Claude from the prompt 'Tell me 5 reasons to visit Dubai' Sora OpenAI, best known for ChatGPT, released a new service called Sora in February 2024. It generates short (up to one minute) Full HD videos from user text descriptions. The model was trained on a large video dataset and can create videos on various topics. Features include: Full built-in video creation functionality. Besides generating videos from text, Sora includes editing tools like Remix (element modification), Storyboard (scene assembly), Loop (looping), and Blend (video transitions). Style support is also available. Recraft Closing our list of the top AI apps is Recraft, a tool for creating and editing images and graphic content. Launched in 2023, by 2025 it became popular among creative users. Recraft can create images based on text descriptions with specific styles and edit existing images by removing/replacing objects or changing backgrounds. Main features: Creation of various image types. Can generate both raster and vector graphics. Customization. Users can select size, style, color palette, and fine-tune details like color, element placement, detail level, and add text. Image generated by Recraft from the prompt 'Draw Dubai city at night' Conclusion: Comparative Table We reviewed 8 top AI applications for 2025. The market offers various AI tools not only for text but also for photo and video creation. Each service has unique features. For clearer comparison, see the table below: Neural Network Developer Main Purpose Multimodality Pricing Policy Features Grok xAI General queries, reasoning Yes (text, images) Paid plans, free tier exists High accuracy, single interface for text and images ChatGPT OpenAI Text generation, dialogue, data analysis Yes (text, images) Free and paid plans Versatile, voice support, fast response generation Gemini Ultra Google DeepMind Text, images, code generation Yes (text, images, audio) Free and PRO plans in some countries Google ecosystem integration, high performance, task-specific models DeepSeek DeepSeek AI Text, scientific articles, code generation No (text only) Free (open source), paid API Open source, optimized for technical tasks Midjourney Midjourney Image creation No (images only) Free limited use, paid plans High image quality, supports references Claude Anthropic Text, big data analysis, automation, forecasting Yes (text, images) Free limited use, paid plans High performance in creative and technical tasks Sora OpenAI Video creation No (video only) Paid plans, free limits High-quality videos, cinematic style, text-based generation Recraft Recraft Image creation and editing No (images only) Paid plans, free limits Suitable for design and commercial use
02 June 2025 · 8 min to read
Infrastructure

Top Dock Panels for Linux in 2025: Lightweight, Fast & Flexible

A dock panel, or simply a “dock”, is a toolbar that makes working with frequently used applications easier and extends the capabilities of the standard desktop panel. Unlike the traditional taskbar, dock panels offer significantly more features, not just for working with icons but also with widgets. Additionally, they can be positioned anywhere on the screen, not just across the full width. In this article, we’ll look at the best Linux dock panels that can make working with your favorite programs much more convenient and add useful features. Of course, “best” is a subjective term, so we’ve selected the six most popular docks among Linux users. Docky Docky's popularity is largely due to its lightweight and resource-efficient nature. Its interface resembles macOS, which many users find appealing. Docky is also a stable application that won’t cause lags or crashes. It supports themes, widgets (called "docklets"), a 3D mode, and can stretch like a regular toolbar. Thanks to widget support, you can instantly see the weather, monitor system resource usage (CPU, RAM), or check power status. Key Features: Lightweight Stable Highly customizable Supports docklets How to Install Docky: Debian/Ubuntu:  apt install docky Arch:  pacman -S docky Fedora/CentOS:  dnf install docky Plank Another lightweight dock panel, Plank, is very easy to install and configure, making it a great option for Linux beginners or anyone wanting to conserve system resources. It has a clean interface, flexible placement, and auto-hide options. Fans of customization will appreciate the wide selection of built-in icons and the ability to add their own. Like Docky, Plank supports docklets. A notable one is Clippy, which shows clipboard contents. Key Features: Lightweight Easy to configure Customizable Supports docklets How to Install Plank: Debian/Ubuntu:  apt install plank Arch:  pacman -S plank Fedora/CentOS:  dnf install plank Latte Dock While Docky and Plank focus on speed and simplicity, Latte excels in visual customization. It’s perfect for those who dislike minimalism, featuring effects like parabolic zoom. Latte Dock also supports multiple dock panels, detailed visibility settings, widgets, and custom layouts. Originally designed for KDE, it can also run in other desktop environments with the right dependencies installed. It's worth noting that Latte hasn't been actively maintained for some time and hasn't received many updates in the last couple of years. However, many users still run Latte Dock successfully on different Linux distributions—and swear by it. Key Features: Beautiful and customizable Supports multiple dock panels Supports docklets and custom layouts Built for KDE How to Install Latte: Debian/Ubuntu:  apt install latte-dock Arch:  pacman -S latte-dock Fedora/CentOS:  dnf install latte-dock Cairo-Dock A well-known dock featured in most reviews, Cairo-Dock is praised for its high degree of customization and optimization. There’s even a low-resource version. Built-in widgets (weather, email notifications, torrent loading) are not dock-bound, and you can place them anywhere on the desktop. Cairo-Dock also includes system-wide search, eliminating the need to open the start menu. Key Features: Maximum customization Well optimized Freely placeable docklets Built-in system search How to Install Cairo-Dock: Debian/Ubuntu:  apt install cairo-dock Arch:  pacman -S cairo-dock Fedora/CentOS:  dnf install cairo-dock Tint2 Less popular but still worth considering, Tint2 offers minimalistic design and excellent optimization—ideal for low-spec computers. It supports nearly all Linux window managers, plug-in docklets, and has a rich configuration file enabling fine-tuned customization, especially for fonts and panel colors. Key Features: Well optimized Compatible with window managers Docklet support Great customization options How to Install Tint2: Debian/Ubuntu:  apt-get install tint2 Arch: pacman -S tint2 Gentoo:  emerge -av tint2 Dash to Dock While Latte is KDE-focused, Dash to Dock is designed for GNOME. It doesn't integrate well with other desktop environments, but GNOME users, especially those on Ubuntu and Fedora, will find it highly capable. Dash to Dock is lightweight, simple to configure, and offers the level of customization most users expect from a modern dock. Key Features: Lightweight Easy to configure Customizable Built for GNOME How to Install Dash to Dock: Arch:  Arch supports direct installation with Yay. Simply run the command: yay -S gnome-shell-extension-dash-to-dock Other distros: For other distributions, you need first to clone the package in GitHub: git clone https://github.com/micheleg/dash-to-dock.git   Then navigate to the directory: cd dash-to-dock And run these two commands consecutively: make sudo make install
30 May 2025 · 4 min to read

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