Continue vs Kilo Code
Compare Continue and Kilo Code by workflow, pricing, privacy, model support, and best use cases.
Continue
Choose Continue when model control, open-source extensibility, and repository-defined AI checks matter more than a fully managed AI editor experience.
Kilo Code
Choose Kilo Code when openness, model flexibility, BYOK/local options, and cross-surface agent workflows matter more than having one tightly controlled first-party editor experience.
Key Differences
Workflow
Continue is an open-source AI coding agent and IDE extension ecosystem focused on configurable model access, repository-defined AI checks, and team-controlled coding workflows.
Kilo Code positions itself as an open-source, multi-model coding agent that spans IDE extensions, CLI, cloud agents, and team governance.
Pricing
freemium
open-source
Feature Comparison
| Feature | Continue | Kilo Code |
|---|---|---|
| Primary workflow | Continue is an open-source AI coding agent and IDE extension ecosystem focused on configurable model access, repository-defined AI checks, and team-controlled coding workflows. | Kilo Code positions itself as an open-source, multi-model coding agent that spans IDE extensions, CLI, cloud agents, and team governance. |
| Type | extension | extension |
| Editor base | VS Code | VS Code |
| Pricing model | freemium | open-source |
| Starting price | $3 | $0 |
| Free plan | Yes | Yes |
| Open source | Yes | Yes |
| Local models | Yes | Yes |
| BYOK | Yes | Yes |
| Platforms | VS Code, JetBrains IDEs, CLI, GitHub | VS Code, Open VSX-compatible editors, JetBrains IDEs, CLI, Cloud Agents, Slack |
| Models | Anthropic, OpenAI, Azure, Amazon Bedrock, Ollama, Google Gemini, DeepSeek, Mistral, xAI, Vertex AI, Inception, HuggingFace, Groq, Together AI, DeepInfra, OpenRouter, ClawRouter, Tetrate Agent Router Service, Cohere, NVIDIA, Cloudflare, MiniMax, LM Studio, llama.cpp, LlamaStack, llamafile, SambaNova, Watson x, Sagemaker, Nebius | Anthropic Claude, OpenAI GPT, Google Gemini, xAI Grok, MiniMax, Z.ai GLM, DeepSeek, Mistral AI, Moonshot AI Kimi, AWS Bedrock, Ollama, LM Studio, Atomic Chat, OpenRouter, OpenAI-compatible providers |
| Enterprise features | Shared private agents, Team agent controls, Gmail/GitHub SSO on Team, SAML or OIDC SSO on Company, BYOK on Company, Commitment, invoicing, and SLA on Company, GitHub PR check integration, Centralized Mission Control management | Centralized billing, Usage analytics and reporting, AI adoption score, Shared agent modes, Shared BYOK, Team management, Data privacy controls, Model and provider restrictions, Shared Private Gateway BYOK, Audit logs, SSO, OIDC, and SCIM, SLA commitments, Dedicated support channels |
| Best for | Developers who want AI coding assistance inside VS Code without switching to a full AI-native editor., Teams that want AI review rules stored in the repository and enforced as PR status checks., Organizations that need model flexibility across cloud, local, self-hosted, and gateway providers., Developers building custom coding agents with YAML configuration, rules, prompts, models, and tools., Engineering teams experimenting with AI quality gates before adopting larger autonomous coding systems. | Developers who want an open-source AI coding agent inside VS Code or JetBrains., Teams that want BYOK, shared modes, usage analytics, and centralized AI cost controls., Power users who switch between IDE and terminal workflows., Developers comparing Roo Code, Cline, Continue, Cursor, and Claude Code., Privacy-conscious workflows that can run capable local models. |
| Not best for | Users who want a polished all-in-one AI IDE with minimal configuration., Teams that prefer a single vendor-managed model and billing experience., JetBrains-heavy teams that need the IDE plugin to be the primary supported path., Users who do not want token-based billing for hosted model usage., Organizations that are uncomfortable with the current read-only status of the legacy main GitHub repository. | Users who only need lightweight autocomplete with minimal setup., Non-technical users looking for a no-code prompt-to-app builder., Teams that require a single fixed first-party model vendor., Developers without budget or hardware for higher-capability model usage. |
Use Case Winners
Both Continue and Kilo Code have comparable signals here.
Both Continue and Kilo Code have comparable signals here.
Kilo Code lists more team or enterprise controls.
Continue has stronger frontend or web workflow signals.
Continue supports more model/provider options or BYOK-style workflows.
Both Continue and Kilo Code have comparable signals here.
Pricing Comparison
Continue
- Open-source Extension / CLI$0
Apache-2.0 codebase with VS Code extension, CLI, and JetBrains plugin artifacts available from official channels.
- Starter$3 / million tokens
Pay-as-you-go usage for creating and running agents, integrations, and frontier model credits.
- Team$20 / seat/month
Team management, private shared agents, agent controls, Gmail/GitHub SSO, and $10 credits per seat.
- CompanyCustom
Enterprise plan with SAML or OIDC SSO, BYOK, commitments, invoicing, and SLA.
Kilo Code
- Free & Open Source$0 / forever
Core VS Code, JetBrains, and CLI coding agent; AI usage is billed separately or supplied via BYOK/local models.
- Teams$15/user / month
Adds centralized billing, usage analytics, shared modes, shared BYOK, team management, privacy controls, and priority support.
- EnterpriseCustom
Adds model/provider restrictions, private gateway BYOK, audit logs, SSO/OIDC/SCIM, SLA commitments, and dedicated support.
- Auto Free / BYOK / Local$0 / month
Use free routed models where available, bring provider keys, or run local models with Ollama, LM Studio, or Atomic Chat.
- Kilo Gateway$0 + usage / month
Pay-as-you-go hosted inference at provider rates with no AI inference markup.
Privacy & Security
Continue
Continue documents anonymous telemetry in the open-source extensions, says it strips personally identifiable information, and provides opt-out controls for IDE extensions and the CLI. Local and offline setups are documented, but privacy also depends on the chosen model provider, GitHub integration, telemetry settings, and any configured data destinations.
Kilo Code
Kilo Code can use local models through Ollama, LM Studio, and Atomic Chat for workflows where code and prompts stay on the local machine. Hosted Gateway, Cloud Agents, code review, and BYOK routing may send prompts, repository context, or outputs to Kilo infrastructure and/or the selected model provider, so sensitive repositories should be reviewed against provider terms, enterprise controls, and internal policy.
Choose Continue if...
- Developers who want AI coding assistance inside VS Code without switching to a full AI-native editor.
- Teams that want AI review rules stored in the repository and enforced as PR status checks.
- Organizations that need model flexibility across cloud, local, self-hosted, and gateway providers.
- Developers building custom coding agents with YAML configuration, rules, prompts, models, and tools.
- Engineering teams experimenting with AI quality gates before adopting larger autonomous coding systems.
Choose Kilo Code if...
- Developers who want an open-source AI coding agent inside VS Code or JetBrains.
- Teams that want BYOK, shared modes, usage analytics, and centralized AI cost controls.
- Power users who switch between IDE and terminal workflows.
- Developers comparing Roo Code, Cline, Continue, Cursor, and Claude Code.
- Privacy-conscious workflows that can run capable local models.
Avoid Continue if...
- Users who want a polished all-in-one AI IDE with minimal configuration.
- Teams that prefer a single vendor-managed model and billing experience.
- JetBrains-heavy teams that need the IDE plugin to be the primary supported path.
- Users who do not want token-based billing for hosted model usage.
- Organizations that are uncomfortable with the current read-only status of the legacy main GitHub repository.
Avoid Kilo Code if...
- Users who only need lightweight autocomplete with minimal setup.
- Non-technical users looking for a no-code prompt-to-app builder.
- Teams that require a single fixed first-party model vendor.
- Developers without budget or hardware for higher-capability model usage.