Best AI Coding CLI Tools in 2026: 7 Terminal Agents Compared

The command line has quietly become the most interesting battleground in AI-assisted development. While IDE integrations get the marketing budgets, a growing class of terminal-native agents can now read your codebase, edit files across repos, run tests, commit changes, and debug failures - all from a single prompt.

I have been testing these tools daily for months, running them against real codebases rather than toy examples. Here is how the seven most important AI coding CLI tools stack up as of February 2026.

Why CLI Over IDE?

Before diving in: why would you want an AI agent in your terminal instead of (or alongside) your IDE?

Composability. CLI tools pipe into existing workflows. You can chain them with git, make, docker, and CI/CD scripts. They do not care which editor you use.

Transparency. You see every command the agent runs, every file it touches, every test it executes. No magic behind a GUI.

Resource efficiency. No Electron overhead. Most of these tools are lightweight processes that connect to remote models.

Automation. Terminal agents can run headlessly in CI, as GitHub Actions, or as cron jobs. Try doing that with an IDE plugin.

The Contenders

Tool	Developer	Open Source	Base Price	Underlying Models
Claude Code	Anthropic	No	$20/mo (Pro)	Claude Opus 4.6, Sonnet 4.5
Gemini CLI	Google	Yes	Free	Gemini 2.5 Pro, Flash
Codex CLI	OpenAI	Yes	$20/mo (Plus)	GPT-5.2-Codex
Aider	Community	Yes (Apache 2.0)	Free (BYOK)	Any (100+ models)
OpenCode	Community	Yes	Free (BYOK)	Any (75+ providers)
Warp	Warp Inc.	No	$20/mo (Build)	OpenAI, Anthropic, Google
Amp	Sourcegraph	No	Free tier (~$10/day)	Claude Opus, GPT-5

Head-to-Head: Features

Feature	Claude Code	Gemini CLI	Codex CLI	Aider	OpenCode	Warp	Amp
Context window	200K (1M with API)	1M	200K	Model-dependent	Model-dependent	Model-dependent	Model-dependent
Auto git commits	Yes	No	Yes	Yes	No	No	Yes
Multi-file editing	Yes	Yes	Yes	Yes	Yes	Yes	Yes
Test execution	Yes	Yes	Yes	Yes (auto-fix)	Yes	Yes	Yes
MCP support	Yes	Yes	Yes	No	Yes	No	Yes
Image/screenshot input	Yes	Yes	Yes	No	No	Yes	Yes
Voice input	No	No	No	Yes	No	No	No
GitHub integration	Yes (@claude)	No	Via ChatGPT	Via git	Yes (@opencode)	No	Yes
Runs locally/offline	No	No	No	Yes (Ollama)	Yes (Ollama)	No	No

Pricing Breakdown

This is where the differences really matter for daily use.

Claude Code

Claude Code requires a Claude subscription or API access. The Pro plan ($20/month) gives you 5x free capacity. For heavier usage, Max plans run $100/month (5x Pro) or $200/month (20x Pro). API users pay per token: $5/$25 per million tokens for Opus 4.6, $3/$15 for Sonnet 4.5. A typical coding session costs $2-8 depending on the task complexity and model choice.

Gemini CLI

The clear winner on price. Sign in with a personal Google account and you get 60 requests per minute, 1,000 requests per day, access to Gemini 2.5 Pro with a 1 million token context window - all free. Paid tiers exist through Google AI Studio or Vertex AI for higher rate limits.

Codex CLI

Included with ChatGPT Plus ($20/month), Pro ($200/month for 6x usage limits), or Team/Enterprise plans. API pricing for the codex model runs $1.50/$6 per million tokens with a 75% prompt caching discount, making it the cheapest per-token option for API users.

Aider

Free and open source. You bring your own API keys and pay the model providers directly. With GPT-4o, typical feature implementations cost $0.01-0.10. Run with DeepSeek or local models via Ollama for near-zero cost.

OpenCode

Same model as Aider: free tool, you pay providers. The January 2026 GitHub partnership means Copilot subscribers can authenticate directly with no additional license needed.

Warp

The Build plan is $20/month and includes 1,500 AI credits. Free users get 75 credits/month after an initial two-month period of 150/month. You can also bring your own API keys and pay providers directly.

Amp

Ad-supported free tier allows up to roughly $10/day in usage. Pay-as-you-go after that with no markup on model costs.

Benchmark Performance

I track multiple benchmarks to evaluate these tools. Here is how the underlying models perform on standardized coding tasks.

Aider Polyglot Benchmark (225 Exercism exercises, 6 languages)

Model	Score
GPT-5 (high reasoning)	88.0%
GPT-5 (medium)	86.7%
o3-pro (high)	84.9%
Gemini 2.5 Pro (32K think)	83.1%
GPT-5 (low)	81.3%
Grok 4 (high)	79.6%
Gemini 2.5 Pro (default)	79.1%

Note: Claude Opus 4.6 and Sonnet 4.5 scores were not available on the Aider leaderboard at time of writing.

SWE-Bench Verified (real-world GitHub issue resolution)

Model/Agent	Score
Claude Opus 4.5	80.9%
Claude Opus 4.6	80.8%
MiniMax M2.5	80.2%
GPT-5.2	80.0%
Gemini 2.5 Pro	63.8%

The SWE-Bench numbers tell a different story from the Aider leaderboard. Claude's Opus models dominate real-world issue resolution, while GPT-5 variants lead on isolated coding exercises. Agent scaffolding matters enormously here - the same model can score 10-20 points higher with a well-designed agent framework around it.

My Testing: Real-World Impressions

I ran each tool through the same set of tasks on a mid-size TypeScript project (~50K lines): refactoring a module, adding a new API endpoint with tests, fixing a tricky async bug, and performing a dependency upgrade.

Claude Code

The most polished end-to-end experience. It maps your entire codebase before making changes, proposes a plan, and executes it with minimal hand-holding. Multi-step tasks that require editing 5-10 files, running tests, and iterating on failures are where Claude Code pulls ahead. The context compaction feature means long sessions do not just crash when you hit the window limit. Downside: cost adds up fast on Opus 4.6 during extended sessions.

Gemini CLI

The 1M token context window is not just a spec-sheet talking point. On large codebases, Gemini CLI can ingest your entire project in one shot, which is a real advantage for cross-cutting refactors. The free tier is absurdly generous for individual developers. The main weakness is autonomy - it tends to need more manual nudging compared to Claude Code, and in my testing a task Claude finished in 1h17m for $4.80 took Gemini fragmented attempts totaling $7.06.

Codex CLI

Lightweight and fast, built in Rust. The three-tier permission system (read-only, auto, full) is well-designed for different trust levels. If you are already paying for ChatGPT, this is essentially free. Weaker on complex multi-file refactors compared to Claude Code but solid for focused tasks.

Aider

The OG of terminal AI coding. 39K+ GitHub stars, 4.1M+ installations, and 15 billion tokens processed per week speak for themselves. The killer feature is model flexibility - swap between Claude, GPT, DeepSeek, Gemini, or local models mid-session. Automatic git commits with descriptive messages and built-in lint/test integration make it the most git-native tool in this list. No MCP support is the main gap.

OpenCode

The fastest-growing entrant. 95K+ GitHub stars and 2.5M monthly developers. LSP integration (language server awareness for Rust, TypeScript, Python, and more) gives the LLM genuine understanding of your code structure, not just raw text. Multi-session support lets you run parallel agents on the same project. The Copilot authentication partnership removes a significant friction point.

Warp

Different category, really. Warp replaces your entire terminal rather than running inside it. The GPU-accelerated Rust terminal with built-in AI, multi-agent orchestration (Oz agents), and code review panels is impressive. But at $20/month with limited credits, it is hard to justify unless you want the full terminal replacement experience.

Amp

Sourcegraph's entry has a unique "Deep mode" with extended reasoning that can run for minutes on complex problems. Sub-agents (Oracle for codebase analysis, Librarian for docs, Painter for image generation) make it feel more like a team than a single tool. The ad-supported free tier offering ~$10/day of usage is generous, though the ads are a trade-off some will not accept.

Decision Matrix

Choose Claude Code if: You want the most capable autonomous agent and are willing to pay for it. Best for complex, multi-file tasks on professional codebases.

Choose Gemini CLI if: You want free, high-quality AI coding assistance. The 1M context window makes it unbeatable for large monorepos.

Choose Codex CLI if: You are already in the OpenAI/ChatGPT ecosystem. The Rust-based CLI is fast and the permission system is well-thought-out.

Choose Aider if: You want maximum model flexibility and the deepest git integration. The open-source community is active and the tool is battle-tested.

Choose OpenCode if: You want an open-source tool with IDE-level language awareness (LSP) in your terminal. The GitHub/Copilot partnership is a nice bonus.

Choose Warp if: You want to replace your terminal entirely with an AI-native environment. The multi-agent orchestration is unique.

Choose Amp if: You need extended autonomous sessions with deep reasoning. The free tier is generous for individual developers.

The Bottom Line

If I had to pick one tool today, it would be Claude Code for professional work and Gemini CLI for personal projects and experimentation. Claude Code's autonomous multi-step execution is ahead of everything else when you throw real engineering tasks at it. But Gemini CLI's free tier with 1M context and 1,000 daily requests is genuinely hard to argue with for individual developers.

The open-source options - particularly Aider and OpenCode - deserve serious consideration if you want model flexibility and vendor independence. Aider's community and track record are hard to beat, while OpenCode's growth trajectory (95K+ stars and growing) and LSP integration hint at where this category is headed.

84% of developers now use AI tools in their workflow. The question is no longer whether to use an AI coding assistant, but which terminal agent fits your stack.

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