Tools
CLI Coding Agents Compared
Claude Code, Mistral Vibe, Gemini CLI and OpenAI Codex CLI — honest comparison with feature matrix, pricing, GDPR assessment and hands-on experience.
CLI Coding Agents are terminal-based AI assistants that work directly in your file system: reading, writing, and editing code, executing shell commands, and performing git operations. Unlike chat interfaces like ChatGPT or Claude.ai, they work directly in your project context and can autonomously complete complex multi-step tasks.
This comparison is based on our daily hands-on experience. We use Claude Code as our primary tool and have systematically tested the alternatives. The assessment is honest: where others are better, we say so.
The 4 Agents in Detail
1. Claude Code (Anthropic)
CLI agent with the strongest reasoning
Model
Claude Opus 4.6 / Sonnet 4.6
Open Source
CLI is open source, model is proprietary
Local Execution
No — Anthropic API only
Pricing
Anthropic API: $3–15 / 1M Tokens
Protocol
MCP (Model Context Protocol)
Context Window
200K–1M Tokens
Tools
Strengths
- Best reasoning of all tested agents
- Subagents for parallel task execution
- MCP integration (Notion, Playwright, Docker, etc.)
- Hooks for automated quality assurance
- Skills and plugin system
- Git worktrees for isolated branches
- Plan mode for complex tasks
Weaknesses
- Not locally executable — all data goes to Anthropic API
- Expensive at high volume ($150–500/month with intensive use)
- Dependency on Anthropic as sole provider
- No free tier for the API
Key Features
Subagents can work in parallel and split complex tasks. Hooks enable automatic rules (e.g. "never delete without confirmation"). CLAUDE.md files define project-specific behavior. MCP servers extend capabilities with external tools (databases, browsers, APIs).
2. Mistral Vibe (Mistral AI)
The only agent that runs fully locally
Model
Devstral 2 (123B) / Devstral Small 2 (24B)
Open Source
Yes — MIT / Apache 2.0
Local Execution
Yes — Devstral Small 2 (24B) runs on RTX 3090
Pricing
Le Chat Plans or self-hosted free
Protocol
ACP (Agent Communication Protocol)
Context Window
~128K Tokens
Tools
Strengths
- Fully open source (MIT / Apache 2.0)
- Local execution — no data leaves the company
- 24B model runs on consumer GPU (RTX 3090)
- GDPR-compliant without additional measures
- Own protocol (ACP) for agent communication
Weaknesses
- Less tool variety than Claude Code (4 vs. 10+ tools)
- Younger ecosystem — fewer plugins and integrations
- Reasoning quality below Claude Opus 4.6
- No MCP support (own ACP protocol)
- Turn limit on complex tasks (5 turns in our test)
Tested Version
v2.5.0
3. Gemini CLI (Google)
Largest context window and free tier
Model
Gemini 2.5 Pro / Flash
Open Source
CLI is open source, model is proprietary
Local Execution
No — Google AI API only
Pricing
Google AI API (free tier available)
Protocol
Standard API
Context Window
1M+ Tokens
Strengths
- 1M+ context window — largest of all tested agents
- Free tier for getting started
- Multimodal capabilities (images, code, text)
- 98k+ GitHub stars — large community
Weaknesses
- Less code-focused than Claude Code
- Dependency on Google infrastructure
- Not locally executable
- No MCP support
- No subagent system
4. OpenAI Codex CLI
OpenAI ecosystem with GPT-4o and o3
Model
GPT-4o / o3
Open Source
CLI is open source, model is proprietary
Local Execution
No — OpenAI API only
Pricing
OpenAI API: $5–15 / 1M Tokens
Protocol
Standard API
Context Window
128K Tokens
Strengths
- Broad OpenAI ecosystem and community
- GPT-4o quality for coding tasks
- Good integration with existing OpenAI workflows
Weaknesses
- Not locally executable
- Dependency on OpenAI
- Expensive at high volume
- No MCP support
- No subagent system
- Smallest context window (128K)
Feature Matrix
| Feature | Claude Code | Mistral Vibe | Gemini CLI | Codex CLI |
|---|---|---|---|---|
| Local Execution | No | Yes (24B) | No | No |
| Open Source Model | No | Yes (MIT/Apache) | No | No |
| Subagents | Yes | No | No | No |
| MCP Support | Yes | No (ACP) | No | No |
| Plugin System | Yes | No | No | No |
| Context Window | 200K–1M | ~128K | 1M+ | 128K |
| Hooks / Rules | Yes | No | No | No |
| Git Worktrees | Yes | No | No | No |
| GDPR-local | No | Yes | No | No |
| Free Tier | No | Local = free | Yes | No |
Cost Comparison (estimated at 1,000 requests/day)
| Agent | Cost / Month | Local Possible | Note |
|---|---|---|---|
| Claude Code | ~$150–500 | No | Opus more expensive, Sonnet cheaper |
| Mistral Vibe (API) | ~$50–150 | — | Via Le Chat or Mistral API |
| Mistral Vibe (Local) | ~$50 (electricity) | Yes | One-time hardware costs not included |
| Gemini CLI | ~$0–100 | No | Free tier for low usage |
| Codex CLI | ~$150–500 | No | GPT-4o and o3 similarly priced |
Hands-on Test: Mistral Vibe v2.5.0
We tested Mistral Vibe v2.5.0 on this wiki to get a direct comparison with our primary tool Claude Code.
Simple task (counting files)
Completed correctly and quickly. Shell tool works reliably.
Complex task (code analysis)
Hit turn limit at 5 turns. The agent could not fully complete the task. Claude Code completed the same task in a single session.
Conclusion: Mistral Vibe works reliably for simple to medium tasks. For complex, multi-step workflows with many file interactions, Claude Code is significantly superior — both in reasoning quality and tool variety, with no turn limit.
Who Should Use What?
Enterprise with Budget
Claude Code
Best reasoning quality, subagents for parallel tasks, MCP integration for tool connectivity. When quality matters more than cost.
GDPR-critical / Self-Hosted
Mistral Vibe (local)
Only option when no data may leave the company. Devstral Small 2 (24B) on RTX 3090 is sufficient. Open source, MIT license.
Budget-conscious
Gemini CLI
Free tier to try it out. 1M context window for large codebases. Good for getting started without financial commitment.
OpenAI Ecosystem
Codex CLI
Seamless integration if already using OpenAI APIs and GPT-4o. Familiar ecosystem, proven model quality.
Our Recommendation
Honest Assessment
- We are not neutral: This article is written with Claude Code. We use it daily and know it best. The strengths are first-hand, as are the weaknesses.
- No agent is perfect: Claude Code is expensive and not local. Mistral Vibe is less capable on complex tasks. Gemini CLI is less code-focused. Codex CLI has the smallest context window.
- The market moves fast: This comparison reflects the state of March 2026. All four providers release regular updates.
Protocol Comparison: MCP vs. ACP
| Aspect | MCP (Model Context Protocol) | ACP (Agent Communication Protocol) |
|---|---|---|
| Developer | Anthropic | Mistral AI |
| Focus | Tool integration (filesystem, APIs, DBs) | Agent-to-agent communication |
| Ecosystem | Large (Notion, Playwright, Docker, etc.) | Growing, still young |
| Compatibility | Broad (Claude, Cursor, Windsurf, etc.) | Primarily Mistral Vibe |
| Open Standard | Yes (open specification) | Yes (open specification) |
Sources
- Claude Code Documentation — Official Anthropic documentation
- Claude Code GitHub — Open source CLI repository
- Mistral Vibe Documentation — Official Mistral AI documentation
- Devstral Small 2 on Hugging Face — 24B model for local execution
- Gemini CLI GitHub — Google Gemini CLI (98k+ Stars)
- OpenAI Codex CLI GitHub — OpenAI Codex CLI repository
- Model Context Protocol (MCP) — Official MCP specification
- Agent Communication Protocol (ACP) — Official ACP specification
Related articles: AI Tools Database · What is an LLM?
For implementation support, find resources at ai-engineering.at.
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