--- title: "ai-getting-started vs starcoder" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/a16z-infra-ai-getting-started-vs-bigcode-project-starcoder" tools: ["a16z-infra-ai-getting-started", "bigcode-project-starcoder"] --- # ai-getting-started vs starcoder *GraphCanon updated Oct 7, 2026* ## Verdict Pick ai-getting-started if ai-getting-started is a TypeScript-based JavaScript AI tool tailored for weekend projects, offering everything from model implementation to deployment configurations; pick starcoder if starcoder, under Apache-2.0 license, provides tools for installation and usage of StarCoder, supporting both fine-tuning and inference processes. [ai-getting-started](https://ai-getting-started.com/) reports 4.1k GitHub stars, 659 forks, and 16 open issues, last pushed Aug 21, 2024. [starcoder](https://github.com/bigcode-project/starcoder) has 7.5k stars, 521 forks, and 104 open issues, last pushed Feb 27, 2024. Figures are from public GitHub metadata via [ai-getting-started's repository](https://github.com/a16z-infra/ai-getting-started) and [starcoder's repository](https://github.com/bigcode-project/starcoder). | | [ai-getting-started](/tools/a16z-infra-ai-getting-started.md) | [starcoder](/tools/bigcode-project-starcoder.md) | | --- | --- | --- | | Tagline | A Javascript AI getting started stack for weekend projects | Home of StarCoder: fine-tuning & inference! | | Stars | 4,142 | 7,501 | | Forks | 659 | 521 | | Open issues | 16 | 104 | | Language | TypeScript | Python | | Adopt for | ai-getting-started is a TypeScript-based JavaScript AI tool tailored for weekend projects, offering everything from model implementation to deployment configurations. | Starcoder, under Apache-2.0 license, provides tools for installation and usage of StarCoder, supporting both fine-tuning and inference processes. | | Persona | - | - | | Runtime | - | - | | License | MIT | Apache-2.0 | | Categories | Developer Tools, Model Training, Vector Databases | Inference & Serving, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [ai-getting-started](/tools/a16z-infra-ai-getting-started.md) | [starcoder](/tools/bigcode-project-starcoder.md) | | --- | --- | --- | | Days since push | 759d | 953d | | Open issues (now) | 16 | 104 | | Stars delta | +1 (30d) | -8 (30d) | | Open issues delta | 0 (30d) | +1 (30d) | | Full report | [trust report](/tools/a16z-infra-ai-getting-started/trust.md) | [trust report](/tools/bigcode-project-starcoder/trust.md) | ## Decision facts: ai-getting-started - **Adopt for:** ai-getting-started is a TypeScript-based JavaScript AI tool tailored for weekend projects, offering everything from model implementation to deployment configurations. ## Decision facts: starcoder - **Adopt for:** Starcoder, under Apache-2.0 license, provides tools for installation and usage of StarCoder, supporting both fine-tuning and inference processes. ## Choose when ### Choose ai-getting-started if… - ai-getting-started is primarily TypeScript; starcoder is Python. - License: ai-getting-started is MIT, starcoder is Apache-2.0. - Tags unique to ai-getting-started: deployment, image models, javascript, text models. - Also covers Developer Tools, Vector Databases. - ai-getting-started ships Docker support for self-hosted deployment. - * Use this tool if you are already familiar with or prefer working in TypeScript and want an easy entry point into AI project development. ### Choose starcoder if… - starcoder is primarily Python; ai-getting-started is TypeScript. - License: starcoder is Apache-2.0, ai-getting-started is MIT. - Tags unique to starcoder: conda, fine-tuning, inference, pip. - Also covers Inference & Serving. - When you need to perform inference tasks on a model that can be managed within hardware constraints such as FP16 or BF16 formats in about 30GB of RAM ## When NOT to use ai-getting-started - * If your focus is on developing large-scale, production-level applications, this tool may not offer the necessary scalability features. - * Not suitable if you require highly customized vector stores or specific AI model training environments beyond what the package provides as it focuses more on a general setup. ## When NOT to use starcoder - Avoid if your environment lacks resources and you cannot meet the minimum memory requirement even in an 8-bit precision mode which needs under 20GB RAM - If you seek a tool that does not rely heavily on setup instructions guided by specific frameworks such as Hugging Face Transformers or PyTorch ## Common questions ### What is the difference between ai-getting-started and starcoder? ai-getting-started: A Javascript AI getting started stack for weekend projects. starcoder: Home of StarCoder: fine-tuning & inference!. See the comparison table for live GitHub stats and shared categories. ### When should I choose ai-getting-started over starcoder? Choose ai-getting-started over starcoder when ai-getting-started is primarily TypeScript; starcoder is Python; License: ai-getting-started is MIT, starcoder is Apache-2.0; Tags unique to ai-getting-started: deployment, image models, javascript, text models; Also covers Developer Tools, Vector Databases; ai-getting-started ships Docker support for self-hosted deployment; * Use this tool if you are already familiar with or prefer working in TypeScript and want an easy entry point into AI project development. ### When should I choose starcoder over ai-getting-started? Choose starcoder over ai-getting-started when starcoder is primarily Python; ai-getting-started is TypeScript; License: starcoder is Apache-2.0, ai-getting-started is MIT; Tags unique to starcoder: conda, fine-tuning, inference, pip; Also covers Inference & Serving; When you need to perform inference tasks on a model that can be managed within hardware constraints such as FP16 or BF16 formats in about 30GB of RAM. ### When should I avoid ai-getting-started? * If your focus is on developing large-scale, production-level applications, this tool may not offer the necessary scalability features. * Not suitable if you require highly customized vector stores or specific AI model training environments beyond what the package provides as it focuses more on a general setup. ### When should I avoid starcoder? Avoid if your environment lacks resources and you cannot meet the minimum memory requirement even in an 8-bit precision mode which needs under 20GB RAM If you seek a tool that does not rely heavily on setup instructions guided by specific frameworks such as Hugging Face Transformers or PyTorch ### Is ai-getting-started or starcoder more popular on GitHub? starcoder has more GitHub stars (7,501 vs 4,142). Stars measure visibility, not whether either tool fits your constraints. ### Are ai-getting-started and starcoder open source? Yes - both are open-source projects on GitHub (ai-getting-started: MIT, starcoder: Apache-2.0). ### Where can I find alternatives to ai-getting-started or starcoder? GraphCanon lists graph-backed alternatives at [ai-getting-started alternatives](/tools/a16z-infra-ai-getting-started/alternatives) and [starcoder alternatives](/tools/bigcode-project-starcoder/alternatives) ([ai-getting-started markdown twin](/tools/a16z-infra-ai-getting-started/alternatives.md), [starcoder markdown twin](/tools/bigcode-project-starcoder/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/a16z-infra-ai-getting-started-vs-bigcode-project-starcoder.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, ai-getting-started or starcoder? ai-getting-started: Dormant. starcoder: 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 ai-getting-started and starcoder? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [ai-getting-started trust report](/tools/a16z-infra-ai-getting-started/trust); [starcoder trust report](/tools/bigcode-project-starcoder/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=a16z-infra-ai-getting-started`](/api/graphcanon/graph?tool=a16z-infra-ai-getting-started) - 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/_