Claude Code vs OpenCode: Which Agentic CLI Fits Your Workflow?

If you’ve been using AI in software engineering for a while, you know the real productivity jump doesn’t come from "chatting about code". It comes from agentic workflows: letting an AI agent read your repo, run commands, change files, and keep context across a multi-step task.

Two CLI tools stand out right now: Claude Code and OpenCode. (Other tools like aider, Cursor, and Continue also play in this space, but these two represent distinct philosophies worth examining.)

This post is a practical comparison: where each tool shines, where it doesn't, and how to decide based on your constraints (model choice, cost, local LLMs, and daily workflow).

Note: This comparison is based on Claude Code v2.1.23 and OpenCode v1.1.37 as of January 2026.

What "Agentic CLI" Actually Means

An agentic CLI is not just an interface to an LLM. It’s a workflow tool that can typically:

• Inspect your repository structure and files
• Propose a plan, then execute it step-by-step
• Run terminal commands (tests, builds, linters, git)
• Edit files and keep track of changes
• Ask clarifying questions when needed
• Maintain context across a longer engineering session

The CLI becomes the "hands", and the model becomes the "brain".

Claude Code

Claude Code is Anthropic's official agentic CLI.

Getting Started

1npm install -g @anthropic-ai/claude-code
2claude

You can authenticate via API key (ANTHROPIC_API_KEY) or use a Claude Pro/Max subscription directly.

Pros

• Newest Claude features land first: when Anthropic releases new capabilities, Claude Code tends to be the first place where they feel "native".
• Strong end-to-end experience with Anthropic models: the tool and the model are designed to work together.
• Source-available: the code is publicly viewable on GitHub, though under Anthropic's commercial terms rather than an open-source license.
• MCP (Model Context Protocol) support: connect to external tools and data sources.
• Hooks system: run custom scripts before/after tool calls for validation or logging.
• Memory: persistent context across sessions via CLAUDE.md files.

Cons

• Full potential is tied to Anthropic models: even if you can wire it up to other agents or workflows, Claude Code is at its best when the underlying model is from Anthropic. If you want a truly provider-agnostic setup, this is a real limitation.
• Cost can add up: API usage is metered. A Claude Max subscription ($100-200/month) offers better economics for heavy users.

Best fit: Teams and individuals who have standardized on Claude (and want the most "first-class" Claude experience).

OpenCode

OpenCode comes from a different philosophy: make the CLI the stable layer, and treat models as interchangeable "engines".

Getting Started

1go install github.com/opencode-ai/opencode@latest
2opencode

Or download pre-built binaries from the releases page. Configuration is done via opencode.json or environment variables.

Pros

• Works with (almost) any AI model: you can choose the provider and model that fits your needs (cost, speed, privacy, reasoning). Supports OpenAI, Anthropic API, Azure, Google, Mistral, Groq, and more.
• Switch models mid-task: a very practical workflow is:
  • plan/architecture with one model (e.g., "thinky" reasoning like o1 or Claude)
  • execute/refactor with another model (e.g., fast, code-strong like GPT-4o or Codestral)
  • you can use GitHub Copilot with it
• Open source: easier to audit, extend, and integrate into your engineering culture.
• Great integration with local LLMs: works with Ollama, LM Studio, and any OpenAI-compatible endpoint. If you care about data residency, offline work, or just experimenting with local models, this is a major advantage.
• Cost optimization: mix cheap models for simple tasks with expensive models for complex reasoning.

Cons

• No direct Anthropic subscription support: OpenCode requires API access for Claude models. It cannot use your Claude Pro/Max subscription directly. Unlike Claude Code which has official subscription integration, third-party tools accessing Claude's web interface risk being blocked or rate-limited (Anthropic's terms prohibit automated access to consumer products). If your budget depends on subscription-based access rather than API billing, this is a blocker. However, in my personal experience "Claude Pro/Max" works from time to time. Maybe there is a bit of "cat and mouse" game going on here?
• Configuration complexity: more setup required to configure multiple providers and switch between them.

Best fit: Engineers and teams who want model flexibility, local LLM support, and an open tooling ecosystem—especially if they already operate with API-based model access.

Quick Comparison Table

How I’d Choose (Practical Scenarios)

1) "We want the best Claude experience, period."

Pick Claude Code.

If your workflow, prompts, and trust are centered on Claude models, Claude Code is the most direct path with the least friction.

2) "We want the best model for each step."

Pick OpenCode.

This is where OpenCode feels like a power tool: plan with one model, execute with another, and optimize for speed/cost/quality per task phase.

3) "We want local LLMs for privacy or cost control."

Pick OpenCode.

If local models are part of your strategy (even if only for certain tasks), OpenCode is simply built for that reality.

4) "We’re on Anthropic Pro/Max and don’t want API usage."

Lean Claude Code.

If subscription-based access is your default and you don’t want to manage API keys/billing, OpenCode can be frustrating here.

A Concrete Example: Fixing a Failing Test

Here's how a typical task looks in each tool:

Claude Code:

1$ claude
2> The tests in auth.test.js are failing. Fix them.
3
4Claude will:
51. Read the test file and related source files
62. Run the tests to see the failure
73. Propose and apply fixes
84. Re-run tests to verify

OpenCode:

1$ opencode
2> /model claude-3-5-sonnet  # or switch to gpt-4o, local llama, etc.
3> The tests in auth.test.js are failing. Fix them.
4
5# Same workflow, but you can switch models mid-session:
6> /model gpt-4o-mini  # cheaper model for simple follow-ups

The core agentic loop is similar—both tools read files, run commands, and iterate. The difference is in model flexibility and the depth of Claude-specific optimizations.

Security Considerations

For teams in regulated environments, consider:

• Data residency: Claude Code sends data to Anthropic's API. OpenCode with local LLMs (Ollama) keeps everything on-premise.
• API key management: Both tools need secure credential handling. Use environment variables or secret managers, never hardcode keys.
• Audit trails: Claude Code's hooks system can log all tool calls. OpenCode supports similar customization.
• Code access: Both tools can read your entire repository. Review permissions and consider using in isolated environments (eg. a virtual machine) for sensitive codebases.

A Useful Mental Model: CLI as the Product, Model as a Dependency

If you treat the model as the product, you’ll naturally prefer the tool that best matches it (Claude Code + Claude).

If you treat the CLI workflow as the product, you’ll prefer the tool that keeps models swappable (OpenCode).

Both are valid—just don’t mix the two philosophies accidentally.

Conclusion

Claude Code is the strongest choice when you want the most direct, first-class experience with Anthropic models and the newest Claude capabilities.

OpenCode is the better choice when you want a flexible, open, model-agnostic CLI—especially if you want to switch models mid-task or integrate local LLMs into your daily engineering workflow.

If you want help introducing agentic workflows into your engineering organization (from tool choice to safe operating practices, prompt patterns, and internal enablement), we at Infralovers are happy to support you—especially if you’re building with AI in regulated or security-conscious environments.

We recently added new courses on Claude Code and OpenCode with a strong focus on Enterprise use.