# Augment Code vs Kilo (Kilo Code)

Augment Code records 326,215 monthly visits with +24.1% month-over-month growth and Freemium, Free Trial, Contact for Pricing pricing. Kilo (Kilo Code) records 168 monthly visits with -92.4% growth and Paid pricing.

| Metric | [Augment Code](https://openaitools.app/tool/augment-code) | [Kilo (Kilo Code)](https://openaitools.app/tool/kilo-ai) |
| :--- | :--- | :--- |
| Website URL | https://www.augmentcode.com | https://kilocode.ai |
| Categories | AI Agent, AI Code Assistant, AI Code Generator, AI Developer Tools | AI Agent, AI Code Assistant, AI Code Generator, Open Source AI Models |
| Pricing Model | Freemium, Free Trial, Contact for Pricing | Paid |
| Monthly Visits | 326,215 | 168 |
| MoM Growth Rate | +24.1% | -92.4% |
| Primary Market | United States | Austria |
| Direct Visits | 137,070 | 70 |
| Review Score | 4.5 | 4.8 |
| Saved Count | 0 | 1 |
| Supported Platforms | Website | Website |

## Augment Code

Augment Code is an AI coding platform aimed at engineering organisations rather than individual autocomplete users. Its foundation is the Context Engine, which builds a structured understanding of an existing repository — dependencies, architecture, conventions — so that AI suggestions and generated changes fit the codebase instead of reading like generic boilerplate. The product works inside common IDEs and also in the terminal via a CLI.

The platform's recent focus is Cosmos, an agent orchestration layer for the software development lifecycle. Instead of a single assistant answering prompts, Cosmos runs connected loops: a ticket becomes a reviewed pull request, every new PR gets a first-pass code review, failed CI runs get diagnosed, Dependabot and Snyk alerts get triaged into prioritised issues, and on-call engineers inherit a completed investigation. Each loop hands its outcome to the next, and quality gates pause work for human review rather than shipping automatically.

Agents can be deployed in managed cloud sandboxes, on your own machines for code that cannot leave the building, or a mix of both. Native triggers cover GitHub, GitLab, Slack, Linear, Jira, schedules and typed webhooks, with integrations for CI systems. There is a free tier for individuals to try the assistant, while team and enterprise adoption is quote-based; the company has announced it is joining Harness to push the autonomous SDLC from idea to production.

**Pricing & Plans:** Freemium with a free tier for individual developers to start, plus paid team plans and enterprise/contact-for-pricing options. Enterprise deployment includes self-hosted and hybrid agent execution; exact seat and usage pricing is quoted by sales.

- **Context Engine codebase understanding:** Indexes architecture, dependencies and conventions across large repositories so generated code and reviews match how your team actually writes software.
- **Cosmos agent orchestration:** Runs connected SDLC loops — code review, ticket-to-PR, incident triage, dependency upgrades and security remediation — where each agent hands its result to the next.
- **Human-in-the-loop quality gates:** Work pauses at defined checkpoints so engineers approve plans and consequential actions instead of letting agents ship unreviewed changes.
- **Deploy anywhere:** Execute agents in managed cloud sandboxes, on local machines and dev VMs for sensitive code, or in your own AWS and GCP environments.
- **Expert registry and shared memory:** Choose from shipped agents, fork them, or build your own; corrections and shared knowledge improve future runs for the whole team.

**Strengths:** Deep codebase context means suggestions fit existing architecture and conventions; Loops connect across the SDLC instead of solving one isolated task; Quality gates keep humans in control of consequential changes; Flexible deployment including local and self-hosted execution for sensitive code

**Limitations:** Enterprise pricing is quote-based, which makes budgeting harder before a trial; The full value depends on wiring up integrations and triggers across your toolchain; Small teams and solo developers may find the orchestration layer heavier than needed

[Profile (Markdown)](https://openaitools.app/tool/augment-code.md)

## Kilo (Kilo Code)

Kilo Code is an open-source AI coding assistant and agent platform built around the idea that developers should not be locked into one model or one editor. The same MIT-licensed agent is available as a VS Code extension, a JetBrains plugin, a command-line tool, cloud agents and a desktop app, so work can start in the IDE and be handed off to the CLI or cloud without changing tools.

Rather than a single general-purpose assistant, Kilo ships with specialized agents: a Code agent for writing and refactoring, a Plan agent for structuring complex features, a Debug agent for tracing errors, and review workflows for teams. An Auto Model router picks between Efficient, Frontier and Free model strategies so users can balance cost and capability per task.

The platform emphasizes transparency and pricing alignment: the source code is inspectable, prompt and context windows are visible, and the model gateway claims zero markup on inference with support for bringing your own keys or running local models.

**Pricing & Plans:** Free to start with no credit card required, built around 500+ models at zero markup. Users can bring their own API keys or run local models; paid usage and enterprise plans exist, with pricing listed on the site's pricing page.

- **Specialized agents:** Code, Plan, Debug and review agents let you switch context without switching tools, covering writing, planning and troubleshooting.
- **Every coding surface:** The same open-source agent works in VS Code, JetBrains IDEs, the CLI, cloud agents and a desktop app.
- **500+ models, zero markup:** A model gateway routes to frontier, open-weight or free models, supports bringing your own keys and allows running local models.
- **Auto Model routing:** Choose Efficient, Frontier or Free strategies and let Kilo pick the right model for the budget and task at hand.
- **Open source and auditable:** MIT-licensed source lets teams inspect prompts, context windows and model decisions, and even fork or self-host.

**Strengths:** Fully open-source (MIT) agent that can be inspected, forked and self-hosted; Works across VS Code, JetBrains, CLI, cloud and desktop; 500+ models accessible with claimed zero inference markup; Bring-your-own-keys and local model support for privacy

**Limitations:** Broad platform surface can be overwhelming for beginners; Best value depends on configuring model routing and keys yourself; Enterprise and higher-usage tiers move to paid pricing

[Profile (Markdown)](https://openaitools.app/tool/kilo-ai.md)

## Frequently Asked Questions

### How do Augment Code and Kilo (Kilo Code) compare in monthly traffic?

Augment Code has 326,215 monthly visits, while Kilo (Kilo Code) has 168. Traffic estimates describe audience size, not product quality.

### How do their growth rates compare?

Augment Code has a month-over-month growth rate of +24.1%; Kilo (Kilo Code) has -92.4%.

### How does pricing compare?

Augment Code: Freemium, Free Trial, Contact for Pricing. Freemium with a free tier for individual developers to start, plus paid team plans and enterprise/contact-for-pricing options. Enterprise deployment includes self-hosted and hybrid agent execution; exact seat and usage pricing is quoted by sales. Kilo (Kilo Code): Paid. Free to start with no credit card required, built around 500+ models at zero markup. Users can bring their own API keys or run local models; paid usage and enterprise plans exist, with pricing listed on the site's pricing page.

## Alternatives

| # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) |
| :--- | :--- | :--- | :--- | :--- | :--- | :--- |
| 1 | [DeepSeek](https://openaitools.app/tool/deepseek) | 372,761,591 | +4.3% | Freemium | High-efficiency open-weight and hosted reasoning AI powered by DeepSeek-V4 and R1 at ultra-low token costs. | [.md](https://openaitools.app/tool/deepseek.md) |
| 2 | [Cursor](https://openaitools.app/tool/cursor) | 23,297,751 | +8.4% | Freemium | The AI coding agent for building ambitious software | [.md](https://openaitools.app/tool/cursor.md) |
| 3 | [Google Antigravity](https://openaitools.app/tool/google-antigravity) | 16,054,109 | +8.1% | Freemium | Google's agent-first development platform for building and shipping software with AI agents | [.md](https://openaitools.app/tool/google-antigravity.md) |
| 4 | [Replit](https://openaitools.app/tool/replit) | 10,016,437 | -7.7% | Freemium, Paid | Describe your idea and Replit builds a working app in minutes | [.md](https://openaitools.app/tool/replit.md) |
| 5 | [Cursor](https://openaitools.app/tool/cursor-sh) | 4,790,129 | +6.5% | Freemium | Integrates directly into VS Code as a daily coding editor, but lacks enterprise-wide multi-agent SDLC orchestration. | [.md](https://openaitools.app/tool/cursor-sh.md) |
| 6 | [Kiro](https://openaitools.app/tool/kiro) | 3,330,476 | +4.6% | Freemium | A spec-driven AI IDE and agent platform that plans, builds, reviews, and verifies real engineering work. | [.md](https://openaitools.app/tool/kiro.md) |
| 7 | [Devin](https://openaitools.app/tool/devin) | 2,549,346 | +1% | Paid | Operates as a fully autonomous software engineer tackling complex tickets independently, whereas Augment focuses on developer-in-the-loop workflows. | [.md](https://openaitools.app/tool/devin.md) |
| 8 | [Command Code](https://openaitools.app/tool/command-code) | 2,358,177 | -12.1% | Freemium, Contact for Pricing | The coding agent that learns your coding taste | [.md](https://openaitools.app/tool/command-code.md) |
| 9 | [Orca](https://openaitools.app/tool/orca) | 1,025,891 | +1% | Free, Open Source, Enterprise on request | Run many coding agents in parallel, each in its own worktree | [.md](https://openaitools.app/tool/orca.md) |
| 10 | [KaneAI](https://openaitools.app/tool/kaneai) | 901,340 | +13.2% | Freemium, Paid, Contact for Pricing | GenAI-native end-to-end QA agent that plans, writes and heals tests in plain language | [.md](https://openaitools.app/tool/kaneai.md) |

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Source: https://openaitools.app/compare/augment-code-vs-kilo-ai

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