New AI-based code assistant tools allow automating a large part of software development. Each solution has its strengths and limitations. Below we analyze four popular code agents: GitHub Copilot CLI, Anthropic Claude Code (Opus 4.5), Google Gemini Code Assist, and DeepSeek Coder, integrating real usage experiences and recent references.
Command Execution and Terminal Agents
GitHub Copilot CLI is Copilot's terminal version. It allows starting an interactive AI session directly from the command line, working on local code. According to official documentation, "GitHub Copilot's command-line interface (CLI) lets you use Copilot directly in your terminal." In a Copilot CLI session, the agent can read and modify files, execute commands (e.g., !npm install), and even create pull requests on GitHub automatically.
Anthropic Claude Code (Opus 4.5 model) works as a coding agent assistant that can run in terminals, IDEs, or its own desktop app. Claude Code automates tasks from code generation and refactoring to testing and deployments. According to Anthropic, "developers use it as a direct collaborator in their terminal, IDE, or through cloud APIs." This means it can execute local commands, fix bugs, and manipulate large projects with full context, all while the user supervises.
Google Gemini CLI (part of Gemini Code Assist) is an AI code agent based on Gemini 2.5. Google states that Gemini CLI offers "powerful AI capabilities, from code understanding and file manipulation to command execution and dynamic problem-solving." Additionally, the individual Gemini Code Assist service is free up to certain daily limits (6,000 code requests and 240 daily chats). In practice, it allows requesting code creation or fixes via terminal, although some users have reported it can generate very long outputs if the prompt isn't controlled.
DeepSeek Coder also offers a command-line agent (DeepSeek CLI) that can be installed locally or in the cloud. The tool supports installation via Ollama (local model) or cloud API. According to its repository, DeepSeek CLI offers autocomplete and code generation in 100+ languages, large codebase analysis, refactoring, and bug detection. In other words, DeepSeek CLI can execute terminal commands like Copilot or Gemini, although it doesn't include automatic tests out of the box: it focuses on generating or fixing code upon receiving instructions.
Complex Problem Solving and Planning
- Multi-stage tasks: Claude Opus 4.5 excels at reasoning about complex failures and planning solutions. Anthropic reports that Opus 4.5 can "solve a complex bug across multiple systems" and handle very demanding coding workflows. In our experience, Claude (and Copilot) have identified root causes of network errors or infrastructure configuration issues in production. For example, a Copilot session discovered a busy network preventing TLS certificate renewal via Certbot, something neither the code nor logs clearly showed.
- Code precision: DeepSeek Coder models have also been extensively trained on code (2 trillion tokens) and perform very well on benchmarks. The instructive DeepSeek-Coder-33B model surpasses GPT-3.5-turbo on Python HumanEval tests. Overall, both Claude Opus 4.5 and large DeepSeek models offer cutting-edge code quality, although Claude tends to generate more refactored and better-structured solutions. In contrast, Gemini (and DeepSeek) tend to focus on generating the requested functionality, sometimes without as much style optimization.
- Planning and clarity: Copilot CLI offers a "planning" mode to outline steps before writing code (pressing Shift+Tab). Claude Code also tends to ask for confirmations and details before executing changes. In contrast, Gemini may "jump in" directly to generate a lot of code if not stopped with appropriate prompts. In summary, Copilot and Claude are more proactive in questioning and planning, while Gemini and DeepSeek may require more human supervision in the conversation.
Token Usage and Costs
The four solutions have different business models:
- Copilot CLI comes included with the GitHub Copilot subscription. It doesn't publicly charge per token, although intensive enterprise use is regulated by licenses. There are no "tokens" exposed to the user, but there are usage limits in corporate environments.
- Claude Opus 4.5 is billed per token. Anthropic announced prices of $5/$25 per million tokens (input/output). This can consume credit quickly if long tasks are launched or a bug is repeatedly addressed. It's key to use concise prompts or planned sessions. Claude sometimes "burns" tokens correcting even minor details, so its progress needs supervision.
- Gemini Code Assist (individual) is currently free up to certain limits: the free edition offers 60 requests per minute and 1,000 per day (the site indicates 6,000 code/day). Unlike Claude, it doesn't charge per token individually. For enterprises or Pro/Ultra licenses, there are extended limits.
- DeepSeek Coder is notably affordable: around $0.14 per million tokens (compared to $10 for GPT-4). A small credit (e.g., USD $5-10/month) allows hundreds of requests and tens of millions of tokens. This makes DeepSeek very viable for individual developers.
In summary, DeepSeek is the cheapest, followed by Gemini (free with limits) and then Copilot/Claude.
Frontend, Backend, and Testing Automation
- UI Prototyping: Claude Code includes a unique functionality: it can take an image or screenshot and generate the corresponding UI code. Just pass it a mockup or design screenshot, and Claude will produce HTML/CSS or Flutter code for the UI. This greatly speeds up frontend development. Neither Gemini nor DeepSeek offer this in an integrated way; they focus on text/IDE. Copilot also generates UI parts from descriptions, but not from images.
- Backend logic: All tools can implement business logic, consume APIs, and connect databases. In our tests with C#/.NET and Flutter, we asked agents for complex functions (authentication, Stripe payments, etc.). Copilot and Claude tend to handle security details or infrastructure errors better. Gemini and DeepSeek can generate basic code (classes, controllers, services) but require reviewing fine integration.
- Testing and integration: Claude Code can write unit and integration tests, and even validate they pass. Copilot CLI allows running test commands (
!dotnet testor/run tests) and examining results, facilitating iterative debugging. Agents can create E2E integration test suites, especially if you provide a testing framework. When we migrated from Playwright to Patrol (for better Flutter Web compatibility), Copilot sped up converting old tests to the new syntax. - DevOps and deployments: All can help with infrastructure scripts. Claude Code can automatically generate CI/CD scripts and server administration. For example, we asked Claude to prepare a GitHub Actions pipeline for Docker deployment and it returned a functional YAML. These AIs can advise on HTTPS, TLS certificates, environment variables, and rate limits.
Development and Repository Integration
- Extensions and plugins: GitHub Copilot and Google Gemini Code Assist offer official extensions for VS Code and other IDEs. They're easy to install: just search "Copilot" or "Gemini" in the marketplace. Claude Code was recently integrated into the Claude Desktop application (supporting Windows/macOS/Linux); there's no native Claude extension for VS Code yet, although Claude Chat exists in some environments. DeepSeek doesn't have as polished an official extension; for VS Code, it's recommended to use generic AI agent extensions (like "Continue" or others) that send requests to its API.
- Version control (Git): Copilot CLI greatly facilitates Git. With the
/delegatecommand, Copilot can create a new branch, commit changes, and open a pull request automatically. This allows "delegating" complex tasks to the agent while maintaining full context. Gemini Code Assist can also review and suggest changes on GitHub PRs. DeepSeek, operating via CLI, allows editing local files but relies on the traditional Git flow (manual commits). Additionally, Copilot can generate descriptive commit messages, review code for style issues, and resolve basic conflicts when instructed.
In summary, Git integration is very smooth with Copilot/Gemini; with DeepSeek and Claude it requires extra steps from the developer.
Practical Use Cases
In real projects, we've experienced several cases that illustrate these differences. For example, Copilot and Claude detected that a virtual network was occupied by another service during TLS certificate deployment with Docker. This finding wasn't evident locally, only in production, and the agent solved it by restarting the appropriate resource.
Another case involved Stripe payments: when trying to automate account creation and charges, synchronization errors arose between the Flutter frontend and the .NET backend. After several iterations, Copilot suggested fixing the malformed HTTP call; Claude proposed adding an additional server-side check. Both tools accelerated the resolution of these complex bugs.
We also faced test migration: we started with Playwright, but when using Flutter Web the team switched to Patrol. With AI assistance, we quickly converted old tests to Patrol without schedule delays.
Finally, when implementing complete CI/CD pipelines, at one point Copilot and Claude exhausted their token quotas. That's where DeepSeek proved useful: it continued generating missing scripts for the final deployment, completing the planning previously initiated by the other AIs. In practice, these agents can be used complementarily: when one runs out of tokens or hits usage limits, the team can switch to another without losing productivity.
Conclusions and Recommendations
In summary, each agent has distinct strengths. Copilot CLI and Claude Code (Opus 4.5) are the most powerful globally: they execute commands, handle broad context, and solve complex problems with SOTA code quality. They also facilitate continuous integration (CI/CD) and code review. However, they are more costly in tokens (or subscriptions) and sometimes over-process minor errors.
Gemini Code Assist is a solid option for everyday IDE code generation (free with daily limits), although it can generate too much code if not moderated. DeepSeek Coder excels in efficiency: it offers specialized programming models with high performance and very accessible pricing. It's ideal for initial tasks and prototypes, where its low cost and step-by-step dialogue mode allow exploring functionalities without exhausting budget.
"The best strategy is usually to combine them: use DeepSeek for sketches and base code generation, then Copilot/Claude for debugging complex bugs, optimizing architecture, or finalizing deployment. This synergy maximizes productivity: each tool contributes its strength."
In any case, it's key to provide good prompts and guide the agent to avoid wasting tokens and achieve high-quality results. These AIs already behave almost like real development assistants, streamlining both frontend and backend, testing and deployments, but they require human supervision for best results.