--- title: "LLM-Adapters vs AstrBot" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/agi-edgerunners-llm-adapters-vs-astrbotdevs-astrbot" tools: ["agi-edgerunners-llm-adapters", "astrbotdevs-astrbot"] --- # LLM-Adapters vs AstrBot *GraphCanon updated Jul 12, 2026* ## Verdict Pick LLM-Adapters if lLM-Adapters offers Python-based tools for efficient fine-tuning of language models with Apache-2.0 licensing; pick AstrBot if astrBot is an AI agent assistant and development framework that integrates multiple instant messaging platforms with various language models and plugins under the AGPL-3.0 license. [LLM-Adapters](https://arxiv.org/abs/2304.01933) reports 1.2k GitHub stars, 119 forks, and 55 open issues, last pushed Mar 10, 2024. [AstrBot](https://astrbot.app) has 36k stars, 2.5k forks, and 1.3k open issues, last pushed Jul 9, 2026. Figures are from public GitHub metadata via [LLM-Adapters's repository](https://github.com/AGI-Edgerunners/LLM-Adapters) and [AstrBot's repository](https://github.com/AstrBotDevs/AstrBot). | | [LLM-Adapters](/tools/agi-edgerunners-llm-adapters.md) | [AstrBot](/tools/astrbotdevs-astrbot.md) | | --- | --- | --- | | Tagline | Code for EMNLP 2023 Paper on Parameter-Efficient Fine-Tuning of LLMs | AI Agent Assistant & development framework that integrates lots of IM platforms, LLMs, plugins and AI feature | | Stars | 1,233 | 36,186 | | Forks | 119 | 2,513 | | Open issues | 55 | 1,315 | | Language | Python | Python | | Adopt for | LLM-Adapters offers Python-based tools for efficient fine-tuning of language models with Apache-2.0 licensing. | AstrBot is an AI agent assistant and development framework that integrates multiple instant messaging platforms with various language models and plugins under the AGPL-3.0 license. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | AGPL-3.0 | | Categories | LLM Frameworks, Model Training | AI Agents, LLM Frameworks | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [LLM-Adapters](/tools/agi-edgerunners-llm-adapters.md) | [AstrBot](/tools/astrbotdevs-astrbot.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 853d | 2d | | Open issues (now) | 55 | 1.3k | | Security scan | No lockfile | No MCP manifest | | Full report | [trust report](/tools/agi-edgerunners-llm-adapters/trust.md) | [trust report](/tools/astrbotdevs-astrbot/trust.md) | ## Decision facts: LLM-Adapters - **Adopt for:** LLM-Adapters offers Python-based tools for efficient fine-tuning of language models with Apache-2.0 licensing. ## Decision facts: AstrBot - **Adopt for:** AstrBot is an AI agent assistant and development framework that integrates multiple instant messaging platforms with various language models and plugins under the AGPL-3.0 license. ## Choose when ### Choose LLM-Adapters if… - License: LLM-Adapters is Apache-2.0, AstrBot is AGPL-3.0. - Tags unique to LLM-Adapters: adapters, fine-tuning, large-language-models, parameter-efficient. - Also covers Model Training. - Optimizing resource usage when you need to fine-tune large language models without altering their core parameters ### Choose AstrBot if… - License: AstrBot is AGPL-3.0, LLM-Adapters is Apache-2.0. - Tags unique to AstrBot: agent, ai, astrbot, chatbot. - Also covers AI Agents. - AstrBot ships Docker support for self-hosted deployment. - When you require a highly integrative environment where your AI agents can communicate across different instant messaging platforms like Discord, Telegram, QQ, and others. ## When NOT to use LLM-Adapters - You require a full retraining approach that modifies all model weights, not just adapters - Your project timeline does not allow for integrating and testing new methodologies from recent papers like EMNLP 2023 ## When NOT to use AstrBot - If you are looking for proprietary solutions or do not want to comply with the AGPL-3.0 open-source license requirements, as AstrBot might not suit businesses preferring closed development. - In scenarios where a very streamlined or simple AI agent without extensive plugin and platform customizability is required due to time constraints or a specific project scope that does not need broad, - +adaptability. ## Common questions ### What is the difference between LLM-Adapters and AstrBot? LLM-Adapters: Code for EMNLP 2023 Paper on Parameter-Efficient Fine-Tuning of LLMs. AstrBot: AI Agent Assistant & development framework that integrates lots of IM platforms, LLMs, plugins and AI feature. See the comparison table for live GitHub stats and shared categories. ### When should I choose LLM-Adapters over AstrBot? Choose LLM-Adapters over AstrBot when License: LLM-Adapters is Apache-2.0, AstrBot is AGPL-3.0; Tags unique to LLM-Adapters: adapters, fine-tuning, large-language-models, parameter-efficient; Also covers Model Training; Optimizing resource usage when you need to fine-tune large language models without altering their core parameters. ### When should I choose AstrBot over LLM-Adapters? Choose AstrBot over LLM-Adapters when License: AstrBot is AGPL-3.0, LLM-Adapters is Apache-2.0; Tags unique to AstrBot: agent, ai, astrbot, chatbot; Also covers AI Agents; AstrBot ships Docker support for self-hosted deployment; When you require a highly integrative environment where your AI agents can communicate across different instant messaging platforms like Discord, Telegram, QQ, and others. ### When should I avoid LLM-Adapters? You require a full retraining approach that modifies all model weights, not just adapters Your project timeline does not allow for integrating and testing new methodologies from recent papers like EMNLP 2023 ### When should I avoid AstrBot? If you are looking for proprietary solutions or do not want to comply with the AGPL-3.0 open-source license requirements, as AstrBot might not suit businesses preferring closed development. In scenarios where a very streamlined or simple AI agent without extensive plugin and platform customizability is required due to time constraints or a specific project scope that does not need broad, +adaptability. ### Is LLM-Adapters or AstrBot more popular on GitHub? AstrBot has more GitHub stars (36,186 vs 1,233). Stars measure visibility, not whether either tool fits your constraints. ### Are LLM-Adapters and AstrBot open source? Yes - both are open-source projects on GitHub (LLM-Adapters: Apache-2.0, AstrBot: AGPL-3.0). ### Where can I find alternatives to LLM-Adapters or AstrBot? GraphCanon lists graph-backed alternatives at [LLM-Adapters alternatives](/tools/agi-edgerunners-llm-adapters/alternatives) and [AstrBot alternatives](/tools/astrbotdevs-astrbot/alternatives) ([LLM-Adapters markdown twin](/tools/agi-edgerunners-llm-adapters/alternatives.md), [AstrBot markdown twin](/tools/astrbotdevs-astrbot/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/agi-edgerunners-llm-adapters-vs-astrbotdevs-astrbot.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, LLM-Adapters or AstrBot? LLM-Adapters: Dormant. AstrBot: 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 LLM-Adapters and AstrBot? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLM-Adapters trust report](/tools/agi-edgerunners-llm-adapters/trust); [AstrBot trust report](/tools/astrbotdevs-astrbot/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=agi-edgerunners-llm-adapters`](/api/graphcanon/graph?tool=agi-edgerunners-llm-adapters) - 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/_