--- title: "graphify vs chunktuner" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/graphify-labs-graphify-vs-shantanu-deshmukh-chunktuner" tools: ["graphify-labs-graphify", "shantanu-deshmukh-chunktuner"] --- # graphify vs chunktuner *GraphCanon updated Jul 12, 2026* ## Verdict Pick graphify if graphify transforms a variety of inputs into a unified knowledge graph, ideal for creating searchable insights from mixed content types; pick chunktuner if a specialized benchmarking suite for optimizing chunking strategies in RAG corpora, offering a comprehensive toolkit inclusive of CLI and server components. [graphify](https://graphifylabs.ai/) reports 82k GitHub stars, 8.1k forks, and 452 open issues, last pushed Jul 11, 2026. [chunktuner](https://shantanu-deshmukh.github.io/chunktuner/) has 2 stars, 0 forks, and 0 open issues, last pushed Jun 21, 2026. Figures are from public GitHub metadata via [graphify's repository](https://github.com/Graphify-Labs/graphify) and [chunktuner's repository](https://github.com/shantanu-deshmukh/chunktuner). | | [graphify](/tools/graphify-labs-graphify.md) | [chunktuner](/tools/shantanu-deshmukh-chunktuner.md) | | --- | --- | --- | | Tagline | Turn any code or documentation into a queryable knowledge graph | Benchmark and optimize chunking strategies for RAG corpus | | Stars | 82,139 | 2 | | Forks | 8,086 | 0 | | Open issues | 452 | 0 | | Language | Python | Python | | Adopt for | Graphify transforms a variety of inputs into a unified knowledge graph, ideal for creating searchable insights from mixed content types. | A specialized benchmarking suite for optimizing chunking strategies in RAG corpora, offering a comprehensive toolkit inclusive of CLI and server components. | | Persona | - | - | | Runtime | - | - | | License | MIT | MIT | | Categories | Data & Retrieval, AI Agents | Data & Retrieval, Evaluation & Observability | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [graphify](/tools/graphify-labs-graphify.md) | [chunktuner](/tools/shantanu-deshmukh-chunktuner.md) | | --- | --- | --- | | Maintenance | Very active (96%) | Active (82%) | | Days since push | 0d | 20d | | Open issues (now) | 452 | 0 | | Owner type | Organization | User | | Security scan | No lockfile | 2 low (2 low) | | Full report | [trust report](/tools/graphify-labs-graphify/trust.md) | [trust report](/tools/shantanu-deshmukh-chunktuner/trust.md) | ## Decision facts: graphify - **Requirements:** Ensure to install from the correct PyPI package named `graphifyy` (with double 'y') and not other similar-named packages which are unaffiliated.; Installation involves setting up a Python environment ('venv') and ensuring all required extras are installed. - **Adopt for:** Graphify transforms a variety of inputs into a unified knowledge graph, ideal for creating searchable insights from mixed content types. ## Decision facts: chunktuner - **Pricing:** freemium - Open source with an MIT license, offering free use for both personal and commercial projects. No costs beyond typical computing resources are implied by its usage. - **Adopt for:** A specialized benchmarking suite for optimizing chunking strategies in RAG corpora, offering a comprehensive toolkit inclusive of CLI and server components. ## Choose when ### Choose graphify if… - Requirements: Ensure to install from the correct PyPI package named `graphifyy` (with double 'y') and not other similar-named packages which are unaffiliated.; Installation involves setting up a Python environment ('venv') and ensuring all required extras are installed.. - Tags unique to graphify: gemini, rag, codex, skills. - Also covers AI Agents. - When you need to turn diverse file types (code, SQL schemas, documents, images) into a single queryable data structure that can be searched and analyzed together. ### Choose chunktuner if… - Pricing: Open source with an MIT license, offering free use for both personal and commercial projects. No costs beyond typical computing resources are implied by its usage.. - Tags unique to chunktuner: chunking, evaluation, llamaindex, llm. - Also covers Evaluation & Observability. - - You are working specifically with retrieval-augmented generation (RAG) systems which require tailored optimization and evaluation. ## When NOT to use graphify - If the project exclusively involves text-based content without requiring integration or querying across different file types (e.g., plain documents with no need for cross-referencing). - Avoid using Graphify if you are looking for a tool that focuses solely on visual graph representation without the depth of semantic querying capabilities. ## When NOT to use chunktuner - - If you do not deal with RAG systems or if the nature of your workflow does not benefit from specific optimizations in text chunking strategies across a corpus. - - You are working on projects that don't necessitate evaluation and optimization at the level provided by 'chunktuner', such as simpler tasks that can be managed without extensive configuration tools. ## Common questions ### What is the difference between graphify and chunktuner? graphify: Turn any code or documentation into a queryable knowledge graph. chunktuner: Benchmark and optimize chunking strategies for RAG corpus. See the comparison table for live GitHub stats and shared categories. ### When should I choose graphify over chunktuner? Choose graphify over chunktuner when Requirements: Ensure to install from the correct PyPI package named `graphifyy` (with double 'y') and not other similar-named packages which are unaffiliated.; Installation involves setting up a Python environment ('venv') and ensuring all required extras are installed.; Tags unique to graphify: gemini, rag, codex, skills; Also covers AI Agents; When you need to turn diverse file types (code, SQL schemas, documents, images) into a single queryable data structure that can be searched and analyzed together. ### When should I choose chunktuner over graphify? Choose chunktuner over graphify when Pricing: Open source with an MIT license, offering free use for both personal and commercial projects. No costs beyond typical computing resources are implied by its usage.; Tags unique to chunktuner: chunking, evaluation, llamaindex, llm; Also covers Evaluation & Observability; - You are working specifically with retrieval-augmented generation (RAG) systems which require tailored optimization and evaluation. ### When should I avoid graphify? If the project exclusively involves text-based content without requiring integration or querying across different file types (e.g., plain documents with no need for cross-referencing). Avoid using Graphify if you are looking for a tool that focuses solely on visual graph representation without the depth of semantic querying capabilities. ### When should I avoid chunktuner? - If you do not deal with RAG systems or if the nature of your workflow does not benefit from specific optimizations in text chunking strategies across a corpus. - You are working on projects that don't necessitate evaluation and optimization at the level provided by 'chunktuner', such as simpler tasks that can be managed without extensive configuration tools. ### Is graphify or chunktuner more popular on GitHub? graphify has more GitHub stars (82,139 vs 2). Stars measure visibility, not whether either tool fits your constraints. ### Are graphify and chunktuner open source? Yes - both are open-source projects on GitHub (graphify: MIT, chunktuner: MIT). ### Where can I find alternatives to graphify or chunktuner? GraphCanon lists graph-backed alternatives at [graphify alternatives](/tools/graphify-labs-graphify/alternatives) and [chunktuner alternatives](/tools/shantanu-deshmukh-chunktuner/alternatives) ([graphify markdown twin](/tools/graphify-labs-graphify/alternatives.md), [chunktuner markdown twin](/tools/shantanu-deshmukh-chunktuner/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/graphify-labs-graphify-vs-shantanu-deshmukh-chunktuner.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, graphify or chunktuner? graphify: Very active. chunktuner: 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 graphify and chunktuner? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [graphify trust report](/tools/graphify-labs-graphify/trust); [chunktuner trust report](/tools/shantanu-deshmukh-chunktuner/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=graphify-labs-graphify`](/api/graphcanon/graph?tool=graphify-labs-graphify) - 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/_