Kilo Code: The New Open-Source AI Coding Agent for VS Code

In the fast-evolving world of AI-assisted coding, Kilo Code emerges as a compelling open-source extension for Visual Studio Code that promises far more than simple code completion. Described by its creators as a “superset” of existing tools like Roo Code and Cline, Kilo Code aims to combine planning, generation, refactoring, debugging, and orchestration all within your editor. If it delivers, it could become your ongoing development co-pilot without vendor lock-in or opaque pricing.

This article explores Kilo Code end-to-end: what it offers, how it compares to alternatives, technical architecture, pricing, real-world adoption, strengths and challenges, and where it’s headed.

What is the kilo code?

Kilo Code is an open-source AI coding agent built as a VS Code extension (also usable via the OpenVSX registry). It integrates with various large language models (LLMs) and provides features like:

• Generating code from natural language prompts
• Refactoring, debugging, and analyzing existing code
• Automating repetitive development tasks
• Running terminal commands, interacting with web, or invoking external tools
• Supporting multiple “modes” (e.g., Architect, Code, Debug) to shift the AI’s behavior

Like its predecessors Roo Code and Cline, Kilo Code is intended to act as your developer assistant—but with added flexibility, extensibility, and control. Because it’s open source under Apache-2.0, it allows transparency and community contributions.

One key promise: you pay only the direct model token costs, with no markups, and you can supply your own API keys or run local models for privacy or cost control.

Kilo Code vs. Roo Code vs. Cursor vs. Cline

To understand where Kilo Code stands, it’s helpful to compare it with existing AI coding assistants:

Roo Code & Cline

Kilo Code explicitly states that it “frequently merges features from open-source projects like Roo Code and Cline” and positions itself as a superset of both. Roo Code was known for its dual Plan/Act modes (plan first, then execute) and its integration with OpenRouter for model flexibility. Cline similarly offered code generation features in VS Code. Kilo Code aims to build and unify these capabilities while adding orchestrator and custom modes, a marketplace for model/context, and richer tool integrations.

Cursor

Cursor (a commercial competitor) offers AI-powered code completion and agentic features. Unlike Cursor, Kilo Code is open source and claims no commission markup on model usage. The ability to use your own API keys or local models gives Kilo Code greater flexibility in cost and privacy.

Other Tools (e.g. GitHub Copilot)

GitHub Copilot is widely used, but is proprietary and comes with subscription fees and usage limits. Kilo Code’s open nature and transparency aim to be distinguishing advantages. Also, Kilo Code touts orchestrator and mode-based design, which go beyond simple line completion.

In community discussion, Kilo Code is praised for combining features you’d need multiple extensions to get in earlier setups.

Thus, Kilo Code tries to bridge the gap: combining depth and flexibility of open tools with modern agent-style capabilities.

Key Features & Capabilities

Below is a detailed breakdown of Kilo Code’s core features and how they enhance the development workflow.

Multi-Mode Operation

Kilo Code supports several modes, which are essentially behavior profiles steering the AI logic:

• Code Mode: The standard mode:generate, complete, or transform code based on instructions.
• Architect Mode: For planning, system design, high-level technical decisions. (e.g. choose data models, API structure)
• Debug Mode: Diagnose bugs, suggest fixes and patches.
• Ask Mode: Fetch explanations, context or info about existing code without modifying files.
• Custom Modes: You may configure specialized modes (security, performance, etc.).
• Orchestrator Mode: A standout feature that breaks a complex task into subtasks across multiple modes (planner, implementer, debugger) and coordinates them. This gives Kilo Code agentic project-level ambition.

This mode-based design helps keep context and intent clearer, gives the AI more structure, and reduces hallucinations.

Integrated Tools & Actions

Beyond just generating code, Kilo Code comes with integrated tooling to support deeper workflows:

• File read/write operations: It can open, edit, save project files.
• Terminal commands: It can execute shell or CLI commands from within the agent context.
• Browser automation: For interacting with web APIs or scraping tasks.
• Context-aware codebase searching: It can reference your existing project context (imports, file structure) to generate more consistent code.
• Self-checking / error recovery: The extension claims to “check its own work” and auto-recover from errors.

These toolset integrations make Kilo Code closer to a full coding agent rather than a mere autocomplete plugin.

Model Flexibility & Local Use

One major differentiator: Kilo Code supports 400+ hosted models, BYOK (Bring Your Own Key), or local models.

Running models locally (e.g. via Ollama or LM Studio) is especially attractive for privacy, offline use, or lowering cloud API costs.

The architecture uses a Model Context Protocol (MCP) that allows integration or extension with external tools or APIs. There is even a marketplace for MCP servers to connect services like Figma, Git, or domain-specific tooling.

Anti-Hallucination, Versioning, and Reliability

Kilo Code emphasizes safety by trying to anchor outputs in context, read documentation, and run verification steps. It also features versioned releases and updates frequently.

Community feedback notes that as a newer tool, there remain bugs or UI quirks, but the project is active in fixing them.

How to Install & Start Using Kilo Code

Here’s a step-by-step guide to set up Kilo Code and try your first task.

Installation & Setup

• Prerequisite: Have Visual Studio Code (or a compatible VS Code-based editor) installed.
• Install extension: Go to Extensions tab and search for “Kilo Code” or install via VS Code Marketplace or OpenVSX Registry.
• Reload / enable: After installation, reload VS Code if prompted.
• Open Kilo panel: Click the Kilo Code icon in the sidebar to open the chat/agent panel.
• Authenticate / configure: Use your account (often via Google) to get free starter credits. Optionally configure your own API keys or local model settings.
• Start a request: Use the chat interface, select mode (e.g. Code mode), and ask a natural-language request.

For example: “Create a Python function sum_list that sums a list of integers and handles empty lists.” It will produce the code and you can iterate.

You can also install via Cursor Marketplace (if you use Cursor) or manually via .vsix file.

Using Local Models (Offline / Privacy Mode)

Kilo Code supports local models running via tools such as Ollama or LM Studio. This enables:

• Full offline usage without cloud API calls
• Privacy of your code/data
• Potential cost savings by avoiding token billing

However, performance depends on your hardware and model size.

Pricing, Credits & Cost Structure

One of Kilo Code’s most publicized propositions is its transparent, “no markup” pricing ethos.

Free Base & Credits

The core extension is open source and free. New users generally receive free credits (e.g. $20) to try models like Claude, Gemini, or GPT variants.

The marketplace listing states: “Get $20 in bonus credits when you top-up for the first time.

Pay-As-You-Go for LLM Costs

Kilo Code claims it does not add a commission on top of model provider costs. You pay the raw token pricing from the underlying provider.

You may also use your own API keys or local models, meaning you control model usage costs fully.

Promotional / Frontier Model Access (Grok, etc.)

In late August 2025, Kilo Code announced “Grok Code Fast”, an exclusive model made available via partnership with xAI. Users got free, unlimited access (no rate limits) for a limited time.

Grok Code Fast supports a large context window (262k tokens) and strong tool calling proficiency. This acted as a free incentive draw to Kilo’s user base.

Enterprise Plan & Future Monetization

While not yet fully released, Kilo Code plans to offer enterprise features such as audit logs, role-based access control (RBAC), and managed deployments. The core extension itself stays open source; the monetization would come from premium agent infrastructure and enterprise management layers.

Real-World Use & Adoption

Kilo Code is relatively new, but already showing promising traction and use cases.

• GitHub Stars: Kilo Code’s GitHub repository has surpassed 10,000 stars, reflecting strong community interest and engagement.
• Extension Installs: The Kilo Code extension has been installed over 250,000 times, indicating significant adoption among developers.
• Community Discussion: Developers highlight the utility of modes like Architect, Ask, Debug, and Orchestrator, which facilitate structured workflows and integration with top AI models.
• Cost-Efficient Projects: Users have reported building practical tools, such as a GitHub issue processor using Kilo Code and Gemini 2.5, with token usage costs as low as $0.41
• Grok Code Fast Launch: The promotional release of Grok Code Fast 1 significantly boosted user engagement, with Kilo Code processing 169 billion tokens during the four-day launch window, surpassing the combined usage of the top 20 competing applications. 

These early signals suggest real interest among developers, especially those prioritizing control, flexibility, and cost transparency.

Strengths, Challenges & Risks

Strengths

1. Open source & transparency: The Apache-2.0 license and visibility into internals build trust and allow community contributions.
   
2. Flexibility in models: Ability to use many hosted models, BYOK, or local models gives control over cost and data.
   
3. Rich mode architecture: Modes like architect, orchestrator, debug help structure AI intent.
   
4. Tool integration: File operations, terminal commands, browser automation, all from within an agent context.
   
5. Zero-commission pricing: No markup on underlying model costs is rare in this market.
   
6. Active development & community: Frequent updates and responsiveness to feedback.
   

Challenges & Risks

1. Polish and stability: As a younger project, some UI or feature rough edges may remain. Community feedback notes occasional quirks.
   
2. VS Code dependency: It stays primarily within the VS Code ecosystem. Developers who prefer JetBrains or other IDEs may feel left out.
   
3. Performance of large contexts or local models: Some models may perform slowly or have hardware constraints.
   
4. Model risk & hallucinations: Regardless of infrastructure, AI-generated code can misbehave. Safe fallback and verification is essential.
   
5. Enterprise adoption hurdles: Until enterprise features (RBAC, auditability, compliance) are mature, corporate adoption may remain cautious.
   
6. Competition from well-funded incumbents: Giants like GitHub Copilot, Tabnine, and others have large user bases and deep integrations, Kilo must keep innovating.

“Kilo Code vs Other Tools: Quick Comparisons

Here’s a side-by-side look at how Kilo Code compares with some specific alternatives:

Comparison	Advantage for Kilo Code	Possible Weakness
Kilo Code vs Roo Code / Cline	Combines features of both + added orchestration, mode flexibility, model variety	Larger surface area and complexity may lead to integration challenges
Kilo Code vs Cursor	Open source, cheaper transparent usage, model flexibility	Cursor may have more polished UX or integration in some IDEs
Kilo Code vs Tabnine / Copilot	Full control, BYOK, local model support, no markup	Those may have more stable enterprise support or integrations
Kilo Code vs cursor / cline in VS Code	Supports installing from Cursor marketplace and Open VSX registry for broad compatibility	Might lag in smoother UI or feature polish in those marketplaces

In community comparisons, users often highlight Kilo’s depth of features and its consolidation of many tools into a single extension.

Tips & suitable Practices for Power Users

• Start small, modular: Use small prompts, one mode at a time, to avoid context overload.
  
• Use local models for sensitive code: If confidentiality matters, run models locally to avoid sending code to cloud APIs.
  
• Leverage modes intentionally: Switch to Architect or Orchestrator for planning tasks vs code generation.
  
• Use MCP for tool integration: Use or build MCP servers to integrate domain APIs, code metrics, or internal dev tools.
  
• Version control agent-generated code: Always review and track changes in version control.
  
• Track token usage: Monitor which model calls are costly and optimize.
  
• Stay updated: Watch GitHub and Kilo’s Discord for weekly builds and fixes.

Future Outlook & Roadmap

Kilo Code is moving quickly, with roadmap hints in public communications:

• Full enterprise features (audit logs, RBAC, managed hosting) are planned.
  
• Support for JetBrains or other IDEs is a requested community feature.
  
• Parallel agent or memory bank models: hints in community and documentation suggest richer multi-step agent chains or persistent memory.
  
• Expanding model ecosystem (e.g. new frontier models) — the Grok Code Fast partnership is one early example.
  
• Increased stability and polish: as the user base grows, more QA, UI improvements, tooling, and documentation will evolve.

Conclusion

Kilo Code is among the most ambitious and promising open-source AI coding assistants today. It blends features from Roo Code and Cline, introduces multi-mode agent orchestration, supports local and hosted models, and embraces transparency in pricing, qualities rare among competitors.

If you’re a developer or team looking for AI assistance that doesn’t lock you into a vendor or opaque pricing, Kilo Code is worth testing. Start with small tasks, explore its modes, try local models, and see how well its orchestration and tool integrations fit your workflow.

As it matures, especially with enterprise features, the real test will be stability, scalability, and ecosystem growth. But already in mid-2025, Kilo Code is shaping up to be a genuine challenger in the AI coding assistant space.

FAQs

What is Kilo Code’s primary differentiation?

It’s open source, gives you control over model usage and costs, supports local models, and integrates modes + orchestration meaningfully.

Is Kilo Code free?

The extension is free. You pay only for model usage (if not using local or free models). You also receive starter credits for premium models.

Which AI models does Kilo Code support?

It supports many hosted models (400+), including Gemini, Claude, GPT, etc. It also allows local model use via Ollama or LM Studio.

How does orchestration (Orchestrator mode) work?

It decomposes a large task into subtasks, assigns specialized mode agents to each, and coordinates their execution, bridging planning and execution.

Can Kilo Code run offline?

Yes, using local models like Ollama or LM Studio. But performance depends on your hardware.

Is there a Kilo Code “price list” for model usage?

The tool uses raw provider token pricing (no markup). During promotions (e.g. Grok Code Fast), some usage may be free.

Which file types / languages does Kilo Code support?

The docs cover many mainstream programming languages and file types. The extension is generic; usage depends on model capabilities.