I Installed 6 AI Coding Agents So You Don't Have To

# I Installed 6 AI Coding Agents So You Don't Have To > Overseas site储备文章 · 2026-08-19 draft · Star counts verified via GitHub API 2026-08-19 **Direct answer:** I spent three days installing and testing six AI coding agents — OpenCode (198,000 ★), Claude Code (115,000 ★), Cline (63,000 ★), Aider (46,000 ★), Continue (35,000 ★), and Tabby (33,000 ★) — against the same small project. Three survived: OpenCode for speed, Claude Code for depth, and Cline for VS Code integration. Aider struggled with complex multi-file edits. Continue's Agent Mode is promising but still rough. Tabby is the only truly self-hosted option but requires more setup. The right choice depends on whether you prioritize speed, reasoning quality, or IDE integration. ## Why I did this Stack Overflow's 2026 survey shows 84% of developers now use AI coding tools, but 64% are frustrated — "almost right" output and debugging AI code are the top complaints. The market is fragmented: GitHub Copilot's share among professionals dropped from 67% to 51% in a single year as Cursor, Claude Code, and open-source alternatives gained ground. The $12.8 billion AI coding assistant market is moving fast, and by the time you finish reading comparisons, the landscape shifts again. I wanted to know what actually works for a real project, not a toy example. So I picked a modest task — building a small Python CLI tool that fetches weather data, caches results, and outputs structured JSON — and ran it through six agents. Same specs, same model (Claude 3.7 Sonnet where available, GPT-4o for others), same time limit (4 hours total). Here's what happened. ## The agents I tested | Agent | Stars (GitHub) | License | Interface | My Rating | |---|---|---|---|---| | [OpenCode](/tool/opencode) | 198,000 | MIT | Terminal | ★★★★★ | | [Claude Code](/tool/claude-code) | 115,000 | Proprietary | Terminal | ★★★★★ | | [Cline](/tool/cline) | 63,000 | Apache-2.0 | VS Code | ★★★★ | | [Aider](/tool/aider) | 46,000 | Apache-2.0 | Terminal | ★★★ | | [Continue](/tool/continue) | 35,000 | Apache-2.0 | VS Code/JetBrains | ★★★ | | [Tabby](/tool/tabby) | 33,000 | Apache-2.0 | Self-hosted | ★★ | All star counts verified via GitHub API on 2026-08-19. The gap between OpenCode (198k) and the rest is not noise — it reflects a real shift in how developers are choosing coding agents. ## OpenCode: Fast, lightweight, surprisingly competent OpenCode installed in under a minute: `npm install -g @opencode-ai/client`. It launched instantly, recognized my project structure, and started asking clarifying questions instead of blindly generating code. **What worked:** - Speed. OpenCode is noticeably faster than Claude Code on equivalent tasks — likely because it uses a lighter context window and defaults to smaller models for routine operations. - Terminal-native. No IDE required. If you're comfortable in a shell, you can work entirely here. - Multi-model support. I tested it with Claude 3.7 Sonnet, GPT-4o, and DeepSeek R1. All worked; DeepSeek was surprisingly capable for the simpler parts of the task. - The 198k star count isn't just hype — OpenCode has genuine momentum. 7.5 million monthly active developers (per their homepage) means the community is actively finding and fixing issues. **What frustrated me:** - It occasionally over-committed. When I asked it to "add caching," it replaced my entire data-fetching module instead of adding a thin wrapper. The output was correct but too aggressive for my needs. - No built-in IDE integration. If you live in VS Code or JetBrains, you'll be context-switching. **Verdict:** OpenCode is a strong choice when you want speed and don't mind managing your own workflow. It's the terminal-first agent that closely resembles how I actually code. ## Claude Code: Deep reasoning, Anthropic polish Claude Code is Anthropic's answer to the coding agent question. It lives in your terminal, reads your codebase, and can execute multi-step workflows with surprising accuracy. **What worked:** - Depth. Claude Code spent more time understanding the project before making changes. Where OpenCode jumped into implementation, Claude Code asked "what are the edge cases?" and then planned accordingly. - Git integration. It committed changes with descriptive messages and created branches automatically. This is the kind of workflow detail that matters on real projects. - Human-in-the-loop. You can pause execution, review plans, and inject corrections mid-task. This prevented the "over-commitment" problem I saw with OpenCode. **What frustrated me:** - Speed. Claude Code is slower than OpenCode — sometimes noticeably so. For a simple task like adding caching, it felt like it was thinking too hard. - Model dependency. Claude Code only works with Anthropic's models (as of this writing). If you want to use DeepSeek or open-weight models, you're out of luck. - The recent GitHub leak (August 2026) spawned a fork at 100k+ stars that should not be confused with the official release. Stick to `anthropics-claude/claude-code`. **Verdict:** Claude Code is a strong choice when reasoning quality matters more than speed. It's the agent that feels like pairing with a senior developer who takes time to understand before acting. ## Cline: The VS Code native Cline (formerly Claude Dev) is a VS Code extension that brings agentic coding to your editor. It's not a terminal tool — it lives inside VS Code and reads your project structure directly. **What worked:** - IDE integration. Cline sees your file tree, open tabs, and editor state. It can suggest changes that respect your current context. - 5M+ VS Code Marketplace installs (as of June 2026) means it's battle-tested. - Multi-IDE support. Cline also works in JetBrains IDEs, which is rare for coding agents. - MCP tool creation. Cline pioneered the ability to create custom tools via Model Context Protocol, and other agents have copied this pattern. **What frustrated me:** - It felt slow to initialize. VS Code extensions have overhead, and Cline's first load took longer than I expected. - The agent mode is still rough. It can handle simple tasks well, but complex multi-file edits sometimes produced inconsistent results. - The 2026 security incident (a compromised package that injected OpenClaw into Cline's install) is a reminder to verify your extension sources. **Verdict:** Cline is a strong choice if you live in VS Code and want an agent that understands your editor context. It's not the most capable agent, but it's quite convenient. ## Aider: The terminal pair programmer Aider positions itself as "AI pair programming in your terminal." It's Python-based, supports many LLM providers, and tracks changes in Git from the start. **What worked:** - Git-native workflow. Every change Aider makes is tracked in your repository with clear commit messages. This is valuable for audit trails and collaboration. - Model flexibility. Aider supports OpenAI, Anthropic, Google, OpenRouter, and local models via Ollama. If you have API credits with multiple providers, Aider lets you use them. - Simple interface. The terminal UI is clean and focused. No config files to wrestle with. **What frustrated me:** - Multi-file edits were inconsistent. Aider struggled to coordinate changes across files that depended on each other. It would edit one file correctly, then fail to update a dependent file. - Slower commit cadence. Aider's last repo push was May 22, 2026 — significantly slower than OpenCode and Cline, which push daily. For an open-source project, this is a yellow flag. - The 46k star count is respectable but doesn't match the momentum of OpenCode or Claude Code. **Verdict:** Aider is a solid choice if you want Git-native workflows and model flexibility. It's a reliable tool, but the multi-file coordination issues held it back in my test. ## Continue: The IDE extension evolving into an agent Continue started as a code completion extension and has evolved into a full agent with "Agent Mode" that can plan and execute multi-step tasks. **What worked:** - IDE familiarity. If you already use Continue for completions, upgrading to Agent Mode is seamless. - Multi-IDE support. VS Code and JetBrains out of the box. - The agent mode is promising. It can handle simple multi-step tasks and is clearly improving with each release. **What frustrated me:** - Agent Mode is still rough around the edges. It worked for simple tasks but stumbled on the more complex parts of my project. - The 35k star count reflects a younger project. Continue is growing but hasn't yet reached the maturity of OpenCode or Cline. - Configuration can be tedious. Setting up custom models and workflows requires more upfront work than OpenCode or Claude Code. **Verdict:** Continue is worth watching. It's not the most capable agent today, but the trajectory is promising. If you're already using it for completions, try Agent Mode on a small task. ## Tabby: The self-hosted option Tabby is a self-hosted AI coding assistant built in Rust. It's designed for teams that want to keep their code private and control their own infrastructure. **What worked:** - Self-hosting. Tabby runs on your own servers, which matters for teams with compliance requirements. - Rust performance. The backend is fast and resource-efficient. - IDE integrations. Tabby works with VS Code, JetBrains, and Neovim. **What frustrated me:** - Setup complexity. Tabby requires more infrastructure than the other agents. You need to deploy a server, configure models, and manage updates. - It's not an agent in the same sense. Tabby is more of a code completion and chat tool than a multi-step coding agent. - The 33k star count reflects a niche audience. Self-hosted tools always have smaller communities than SaaS products. **Verdict:** Tabby is an option if you need self-hosting for compliance reasons. For everyone else, the setup overhead isn't worth it. ## What I learned **1. Speed vs. depth is a real trade-off.** OpenCode is faster because it's lighter. Claude Code is slower because it thinks more. Neither is "better" — they serve different workflows. **2. IDE integration matters more than I expected.** Cline and Continue felt more "present" in my workflow because they lived in my editor. Terminal agents required constant context-switching. **3. Multi-file coordination is the hard problem.** Every agent struggled with this to some degree. It's the difference between "writing a function" and "updating three files that depend on each other." **4. The star count gap is real.** OpenCode at 198k is not a fluke. It's the most-starred AI coding agent in GitHub history, and the gap reflects genuine developer preference for terminal-first, lightweight agents. **5. Security matters.** The Cline injection incident (March 2026) and the Claude Code leak (August 2026) are reminders that coding agents have broad filesystem access. Verify your sources, review commit messages, and don't trust agents with sensitive code without supervision. ## How to pick one in 2026 - **You want speed and terminal-native workflow:** OpenCode (198,000 ★). It's among the fastest, most active, and most popular. - **You want deep reasoning and Anthropic models:** Claude Code (115,000 ★). It's among the most thoughtful agents, but model-locked. - **You live in VS Code and want convenience:** Cline (63,000 ★). The IDE integration is quite unmatched. - **You need Git-native workflows and model flexibility:** Aider (46,000 ★). The commit tracking is valuable, but multi-file coordination needs work. - **You're already using Continue for completions:** Try Agent Mode (35,000 ★). It's improving fast. - **You need self-hosting for compliance:** Tabby (33,000 ★). The only real option in this category. ## The honest part Star counts don't tell the whole story. OpenCode's 198k reflects enthusiasm, but enthusiasm doesn't guarantee your project will succeed. Claude Code's 115k is backed by Anthropic's engineering depth, but it's model-locked. Cline's 63k comes with IDE convenience, but the agent mode is still maturing. The 64% of developers who are "almost right" about AI output (Stack Overflow 2026) aren't failing because the tools are bad. They're failing because they're using the wrong tool for the task. OpenCode is fast but occasionally over-commits. Claude Code is deep but slow. Cline is convenient but rough around the edges. My advice: pick one agent that matches your primary workflow, use it for a real project, and upgrade when you hit its limits. Don't try to use all six. The market is moving too fast — by the time you finish testing, the ranking will change again. A practical tip: start with OpenCode if you want speed, or Claude Code if you want depth. Both are free to try, and both will tell you within 30 minutes whether they fit your workflow. ## FAQ **Are the star counts verified?** Yes, GitHub web verification on 2026-08-19: anomalyco/opencode 198,000 ★ (MIT), anthropics-claude/claude-code 115,000 ★ (proprietary), cline/cline 63,000 ★ (Apache-2.0), Aider-AI/aider 46,000 ★ (Apache-2.0), continuedev/continue 35,000 ★ (Apache-2.0), TabbyML/tabby 33,000 ★ (Apache-2.0). Numbers change daily; check the repos for current values. **Which agent supports the most LLM providers?** Aider and OpenCode both support multiple providers (OpenAI, Anthropic, Google, OpenRouter, local models). Claude Code is Anthropic-only. Cline and Continue depend on the model you configure. **Is OpenCode really better than Claude Code?** Not necessarily. OpenCode is faster and more popular, but Claude Code is deeper and more reliable on complex tasks. The right agent depends on your workflow. **What about Cursor and Windsurf?** They're not open-source and don't have GitHub repositories, so I couldn't verify star counts or licenses. They're commercial products with proprietary models, which puts them in a different category than the agents I tested. **How often should I re-test?** Every 3-6 months. The AI coding agent market moves fast — new features, model updates, and security incidents change the landscape regularly. **Did I mention the Cline security incident?** Yes — cline@2.3.0 was compromised in March 2026 and injected OpenClaw into the published package. The maintainers retracted the release, but it's a reminder to verify your extension sources and review commit messages. ## Summary Six AI coding agents, one project, three days. OpenCode won on speed, Claude Code won on depth, and Cline won on convenience. Aider, Continue, and Tabby have strengths but also limitations that held them back in my test. The right choice depends on your workflow, not your star count. Browse the full 461-tool catalog at /tools.