--- title: "amazon-bedrock-samples vs aikit" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/aws-samples-amazon-bedrock-samples-vs-kaito-project-aikit" tools: ["aws-samples-amazon-bedrock-samples", "kaito-project-aikit"] --- # amazon-bedrock-samples vs aikit *GraphCanon updated Aug 24, 2026* ## Verdict Pick amazon-bedrock-samples if amazon-bedrock-samples; 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. [amazon-bedrock-samples](https://aws.amazon.com/bedrock/) reports 1.5k GitHub stars, 719 forks, and 133 open issues, last pushed Aug 21, 2026. [aikit](https://kaito-project.github.io/aikit/) has 537 stars, 57 forks, and 40 open issues, last pushed Aug 24, 2026. Figures are from public GitHub metadata via [amazon-bedrock-samples's repository](https://github.com/aws-samples/amazon-bedrock-samples) and [aikit's repository](https://github.com/kaito-project/aikit). | | [amazon-bedrock-samples](/tools/aws-samples-amazon-bedrock-samples.md) | [aikit](/tools/kaito-project-aikit.md) | | --- | --- | --- | | Tagline | Examples for using Amazon Bedrock Service including embedding and generative AI models | Fine-tune, build, and deploy open-source LLMs easily! | | Stars | 1,493 | 537 | | Forks | 719 | 57 | | Open issues | 133 | 40 | | Language | Jupyter Notebook | Go | | Adopt for | amazon-bedrock-samples | 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 | Licensed under MIT-0, allowing for use and distribution without attribution but with no warranties. | MIT | | Categories | Data & Retrieval, LLM Frameworks | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [amazon-bedrock-samples](/tools/aws-samples-amazon-bedrock-samples.md) | [aikit](/tools/kaito-project-aikit.md) | | --- | --- | --- | | Days since push | 1d | 0d | | Open issues (now) | 133 | 40 | | Stars delta | +16 (30d) | +3 (30d) | | Open issues delta | +3 (30d) | -3 (30d) | | Full report | [trust report](/tools/aws-samples-amazon-bedrock-samples/trust.md) | [trust report](/tools/kaito-project-aikit/trust.md) | ## Decision facts: amazon-bedrock-samples - **Requirements:** Development environment must support Jupyter Notebooks to utilize the repository content effectively. - **Adopt for:** amazon-bedrock-samples - **License detail:** Licensed under MIT-0, allowing for use and distribution without attribution but with no warranties. ## 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 amazon-bedrock-samples if… - amazon-bedrock-samples is primarily Jupyter Notebook; aikit is Go. - License: amazon-bedrock-samples is MIT-0, aikit is MIT. - Requirements: Development environment must support Jupyter Notebooks to utilize the repository content effectively.. - Tags unique to amazon-bedrock-samples: amazon-bedrock, amazon-titan, embeddings, generative-ai. - Also covers Data & Retrieval. - When you need starter code samples for interacting with Amazon Bedrock Service foundational models in Jupyter Notebooks. ### Choose aikit if… - aikit is primarily Go; amazon-bedrock-samples is Jupyter Notebook. - License: aikit is MIT, amazon-bedrock-samples is MIT-0. - Tags unique to aikit: ai, buildkit, chatgpt, docker. - Also covers Inference & Serving, Model Training. - aikit ships Docker support for self-hosted deployment. - - You need a flexible solution specifically built using Go and prefer its concurrency model. ## When NOT to use amazon-bedrock-samples - If you are looking for samples or frameworks not hosted in Jupyter Notebook format, as this may require manual conversion or scripting. - When your project's requirements do not include using Amazon Bedrock Service models, favoring other cloud service providers' foundational models instead. - For scenarios involving proprietary or closed-source AI model integrations incompatible with the MIT-0 license under which these samples are available. ## 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 amazon-bedrock-samples and aikit? amazon-bedrock-samples: Examples for using Amazon Bedrock Service including embedding and generative AI models. 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 amazon-bedrock-samples over aikit? Choose amazon-bedrock-samples over aikit when amazon-bedrock-samples is primarily Jupyter Notebook; aikit is Go; License: amazon-bedrock-samples is MIT-0, aikit is MIT; Requirements: Development environment must support Jupyter Notebooks to utilize the repository content effectively.; Tags unique to amazon-bedrock-samples: amazon-bedrock, amazon-titan, embeddings, generative-ai; Also covers Data & Retrieval; When you need starter code samples for interacting with Amazon Bedrock Service foundational models in Jupyter Notebooks. ### When should I choose aikit over amazon-bedrock-samples? Choose aikit over amazon-bedrock-samples when aikit is primarily Go; amazon-bedrock-samples is Jupyter Notebook; License: aikit is MIT, amazon-bedrock-samples is MIT-0; Tags unique to aikit: ai, buildkit, chatgpt, docker; Also covers Inference & Serving, Model Training; aikit ships Docker support for self-hosted deployment; - You need a flexible solution specifically built using Go and prefer its concurrency model. ### When should I avoid amazon-bedrock-samples? If you are looking for samples or frameworks not hosted in Jupyter Notebook format, as this may require manual conversion or scripting. When your project's requirements do not include using Amazon Bedrock Service models, favoring other cloud service providers' foundational models instead. For scenarios involving proprietary or closed-source AI model integrations incompatible with the MIT-0 license under which these samples are available. ### 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 amazon-bedrock-samples or aikit more popular on GitHub? amazon-bedrock-samples has more GitHub stars (1,493 vs 537). Stars measure visibility, not whether either tool fits your constraints. ### Are amazon-bedrock-samples and aikit open source? Yes - both are open-source projects on GitHub (amazon-bedrock-samples: MIT-0, aikit: MIT). ### Where can I find alternatives to amazon-bedrock-samples or aikit? GraphCanon lists graph-backed alternatives at [amazon-bedrock-samples alternatives](/tools/aws-samples-amazon-bedrock-samples/alternatives) and [aikit alternatives](/tools/kaito-project-aikit/alternatives) ([amazon-bedrock-samples markdown twin](/tools/aws-samples-amazon-bedrock-samples/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/aws-samples-amazon-bedrock-samples-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, amazon-bedrock-samples or aikit? amazon-bedrock-samples: 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 amazon-bedrock-samples and aikit? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [amazon-bedrock-samples trust report](/tools/aws-samples-amazon-bedrock-samples/trust); [aikit trust report](/tools/kaito-project-aikit/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=aws-samples-amazon-bedrock-samples`](/api/graphcanon/graph?tool=aws-samples-amazon-bedrock-samples) - 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/_