What Is Swagger and How It Makes Working with APIs Easier

Neural networks and artificial intelligence can process not only text data, videos, and graphics but also work with audio information. This capability makes it possible to create music. Just a few years ago, it was believed that creating your own musical compositions required a studio and instruments, or at least the skills to work with specialized software. However, the rapid growth of artificial intelligence is completely changing this paradigm—now, AI takes on the entire process of creating musical compositions. The user only needs to create a text prompt specifying the requirements for the composition. Today, we review top AI music creation platforms: Suno AI, AIVA, Soundraw, Mubert, MusicGEN, Loudly, Riffusion. How AI Makes Music Before reviewing the AI platforms, let's understand how they make music. Typically, AI uses deep learning to create musical compositions. This method allows analyzing large volumes of musical data and generating new compositions based on it. The algorithm for generating music involves training a model on large datasets (e.g., MIDI files and audio recordings) and then generating music based on parameters such as genre or instruments. Below are the types of neural networks used in music creation: Recurrent Neural Networks (RNN) A recurrent neural network is a deep learning model trained to process and transform sequential sets of input data into sequential output. Sequential data are data in which components have a strict order and relationships based on complex semantics and syntactic rules, such as words and sentences. As mentioned earlier, RNNs are well-suited for working with sequences. In music, these sequences are melodies and chords, thanks to the network’s ability to "remember" previous notes. Transformers Transformers are a type of neural network architecture designed to transform an input sequence into an output sequence. They study context and track relationships between components of a sequence. In music creation, transformers are used to handle complex musical structures and generate multilayered compositions. Generative Adversarial Networks (GAN) GANs are named for their use of two neural networks that "compete" with each other: one network generates data samples, while the other tries to predict whether the data is original. In music generation, one network creates tracks while the other evaluates their quality, improving the final result as needed. Autoencoders Autoencoders are neural networks that do not use supervision during training and do not rely on data compression. They are used to create variations based on existing tracks or to apply musical stylization. Suno AI Suno AI is a popular AI music software launched in December 2023 that creates vocal and instrumental tracks using a simple text prompt. You can specify the style of the composition and the song lyrics in the prompt. Its popularity led Suno, Inc., in partnership with Microsoft, to integrate Suno AI into the Microsoft Copilot chatbot. Suno AI is ideal for background music and advertising tracks. Advantages: Simple and user-friendly web interface. Supports using images and videos in addition to text prompts. Completely ad-free in the free version. Provides editing tools for generated tracks. Automatic selection of cover images for compositions. Official mobile app available for iOS and Android. Disadvantages: The free version includes 50 credits, allowing only 5 compositions per day; 50 more credits are added daily. Duration limits depend on the AI model used: v2 up to 1:20 min, v3 up to 2 min, v3.5 up to 4 min. AIVA AIVA is one of the best AI music generators designed specifically for creating music, from classical and symphonic compositions to electronic dance music tracks. AIVA was first released in February 2016 by Luxembourg-based Aiva Technologies SARL. Advantages: Advanced editing tools: change tempo, key, duration, style, and instruments. Ability to upload existing tracks to use as templates. Export of compositions in MIDI, WAV, or MP3. Official documentation available. Available as a web interface or desktop app (Windows, macOS, Linux). Monetization of tracks (only in the Pro plan). Disadvantages: The free plan allows only 3 downloads per month. Limited editing features in the free version. Soundraw Soundraw is an online AI song generator, launched in February 2020 by Japanese company SOUNDRAW, Inc. Soundraw is suitable for creating tracks in any genre. It can be used by individuals to create personal tracks or by artists and labels for commercial music (paid plans only). Advantages: Simple, intuitive web interface. Ability to mix multiple genres in a track. Extensive editing options: track length, tempo, genre, mood (epic, happy, angry, sentimental, romantic, etc.), and theme (corporate, cinematic, comedy, documentary, etc.). API available (as of 2025, API for music generation is available in the Enterprise plan only). Disadvantages: Track downloads require a subscription. Mubert Mubert is an online AI platform for generating music tracks in real-time using text prompts, images (.png, .jpg, .webp), or by selecting a genre. Ideal for background music in videos and podcasts. Advantages: Simple 3-click track creation. You can specify genre, mood, track type (Track, Loop, Mix, Jungle), and duration (5 seconds–25 minutes). API available (beta) for registered users. Mubert Studio allows monetization and promotion of tracks. Official iOS and Android apps available. Integration with YouTube, Twitch, TikTok, Streamlabs, Kick. Disadvantages: Instrumental-only tracks; no vocals. Free plan: 30 min/day, 25 tracks/month; paid plans increase limits (up to 500–1000 tracks). Cannot mix multiple genres or use sound effects. No track stems or MIDI export. MusicGEN MusicGEN is a simple AI service for creating music via text prompts or audio samples. Focused on short tracks (up to 2 minutes). Requires installation and setup, which can be challenging for beginners. Advantages: Simple interface. Open-source AudioCraft language model used in MusicGEN and AudioGen. Ready-made implementations available online. Disadvantages: Requires technical skills for setup. Tracks limited to 15 seconds. No customization during track creation. Loudly Loudly is a platform with built-in AI for generating music and tracks. Tracks can be created via text description or a built-in generator. Ideal for social media, videos, and streaming services. Advantages: Rich functionality: choose instruments, genre (15+ including EDM, Hip Hop, Techno, Rock), tempo, subgenres. Built-in templates with flexible filters. API available on request. Disadvantages: Free version: 25 tracks/month, 30 sec each; cannot download tracks. Riffusion Riffusion is an AI service based on the Stable Diffusion deep learning model, generating short music fragments including vocals using text prompts. Advantages: Free, unlimited creation in "relax mode." Ability to create remixes and covers. You can provide the song lyrics.  The web version allows grouping tracks into projects and playlists. Disadvantages: Paid plan required for commercial use. Paid plans allow audio uploads, WAV and Stem downloads. Limited editing functionality compared to competitors. Conclusion: Comparative Table Feature Suno AI AIVA Soundraw Mubert MusicGEN Loudly Riffusion Music creation method Text, images, video Styles, chords, MIDI, or track Interface with options Text, images, filters (genre, mood, tempo) Text prompt, audio import Text prompt, generator Text, image, interface with options Free plan Limited: 5 compositions/day (50 credits) Limited: 3 tracks/month, max 3 min, MP3/MIDI only Limited: cannot download Limited: 25 tracks/month, MP3 only Unlimited Limited: 25 tracks/month, max 30 sec, no download Limited: cannot download or use commercially Paid plans Pro $10, Premier $30/month, 20% annual discount Standard €15, Pro €49/month, 33% annual discount $11.04–$32.49/month, Enterprise by request $11.69–$149.29/month, custom & lifetime plans None (open-source) Personal $10, Pro $30/month Starter $8, Member $48/month, 25% annual discount Interface language English English English, Japanese English, Spanish, Korean English English English Supported song languages 50+ English English English English English English Music editing Text, style, audio template, instrumental style, duration Tempo, chords, instruments, effects, duration Tempo, genre, mood, theme, duration Genre, mood, track type, duration (5 sec–25 min) None Genre, mood, tempo, instruments, duration Text, style Commercial use Paid plans only Pro plan only Artist Starter & above Paid plans only None Paid plans only Paid plans only API No No Yes Yes (on request) No Yes No Export formats Free: MP3, Paid: MP3, WAV, stems Free: MP3, MIDI; Pro: MP3, WAV Paid only: MP3, WAV, stems Free: MP3 (25 tracks/month), Paid: up to 1000 tracks WAV only Paid: MP3, WAV Paid: WAV, stems Mobile app Yes (iOS, Android) No No No No Yes (iOS, Android) No Desktop app No Yes (Windows, macOS, Linux) No No No No No

ChatGPT is a powerful tool for generating text, code, creating content strategies, and even working with images. It allows users to get accurate answers to complex questions across many fields of human activity. Developed by OpenAI based on the GPT architecture, this AI assistant can understand context, maintain long conversations, and adapt its communication style to the user’s needs. To get the most useful answers, it’s important to learn how to properly formulate requests, or “prompts,” for ChatGPT. We’ll explain this in more detail below. We’ll also share the best ChatGPT prompts to help you work more efficiently, show how to build well-structured requests, give examples with detailed ChatGPT responses, and explain how to write prompts for visual content through DALL·E. All examples in this article use the free version of ChatGPT. What Prompts Are and Why They Matter A prompt is a text request that a user sends to ChatGPT or another AI model to get a desired answer. Simply put, it’s an instruction for the neural network explaining exactly what you want to receive. Why is it important to create a good prompt for ChatGPT? Here are the main reasons: Improved answer accuracy: The clearer and more detailed your prompt, the more relevant and useful the response will be. Time savings: A well-structured request saves you from repeatedly rephrasing or clarifying your question. Fewer mistakes: Clear instructions reduce the risk of incorrect or outdated information. Optimized workflow: Good prompts let you automate complex tasks, from content creation to data analysis. Structured results: Properly designed prompts help get answers in the needed format: lists, tables, step-by-step guides, etc. Personalized responses: Adding context to your request makes ChatGPT’s answers more relevant to your needs (context includes role, tone, audience, format, etc.). Better AI learning: Well-crafted prompts help the AI understand your preferences over time. That’s why it’s best to keep an ongoing conversation with ChatGPT within one chat thread when working on the same topic. ChatGPT analyzes your request and provides the most relevant answer based on previously learned data. The clearer your prompt, the more accurate the AI’s response will be. Examples of Weak and Strong Prompts 🔴 Weak Prompt 🟢 Strong Prompt “Collect information about clouds.” “Write a 1,000-word piece about the benefits of cloud technologies for small businesses. Include a comparison of Hostman with competitors.” “Tell me about hosting.” “Compare Hostman and AWS pricing for high-traffic websites. Highlight the pros and cons of each.” “Write something about marketing.” “Write 5 marketing strategies for promoting a SaaS product in 2025 via Facebook. Format: short description + 3 concrete actions for each.” How to Create Your Own Prompts Below are the main rules for writing effective prompts and common mistakes to avoid when working with ChatGPT. Rules for Writing Prompts Main principles for crafting perfect prompts: The more specific your request, the more relevant the answer. Always specify the desired output format (list, table, step-by-step guide). For professional tasks, add context (AI’s role, difficulty level, target audience). Use examples and analogies to match your expectations precisely. Clearly state any constraints or special requirements. Indicate timeframes for data relevance. Ask for sources when you need verified information. Balance detail with conciseness. Another useful tip: save successful prompts somewhere convenient: a text editor, personal notes, or a dedicated ChatGPT chat named “Templates.” This helps in the future since many prompts can be reused simply by changing key parameters. You can also use existing prompt libraries and adapt them to your needs, for example, prompthackers.co. Common Mistakes Here are typical mistakes when writing prompts, along with examples of how to improve them: Too general requests 🔴 “Tell me about AI.” 🟢 “Explain how ChatGPT is used in the banking sector in 2025.” Lack of structure 🔴 “Give tips on time management.” 🟢 “Create a checklist: ‘5 time management methods for remote workers.’ Format: Name → Essence → Example.” Ignoring context 🔴 “Write a text.” 🟢 “Write a commercial proposal for Hostman (audience: CTOs of mid-sized companies). Tone: expert, but conversational.” Vague clarifications 🔴 “Make it shorter.” 🟢 “Reduce to 300 words, keeping key data from the table.” Overloading with details 🔴 “Write an article about cloud technologies but exclude AWS, Microsoft Azure, IBM Cloud, Oracle Cloud, DigitalOcean, Linode, Vultr.” 🟢 “Write an article ‘AWS Alternatives for Small Businesses’ with the main focus on Hostman” Top 10 Universal Prompts for ChatGPT This section includes ready-made prompt templates that will become reliable tools when working with ChatGPT. These prompts cover a wide range of tasks, from creative brainstorming to complex technical analysis. We’ll look at 10 universal and practical prompts for the following categories: Analysis and comparison Idea generation Psychology and self-development Content strategy Writing and editing Programming Image generation (DALL·E) Learning and education Business Creativity Each template is: Well thought out: structured for high-quality answers Universal: suitable for both beginners and professionals Flexible: easily adaptable to specific needs To use a template, choose the category and replace the placeholders in square brackets with your own values. For complex tasks, you can even combine several templates into one (an example will be shown at the end of the section). All prompts are optimized for GPT-4 and newer versions to ensure highly relevant results even for advanced professional use. 1. For Analysis and Comparison Purpose: Professional comparison of products, services, or technologies based on specific criteria with expert conclusions. Ideal for: Selecting IT solutions, preparing reviews, making business decisions. Template: Compare [Object A] and [Object B] by the following criteria: [1–5 parameters]. Format: table with columns “Feature,” “Object A,” “Object B,” and “Recommendation.” Specify the best option for [scenario]. Example: Compare Hostman VPS and Linode VPS by: price per 1 vCPU, SLA, support speed, and control panel usability. Highlight the optimal choice for a startup with 50K visitors/month. ChatGPT response: Tips: Set timeframes: 🔴 “Compare hosting prices.” 🟢 “Compare 2025 hosting prices including seasonal discounts.” Ask for data sources: 🔴 “Which platform is better?” 🟢 “Compare using data from official websites and independent tests.” Provide context: 🔴 “Which is cheaper?” 🟢 “Which is more cost-effective for a site with 50K visits/month: shared hosting or VPS?” Ask for alternatives: “If the budget is limited to $35/month, what are Hostman’s alternatives?” Specify output format: “Present the data in a table, then give a short verdict for beginners.” 2. For Idea Generation Purpose: Structured brainstorming with clear logic. Application: Finding concepts for startups, content marketing, product design, or creative projects. Template: As a [role], suggest [N] ideas for [task]. Structure: 1) Title → 2) Target Audience → 3) Benefit → 4) Example → 5) Risks.Focus on: [requirements]. Example: As an art director, suggest 5 ad campaign ideas for Hostman in the metaverse. Focus on interactivity and B2B audience. ChatGPT response: Tips: Rank ideas by priority: 🔴 “Give 5 post ideas.” 🟢 “Suggest 5 social media post ideas about Hostman, sorted by feasibility/effectiveness. Consider: budget up to $100, B2B engagement.” Define evaluation criteria: “Exclude ideas requiring more than 3 days to execute.” “Prioritize ideas with viral potential.” Ask for examples: “Show similar cases from the industry for the top 3 ideas.” Limit scope: “Only ideas that don’t require contractors.” “Focus on formats: guides, case studies, interactives, polls.” Request next steps: “For the best idea, outline a 3-day action plan.” 3. For Psychology and Self-Development Purpose: Scientifically grounded methods for solving personal and professional issues. Especially useful for: coaching, stress self-help, and developing emotional intelligence. Template: As a [specialist], create a [duration]-long plan for solving [problem].  Include: 1) Theoretical foundation → 2) Step-by-step techniques → 3) Self-diagnosis tools → 4) Recommended resources.  Adapted for: [audience]. Example: As an HR expert with experience in IT, design an 8-week onboarding program for a new employee at a cloud company. Include: Role introduction plan (days 1–30, broken down by week) Methods for evaluating professional skills (checklists, test tasks) Mentorship system (roles, meeting frequency, KPIs) Recommendations for integrating into corporate culture (events, company traditions) ChatGPT response: Tips: Require scientific backing: 🔴 “How to deal with anxiety?” 🟢 “Using CBT (Beck) and the ABCDE model (Ellis), propose a 4-week anxiety management plan for IT specialists. Include research on the effectiveness of these approaches.” Specify theories: “Explain burnout stages using the Maslach model (emotional exhaustion → cynicism → reduced productivity).” “For procrastination, use Piers Steel’s temporal motivation theory.” Request context adaptation: “Apply Gestalt therapy techniques to conflict situations in remote teams.” “How can the GROW model be applied to IT career coaching?” Ask for self-assessment tools: “Add a checklist for tracking progress on a 1–10 scale.” “What 3 questions can help identify the stage of stress according to Selye?” Limit complexity: “Explain terms in simple words, suitable for beginners.” “Exclude medical recommendations.” 4. For Content Strategy Purpose: Comprehensive publication planning with measurable KPIs. Ideal for: blogging, SMM, email marketing, and sales funnels. Template: As a [position], create a [time period] strategy.  Include: 1) Target personas → 2) Thematic clusters → 3) Calendar (format/KPIs) → 4) Tools. Example:  As a head of content marketing, develop a quarterly blog strategy for Hostman with KPIs focused on trial conversions. Emphasize guides about migrating from competitors. ChatGPT response: Tips: Tie it to business goals: 🔴 “Need a content plan.” 🟢 “Develop a quarterly strategy for the Hostman blog with KPI: +15% increase in trial conversions. 70% educational content, 30% case studies.” Specify success metrics: “For Facebook posts, define target metrics: CTR >3%, engagement >5%.” “Estimate potential reach for each topic.” Request cross-channel integration: “How can a guide be turned into a Facebook post series and email campaign?” “Propose a cross-promotion scheme between YouTube and the blog.” Ask for competitor analysis: “Add analysis of 2 successful strategies from competitors in the cloud segment.” “Which topics bring the highest engagement for competitors?” Limit resources: “For a 2-person team: 1 long-read per week + 3 social channels.” “Without hiring copywriters.” 5. For Working with Texts Purpose: Creating and optimizing commercial or informational materials. Fields: copywriting, SEO, technical documentation, scripts. Template: As a [role], write a [type of text] for [target audience]. Parameters: length → style → required elements → restrictions → SEO. Structure: [sections]. Example: As a technical writer, create a guide titled “Setting Up WordPress on Hostman” (1,500 words). Avoid jargon, include GIF instructions. ChatGPT response: Tips: Clearly define the text’s purpose: 🔴 “Write a text about clouds.” 🟢 “Write a commercial proposal for Hostman aimed at small businesses. Goal: conversion into demo requests.” Set style and tone: “Tone: friendly yet professional, as if explaining to a colleague.” “Avoid bureaucratic phrases; write naturally.” Add SEO parameters if needed: “Include keywords: ‘cloud hosting,’ ‘VPS for business,’ ‘reliable hosting.’ Keep keyword density natural.” “Add LSI words: ‘scalability,’ ‘data security,’ ‘uptime.’” Request examples and comparisons: “Provide 3 strong headline examples for this kind of article.” “Compare with competitor texts: what can be improved?” Limit length and complexity: “Max 1,000 words, divided into H2-H3 subheadings.” “Explain terms like ‘CDN’ in parentheses in simple words.” 6. For Programmers Purpose: Code generation and analysis with full documentation. Main uses: writing scripts, debugging, creating APIs, automating DevOps processes. Template: As a [language] developer of [X] level, write code for [task]. Input → expected output → constraints → requirements. Format: algorithm → code → tests. Example: As a senior Python developer, create a server monitoring script for Hostman with API integration and Telegram notifications. Requirements: async, logging. ChatGPT response: Tips: Specify exact versions: 🔴 “Write a backup script.” 🟢 “Write a Python (3.10+) script for daily MySQL (8.0) backups to Hostman S3. Requirements: async, file logging, Telegram error alerts.” Request explanations: “Add comments every 5 lines to clarify complex code sections.” “Explain why you chose this algorithm (e.g., QuickSort vs. MergeSort).” Require tests: “Add 3 unit tests with edge cases.” “How to test this API in Postman?” Ask for alternatives: “Show alternative solutions in Go and Rust. Compare performance.” Set constraints: “No external libraries.” “Execution time ≤100ms for 10K records.” 7. For Image Creation (DALL·E) Purpose: Precise technical specifications for neural image generation (DALL·E). Applications: ad banners, article illustrations, concept art, presentations. Template: As an art director, create a prompt: 1) Object → 2) Style → 3) Composition → 4) Color palette → 5) Lighting → 6) Restrictions. Goal: [usage]. Example: Create a prompt for a “Hostman Enterprise” banner: a cyberpunk-style server, palette #0A1640/#00C1FF, HUD elements, no people. ChatGPT response: Image generated by ChatGPT: Tips: Be extremely specific: 🔴 “Draw a cloud server.” 🟢 “Generate a 3D render of a Hostman server in blue-white tones. Style: cyberpunk with neon accents. Background: network map with nodes. Aspect ratio 16:9, no people.” Reference known styles: “In the style of the interfaces from the Foundation series.” “Like Wired magazine covers from the 2020s.” Control composition: “Main object centered, occupying 70% of the frame.” “Blurred background with depth-of-field effect.” Request variations: “Show 3 versions: minimalism, retro-futurism, and photorealism.” “Change only the palette to dark/light mode.” Technical constraints: “No text in the image.” “Resolution: 1024×1024, format: PNG.” 8. For Learning and Education Purpose: Designing educational programs using modern methodologies. Application: course creation, training materials, workshops, interactive modules. Template: As a professor of [subject], design a [number]-hour module. Include: goals → plan (theory/practice) → adaptations → glossary. Constraints: [parameters]. Example: Develop an 8-hour course “Cloud Fundamentals” for university students: lectures in Prezi, labs on Hostman, quizzes in Kahoot. ChatGPT response: Tips: Base on teaching models: 🔴 “Create a Python course.” 🟢 “Using the ADDIE model (Analysis, Design, Development, Implementation, Evaluation), create a 4-week course ‘Python for Data Analysis.’ Goal: teach students to visualize data using Matplotlib.” Define difficulty level: “For junior DevOps: basics of Kubernetes.” “For senior developers: algorithm optimization in C++.” Add interactive elements: “Include 3 simulated real-world cloud development cases.” “Propose a gamification format for a cybersecurity module.” Require practical tasks: “Design a lab exercise: deploying a web app on Hostman.” “Create a test assignment with automatic checking via GitHub Actions.” Consider technical limitations: “Course must run on low-end PCs (no Docker).” “Use only free tools (VS Code, Colab).” 9. For Business Purpose: Strategic market and process analysis. Applications: business planning, SWOT analysis, competitor research, financial modeling. Template: As a consultant from [company], conduct an analysis of [object] using the following framework:  1) Market Size → 2) PESTEL → 3) Benchmarking → 4) SWOT → 5) Forecasts. Data sources: [list of references]. Example: Analyze the European cloud gaming market: 2024 market size, PESTEL factors, comparison of NVIDIA GeForce Now / Shadow PC / Boosteroid, and projections through 2026. ChatGPT response: Tips: Be specific with goals: 🔴 “How to increase profits?” 🟢 “Develop 3 revenue growth strategies to increase a SaaS startup’s revenue by 30% within 6 months. Focus: upselling existing clients and reducing churn rate. Use the AARRR framework.” Ask for supporting data: “Analyze the European cloud services market (size, trends, competitors). Use sources such as Statista, Gartner, and official company reports.” “Calculate CAC for our current ad campaign.” Request alternative approaches: “What are the best options for entering the EU market: partnerships vs. independent launch?” “Compare investment risks for expanding VPS services versus cloud storage solutions.” Link to business processes: “How can the new product be integrated into our existing SaaS ecosystem?” Consider resource limitations: “Budget: up to €50,000, team of 5 people.” “Propose solutions that don’t require hiring additional staff.” 10. For Creativity Purpose: To generate compelling stories and concepts. Ideal for: Writers: for books and short stories; Screenwriters: for films and series; Game developers: for characters and worldbuilding; Musicians: for album or concept creation. Template: As a [profession], create a [type of work] in the [genre] style. Parameters: Characters → Setting → Conflict → Style. Format: Logline → Synopsis → Scene breakdown. Example: As a Black Mirror-style screenwriter, develop a concept for an episode about AI in 2045, exploring the theme “Privacy vs Convenience.” ChatGPT response: Tips: Be specific about genre and audience: 🔴 “Write a story about a scientist.” 🟢 “Write the first chapter of a science fiction story about a bioengineer who discovers how to edit DNA using quantum computers. Style: mix of Black Mirror and The Martian. Audience: hard sci-fi fans (ages 25–45), with emphasis on scientific realism.” Request structure: “Outline the plot using Joseph Campbell’s ‘Hero’s Journey’ model.” “Create a dialogue example with subtext (in the style of Aaron Sorkin).” Ask for visualization: “Describe a key cinematic shot for a poster in the style of Blade Runner.” “Which color palette best conveys the atmosphere?” Avoid clichés: “Exclude tropes like ‘the chosen one’ or ‘evil AI.’” “Suggest three unexpected plot twists.” Consider technical constraints: “Script for a 10-minute short film (maximum 5 locations).” “Concept for a mobile game with simple gameplay.” Combined Prompt Example The prompt templates presented above cover most professional user tasks. For maximum efficiency, you can combine them, for example: analysis (section 1) + text generation (section 5) + visualization (section 7). Example prompt Act as both an IT analyst and a digital marketer. I need a comprehensive comparison of cloud hosting platforms (AWS, Google Cloud, and Hostman) with materials ready for publication. Perform the following tasks sequentially: 1. Conduct a detailed analysis: Compare by: cost per vCPU, SSD size, network bandwidth, SLA uptime. Present results in a table with columns: “Feature,” “AWS,” “Google Cloud,” “Hostman.” Conclude with a recommendation for a startup with a $50/month budget. 2. Write an SEO article based on the analysis: Title: “AWS vs Google Cloud vs Hostman: An Objective Comparison for 2025.” Length: 2,000 words. Structure: Introduction (importance of choosing the right provider); Methodology; In-depth review of each provider; Summary table (from step 1); Recommendations for different use cases. Tone: Expert but accessible; Keywords: “cloud hosting,” “VPS comparison,” “Hostman review.” 3. Create visualization prompts (for DALL·E or Midjourney): Style: Corporate infographic (blue and white color palette). Elements: 3D servers with provider logos; Comparative performance and pricing charts; “Price/Performance” scale; Minimalist background with digital accents. Formats: Article cover, comparative infographic, architecture diagram. 4. Additional tasks: Suggest 3 social media posts based on the article. Format: “Did you know that…” + key takeaway + infographic. Platforms: LinkedIn, Reddit. Ensure all data is consistent across text and visuals. Numbers in the text must match tables and charts. Use professional terminology, but explain complex terms for beginners. ChatGPT response: This prompt structure provides: A unified request instead of multiple separate ones; Logical flow: analysis → writing → visuals → promotion; Consistent data across all materials; Publication-ready results. For even higher precision, you can add: “Before starting, ask 3 clarifying questions to better define the task.” This approach helps the AI better understand the project and deliver higher-quality results. Key Takeaways In this article, we explored what prompts are and how to craft them effectively, showcasing 10 universal examples across different categories. A prompt is a text instruction you send to ChatGPT to get a desired response. The clearer and more detailed the prompt, the more accurate and useful the result. Core principles of effective prompting: Clarity and detail (including timeframes, parameters, and constraints); Specify the response format (table, list, step-by-step guide); Add context (AI role, complexity level, target audience); Include examples and analogies for clarity; Note technical requirements (length, tone, restricted elements). Common mistakes: Overly vague prompts (“Write something”); No structure or logic; Ignoring context (missing role or audience); Overcomplicating with conflicting details; Poor clarification (missing data or specific names). Improvement tips: Start broad, then refine details step by step; Save successful prompts as templates; Request data sources for analytical tasks; Use iterations: “Add to the previous answer…” Additional recommendations: For creative work, include stylistic references; For technical tasks, specify software versions or languages; For business analysis, ask for alternative scenarios; Always verify critical data. ChatGPT is a tool, not a substitute for expertise. Save the templates from this guide as a quick-reference list and adapt them over time to fit your workflow. By mastering the art of crafting effective prompts, you’ll unlock ChatGPT’s full potential, transforming it into a personal assistant for work, creativity, and learning. Experiment with phrasing, analyze results, and refine your prompts: that’s how you’ll make AI a truly powerful tool in your toolkit.

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