--- title: "aisix vs aikit" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/api7-aisix-vs-kaito-project-aikit" tools: ["api7-aisix", "kaito-project-aikit"] --- # aisix vs aikit *GraphCanon updated Jul 15, 2026* ## Verdict Pick aisix if aISIX is a Rust-native AI gateway designed for routing and managing traffic to various AI providers; 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. [aisix](https://api7.ai/ai-gateway) reports 64 GitHub stars, 9 forks, and 77 open issues, last pushed Jul 15, 2026. [aikit](https://kaito-project.github.io/aikit/) has 533 stars, 57 forks, and 41 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [aisix's repository](https://github.com/api7/aisix) and [aikit's repository](https://github.com/kaito-project/aikit). | | [aisix](/tools/api7-aisix.md) | [aikit](/tools/kaito-project-aikit.md) | | --- | --- | --- | | Tagline | Open-source AI gateway for LLMs & AI agents | Fine-tune, build, and deploy open-source LLMs easily! | | Stars | 64 | 533 | | Forks | 9 | 57 | | Open issues | 77 | 41 | | Language | Rust | Go | | Adopt for | AISIX is a Rust-native AI gateway designed for routing and managing traffic to various AI providers | Aikit is a toolkit designed for fine-tuning, building and deploying large language models (LLMs) with an emphasis on open-source technologies. | | Persona | - | - | | Runtime | - | - | | License | AISIX is available under the Apache License, Version 2.0 which allows you to freely use, modify, and distribute it with proper attribution | MIT | | Categories | AI Agents, Inference & Serving | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [aisix](/tools/api7-aisix.md) | [aikit](/tools/kaito-project-aikit.md) | | --- | --- | --- | | Open issues (now) | 77 | 41 | | Full report | [trust report](/tools/api7-aisix/trust.md) | [trust report](/tools/kaito-project-aikit/trust.md) | ## Decision facts: aisix - **Pricing:** freemium - The open-source core (AISIX Gateway) can be used for free. For advanced features like team governance, budgets, and audit dashboard access, the AISIX Cloud is available on a managed SaaS model. - **Requirements:** Requires etcd running to store configurations; Self-hosted setup requires Docker Compose for local testing with example configuration files - **Adopt for:** AISIX is a Rust-native AI gateway designed for routing and managing traffic to various AI providers - **License detail:** AISIX is available under the Apache License, Version 2.0 which allows you to freely use, modify, and distribute it with proper attribution ## 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. ## Choose when ### Choose aisix if… - aisix is primarily Rust; aikit is Go. - License: aisix is Apache-2.0, aikit is MIT. - Pricing: The open-source core (AISIX Gateway) can be used for free. For advanced features like team governance, budgets, and audit dashboard access, the AISIX Cloud is available on a managed SaaS model.. - Requirements: Requires etcd running to store configurations; Self-hosted setup requires Docker Compose for local testing with example configuration files. - Tags unique to aisix: ai-agents, llm-gateway, observability, openai-compatible. - Also covers AI Agents. - When you need an OpenAI-compatible API that can route requests to multiple LLM providers like OpenAI, Anthropic, Gemini, and Bedrock ### Choose aikit if… - aikit is primarily Go; aisix is Rust. - License: aikit is MIT, aisix is Apache-2.0. - Tags unique to aikit: ai, buildkit, chatgpt, docker. - Also covers LLM Frameworks, Model Training. - - You need a flexible solution specifically built using Go and prefer its concurrency model. ## When NOT to use aisix - If you require a fully managed service with minimal setup and configuration since AISIX requires self-hosting or connecting to AISIX Cloud for management features - For projects preferring dynamic languages over statically compiled binaries, given that AISIX is built in Rust and ships as one static binary ## 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. ## Common questions ### What is the difference between aisix and aikit? aisix: Open-source AI gateway for LLMs & AI agents. aikit: Fine-tune, build, and deploy open-source LLMs easily!. See the comparison table for live GitHub stats and shared categories. ### When should I choose aisix over aikit? Choose aisix over aikit when aisix is primarily Rust; aikit is Go; License: aisix is Apache-2.0, aikit is MIT; Pricing: The open-source core (AISIX Gateway) can be used for free. For advanced features like team governance, budgets, and audit dashboard access, the AISIX Cloud is available on a managed SaaS model.; Requirements: Requires etcd running to store configurations; Self-hosted setup requires Docker Compose for local testing with example configuration files; Tags unique to aisix: ai-agents, llm-gateway, observability, openai-compatible; Also covers AI Agents; When you need an OpenAI-compatible API that can route requests to multiple LLM providers like OpenAI, Anthropic, Gemini, and Bedrock. ### When should I choose aikit over aisix? Choose aikit over aisix when aikit is primarily Go; aisix is Rust; License: aikit is MIT, aisix is Apache-2.0; Tags unique to aikit: ai, buildkit, chatgpt, docker; Also covers LLM Frameworks, Model Training; - You need a flexible solution specifically built using Go and prefer its concurrency model. ### When should I avoid aisix? If you require a fully managed service with minimal setup and configuration since AISIX requires self-hosting or connecting to AISIX Cloud for management features For projects preferring dynamic languages over statically compiled binaries, given that AISIX is built in Rust and ships as one static binary ### 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. ### Is aisix or aikit more popular on GitHub? aikit has more GitHub stars (533 vs 64). Stars measure visibility, not whether either tool fits your constraints. ### Are aisix and aikit open source? Yes - both are open-source projects on GitHub (aisix: Apache-2.0, aikit: MIT). ### Where can I find alternatives to aisix or aikit? GraphCanon lists graph-backed alternatives at [aisix alternatives](/tools/api7-aisix/alternatives) and [aikit alternatives](/tools/kaito-project-aikit/alternatives) ([aisix markdown twin](/tools/api7-aisix/alternatives.md), [aikit markdown twin](/tools/kaito-project-aikit/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/api7-aisix-vs-kaito-project-aikit.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, aisix or aikit? aisix: Very active. aikit: Very active. 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 aisix and aikit? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [aisix trust report](/tools/api7-aisix/trust); [aikit trust report](/tools/kaito-project-aikit/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=api7-aisix`](/api/graphcanon/graph?tool=api7-aisix) - 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/_