--- title: "aikit vs gateway" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/kaito-project-aikit-vs-trylonai-gateway" tools: ["kaito-project-aikit", "trylonai-gateway"] --- # aikit vs gateway *GraphCanon updated Jul 15, 2026* ## Verdict Pick aikit if aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies; pick gateway if self-hosted firewall for securing AI applications with guardrails and content moderation. [aikit](https://kaito-project.github.io/aikit/) reports 533 GitHub stars, 57 forks, and 41 open issues, last pushed Jul 11, 2026. [gateway](https://www.trylon.ai) has 126 stars, 12 forks, and 0 open issues, last pushed Jun 25, 2025. Figures are from public GitHub metadata via [aikit's repository](https://github.com/kaito-project/aikit) and [gateway's repository](https://github.com/trylonai/gateway). | | [aikit](/tools/kaito-project-aikit.md) | [gateway](/tools/trylonai-gateway.md) | | --- | --- | --- | | Tagline | Fine-tune, build, and deploy open-source LLMs easily! | Self-hosted firewall for securing AI applications with guardrails and content moderation. | | Stars | 533 | 126 | | Forks | 57 | 12 | | Open issues | 41 | 0 | | Language | Go | Python | | Adopt for | Aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies. | Self-hosted firewall for securing AI applications with guardrails and content moderation. | | Persona | - | - | | Runtime | - | - | | License | MIT | Other | | Categories | Inference & Serving, LLM Frameworks, Model Training | Evaluation & Observability, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aikit](/tools/kaito-project-aikit.md) | [gateway](/tools/trylonai-gateway.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Dormant (18%) | | Days since push | 0d | 385d | | Open issues (now) | 41 | 0 | | Full report | [trust report](/tools/kaito-project-aikit/trust.md) | [trust report](/tools/trylonai-gateway/trust.md) | ## Decision facts: aikit - **Adopt for:** Aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies. ## Decision facts: gateway - **Pricing:** freemium - Open-source with no explicit monetary cost, but requires users to handle infrastructure costs associated with local Docker deployment - **Requirements:** Min 4 GB RAM; Requires Docker; Docker and Docker Compose are required for deployment; Initial launch takes several minutes due to downloading machine learning models (~1.5GB+) for the first time - **Adopt for:** Self-hosted firewall for securing AI applications with guardrails and content moderation. ## Choose when ### Choose aikit if… - aikit is primarily Go; gateway is Python. - License: aikit is MIT, gateway is Other. - Tags unique to aikit: ai, buildkit, chatgpt, docker. - Also covers Inference & Serving, Model Training. - - You need a flexible solution specifically built using Go and prefer its concurrency model. ### Choose gateway if… - gateway is primarily Python; aikit is Go. - License: gateway is Other, aikit is MIT. - Pricing: Open-source with no explicit monetary cost, but requires users to handle infrastructure costs associated with local Docker deployment. - Requirements: Min 4 GB RAM; Requires Docker; Docker and Docker Compose are required for deployment; Initial launch takes several minutes due to downloading machine learning models (~1.5GB+) for the first time. - Tags unique to gateway: content-moderation, docker-compose, guardrails, pii-redaction. - Also covers Evaluation & Observability. - When you need to self-host a secure gateway for LLM-based AI applications that requires local deployment via Docker ## When NOT to use aikit - - You have a preference or requirement for Python-based tools due to the lack of native support in Aikit. - - If your deployment setup strictly uses cloud-specific platforms and you do not use Kubernetes or Docker, as Aikit heavily integrates with containerized environments like these. ## When NOT to use gateway - Avoid if you are looking for cloud-managed services, as this tool is designed solely for local or self-hosted environments - Not suitable if you require extensive customization beyond the provided policies.yaml file and predefined guardrails for content moderation and security ## Common questions ### What is the difference between aikit and gateway? aikit: Fine-tune, build, and deploy open-source LLMs easily!. gateway: Self-hosted firewall for securing AI applications with guardrails and content moderation.. See the comparison table for live GitHub stats and shared categories. ### When should I choose aikit over gateway? Choose aikit over gateway when aikit is primarily Go; gateway is Python; License: aikit is MIT, gateway is Other; Tags unique to aikit: ai, buildkit, chatgpt, docker; Also covers Inference & Serving, Model Training; - You need a flexible solution specifically built using Go and prefer its concurrency model. ### When should I choose gateway over aikit? Choose gateway over aikit when gateway is primarily Python; aikit is Go; License: gateway is Other, aikit is MIT; Pricing: Open-source with no explicit monetary cost, but requires users to handle infrastructure costs associated with local Docker deployment; Requirements: Min 4 GB RAM; Requires Docker; Docker and Docker Compose are required for deployment; Initial launch takes several minutes due to downloading machine learning models (~1.5GB+) for the first time; Tags unique to gateway: content-moderation, docker-compose, guardrails, pii-redaction; Also covers Evaluation & Observability; When you need to self-host a secure gateway for LLM-based AI applications that requires local deployment via Docker. ### When should I avoid aikit? - You have a preference or requirement for Python-based tools due to the lack of native support in Aikit. - If your deployment setup strictly uses cloud-specific platforms and you do not use Kubernetes or Docker, as Aikit heavily integrates with containerized environments like these. ### When should I avoid gateway? Avoid if you are looking for cloud-managed services, as this tool is designed solely for local or self-hosted environments Not suitable if you require extensive customization beyond the provided policies.yaml file and predefined guardrails for content moderation and security ### Is aikit or gateway more popular on GitHub? aikit has more GitHub stars (533 vs 126). Stars measure visibility, not whether either tool fits your constraints. ### Are aikit and gateway open source? Yes - both are open-source projects on GitHub (aikit: MIT, gateway: Other). ### Where can I find alternatives to aikit or gateway? GraphCanon lists graph-backed alternatives at [aikit alternatives](/tools/kaito-project-aikit/alternatives) and [gateway alternatives](/tools/trylonai-gateway/alternatives) ([aikit markdown twin](/tools/kaito-project-aikit/alternatives.md), [gateway markdown twin](/tools/trylonai-gateway/alternatives.md)), ranked by typed relationship edges rather than popularity votes. ### Is there a machine-readable version of this comparison? Yes. The markdown twin at [this comparison](/compare/kaito-project-aikit-vs-trylonai-gateway.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aikit or gateway? aikit: Very active. gateway: Dormant. Compare maintenance labels, days since push, and release cadence in the trust section below - stars alone do not measure maintenance. ### Where are the full trust reports for aikit and gateway? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aikit trust report](/tools/kaito-project-aikit/trust); [gateway trust report](/tools/trylonai-gateway/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=kaito-project-aikit`](/api/graphcanon/graph?tool=kaito-project-aikit) - LLM index: [/llms.txt](/llms.txt) - Full corpus: [/llms-full.txt](/llms-full.txt) _GraphCanon - The knowledge graph for AI development. https://www.graphcanon.com/_