--- title: "nextpy vs caveman" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/dot-agent-nextpy-vs-juliusbrussee-caveman" tools: ["dot-agent-nextpy", "juliusbrussee-caveman"] --- # nextpy vs caveman *GraphCanon updated Sep 20, 2026* ## Verdict Pick nextpy if nextpy is a framework developed for building self-modifying software with advanced prompt engineering and session state management specifically targeted at large language models; pick caveman if caveman reduces token usage by 65% through minimalistic language for coding agents, supporting two sizes and primarily written in Go. [nextpy](https://dotagent.ai) reports 2.3k GitHub stars, 179 forks, and 23 open issues, last pushed May 1, 2024. [caveman](https://docs.caveman.so/docs/quickstart) has 106k stars, 6.2k forks, and 127 open issues, last pushed Sep 18, 2026. Figures are from public GitHub metadata via [nextpy's repository](https://github.com/dot-agent/nextpy) and [caveman's repository](https://github.com/JuliusBrussee/caveman). | | [nextpy](/tools/dot-agent-nextpy.md) | [caveman](/tools/juliusbrussee-caveman.md) | | --- | --- | --- | | Tagline | Self-Modifying Framework from the Future | Reduces token usage by 65% through minimalistic language for coding agents | | Stars | 2,348 | 106,401 | | Forks | 179 | 6,165 | | Open issues | 23 | 127 | | Language | Python | Go | | Adopt for | Nextpy is a framework developed for building self-modifying software with advanced prompt engineering and session state management specifically targeted at large language models. | Caveman reduces token usage by 65% through minimalistic language for coding agents, supporting two sizes and primarily written in Go. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Caveman operates under a split license: MIT for the skill, Agent SDK, and initializer, and BSL-1.1 for the engine-linked runtime, which converts to Apache-2.0 by 2030 or four years after shipping. | | Categories | AI Agents, Inference & Serving, Model Training | AI Agents, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [nextpy](/tools/dot-agent-nextpy.md) | [caveman](/tools/juliusbrussee-caveman.md) | | --- | --- | --- | | Maintenance | Dormant (18%) | Very active (96%) | | Days since push | 871d | 0d | | Open issues (now) | 23 | 127 | | Stars delta | 0 (30d) | +8.0k (30d) | | Open issues delta | 0 (30d) | -358 (30d) | | Owner type | Organization | User | | Full report | [trust report](/tools/dot-agent-nextpy/trust.md) | [trust report](/tools/juliusbrussee-caveman/trust.md) | ## Decision facts: nextpy - **Adopt for:** Nextpy is a framework developed for building self-modifying software with advanced prompt engineering and session state management specifically targeted at large language models. ## Decision facts: caveman - **Pricing:** freemium - The skill, Agent SDK, and initializer are free under MIT license. Hosting Caveman for third parties requires a commercial license. - **Requirements:** Min 1 GB RAM; Caveman is primarily written in Go and supports two sizes, allowing for flexible deployment. - **Adopt for:** Caveman reduces token usage by 65% through minimalistic language for coding agents, supporting two sizes and primarily written in Go. - **License detail:** Caveman operates under a split license: MIT for the skill, Agent SDK, and initializer, and BSL-1.1 for the engine-linked runtime, which converts to Apache-2.0 by 2030 or four years after shipping. ## Choose when ### Choose nextpy if… - nextpy is primarily Python; caveman is Go. - License: nextpy is Apache-2.0, caveman is Other. - Tags unique to nextpy: agent, agi, ai-agents, autogpt. - Also covers Inference & Serving. - When you require precise control over what the AI system can do by setting clear boundaries, ensuring it does not overstep defined limits while remaining dynamic and self-improving. ### Choose caveman if… - caveman is primarily Go; nextpy is Python. - License: caveman is Other, nextpy is Apache-2.0. - Pricing: The skill, Agent SDK, and initializer are free under MIT license. Hosting Caveman for third parties requires a commercial license.. - Requirements: Min 1 GB RAM; Caveman is primarily written in Go and supports two sizes, allowing for flexible deployment.. - Tags unique to caveman: ai, anthropic, caveman, claude. - caveman ships Docker support for self-hosted deployment. - When you need to significantly reduce token usage in coding agents, as Caveman can cut usage by 65% through its simplified language style. ## When NOT to use nextpy - If your project does not need precise boundary controls for AI systems or if full session state management with LLMs is not required. - When working with proprietary models that do not support maintaining state with LLMs or reusing KV caches, since some of Nextpy's optimizations are only available for open-source models. ## When NOT to use caveman - If your project requires a fully OSI-approved open-source license, as Caveman's engine-linked runtime is BSL-1.1, which is not OSI-approved until a future date. - When you need a tool that does not involve a trademarked name and logo, as Caveman is trademarked and has specific guidelines for its use. ## Common questions ### What is the difference between nextpy and caveman? nextpy: Self-Modifying Framework from the Future. caveman: Reduces token usage by 65% through minimalistic language for coding agents. See the comparison table for live GitHub stats and shared categories. ### When should I choose nextpy over caveman? Choose nextpy over caveman when nextpy is primarily Python; caveman is Go; License: nextpy is Apache-2.0, caveman is Other; Tags unique to nextpy: agent, agi, ai-agents, autogpt; Also covers Inference & Serving; When you require precise control over what the AI system can do by setting clear boundaries, ensuring it does not overstep defined limits while remaining dynamic and self-improving. ### When should I choose caveman over nextpy? Choose caveman over nextpy when caveman is primarily Go; nextpy is Python; License: caveman is Other, nextpy is Apache-2.0; Pricing: The skill, Agent SDK, and initializer are free under MIT license. Hosting Caveman for third parties requires a commercial license.; Requirements: Min 1 GB RAM; Caveman is primarily written in Go and supports two sizes, allowing for flexible deployment.; Tags unique to caveman: ai, anthropic, caveman, claude; caveman ships Docker support for self-hosted deployment; When you need to significantly reduce token usage in coding agents, as Caveman can cut usage by 65% through its simplified language style. ### When should I avoid nextpy? If your project does not need precise boundary controls for AI systems or if full session state management with LLMs is not required. When working with proprietary models that do not support maintaining state with LLMs or reusing KV caches, since some of Nextpy's optimizations are only available for open-source models. ### When should I avoid caveman? If your project requires a fully OSI-approved open-source license, as Caveman's engine-linked runtime is BSL-1.1, which is not OSI-approved until a future date. When you need a tool that does not involve a trademarked name and logo, as Caveman is trademarked and has specific guidelines for its use. ### Is nextpy or caveman more popular on GitHub? caveman has more GitHub stars (106,401 vs 2,348). Stars measure visibility, not whether either tool fits your constraints. ### Are nextpy and caveman open source? Yes - both are open-source projects on GitHub (nextpy: Apache-2.0, caveman: Other). ### Where can I find alternatives to nextpy or caveman? GraphCanon lists graph-backed alternatives at [nextpy alternatives](/tools/dot-agent-nextpy/alternatives) and [caveman alternatives](/tools/juliusbrussee-caveman/alternatives) ([nextpy markdown twin](/tools/dot-agent-nextpy/alternatives.md), [caveman markdown twin](/tools/juliusbrussee-caveman/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/dot-agent-nextpy-vs-juliusbrussee-caveman.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, nextpy or caveman? nextpy: Dormant. caveman: 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 nextpy and caveman? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [nextpy trust report](/tools/dot-agent-nextpy/trust); [caveman trust report](/tools/juliusbrussee-caveman/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=dot-agent-nextpy`](/api/graphcanon/graph?tool=dot-agent-nextpy) - 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/_