---
title: "khoj vs honcho"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/khoj-ai-khoj-vs-plastic-labs-honcho"
tools: ["khoj-ai-khoj", "plastic-labs-honcho"]
---

# khoj vs honcho

*GraphCanon updated Sep 20, 2026*

## Verdict

Pick khoj if khoj is a self-hosted AI assistant that supports integration with multiple LLMs, enabling users to build custom agents and conduct deep research using both web and local documents; pick honcho if memory Library for Stateful Agents.

[khoj](https://khoj.dev) reports 37k GitHub stars, 2.5k forks, and 150 open issues, last pushed Aug 2, 2026. [honcho](https://docs.honcho.dev) has 6.7k stars, 824 forks, and 163 open issues, last pushed Aug 18, 2026. Figures are from public GitHub metadata via [khoj's repository](https://github.com/khoj-ai/khoj) and [honcho's repository](https://github.com/plastic-labs/honcho).

| | [khoj](/tools/khoj-ai-khoj.md) | [honcho](/tools/plastic-labs-honcho.md) |
| --- | --- | --- |
| Tagline | Self-hostable AI second brain for personalized research and automation | Memory library for building stateful agents |
| Stars | 37,399 | 6,703 |
| Forks | 2,484 | 824 |
| Open issues | 150 | 163 |
| Language | Python | Python |
| Adopt for | Khoj is a self-hosted AI assistant that supports integration with multiple LLMs, enabling users to build custom agents and conduct deep research using both web and local documents. | Memory Library for Stateful Agents |
| Persona | - | - |
| Runtime | - | - |
| License | Khoj is licensed under AGPL-3.0, which means it is free to use, modify, and distribute, but any derivative works must also be released under the same license. | AGPL-3.0 |
| Categories | AI Agents, Data & Retrieval, Developer Tools, Inference & Serving, Model Training | AI Agents, Data & Retrieval |

## Trust and health

_Sourced signals - not a safety guarantee. No winner column._

| | [khoj](/tools/khoj-ai-khoj.md) | [honcho](/tools/plastic-labs-honcho.md) |
| --- | --- | --- |
| Maintenance | Steady (60%) | Very active (96%) |
| Days since push | 47d | 0d |
| Open issues (now) | 150 | 163 |
| Stars delta | +887 (30d) | +659 (30d) |
| Open issues delta | +17 (30d) | -3 (30d) |
| Full report | [trust report](/tools/khoj-ai-khoj/trust.md) | [trust report](/tools/plastic-labs-honcho/trust.md) |

## Decision facts: khoj

- **Pricing:** freemium - Khoj is free to use, but users may incur costs related to hosting and the LLMs they choose to integrate.
- **Requirements:** Min 4 GB RAM; Requires Docker; Khoj requires Docker for setup and operation.; Users must have a Python environment and the necessary dependencies installed.
- **Adopt for:** Khoj is a self-hosted AI assistant that supports integration with multiple LLMs, enabling users to build custom agents and conduct deep research using both web and local documents.
- **License detail:** Khoj is licensed under AGPL-3.0, which means it is free to use, modify, and distribute, but any derivative works must also be released under the same license.

## Decision facts: honcho

- **Adopt for:** Memory Library for Stateful Agents

## Choose when

### Choose khoj if…

- Pricing: Khoj is free to use, but users may incur costs related to hosting and the LLMs they choose to integrate..
- Requirements: Min 4 GB RAM; Requires Docker; Khoj requires Docker for setup and operation.; Users must have a Python environment and the necessary dependencies installed..
- Tags unique to khoj: agent, ai, assistant, chat.
- Also covers Developer Tools, Inference & Serving, Model Training.
- When you need a self-hosted solution for personalized research and automation that can integrate with a variety of LLMs, including GPT, Claude, Gemini, LLaMA, Qwen, and Mistral.

### Choose honcho if…

- Tags unique to honcho: agent-memory, ai-agents, embeddings, langchain.
- Requires managing long-term and contextual memory in AI agents for statefulness.
- More recently updated (last pushed Aug 18, 2026).

## When NOT to use khoj

- If you are looking for a cloud-based service without the need for self-hosting, Khoj may not be the best fit.
- Khoj might not be ideal if you are seeking a tool that does not support a wide range of LLMs and requires a more specialized integration.
- If your research and automation needs are simple and do not require deep integration with local documents or web sources, a more straightforward tool might be more appropriate.

## When NOT to use honcho

- Do not need complex SDK support or a customizable framework approach.
- Not interested in using stateful capabilities leveraging multiple APIs such as Gemini, Anthropic, and OpenAI.

## Common questions

### What is the difference between khoj and honcho?

khoj: Self-hostable AI second brain for personalized research and automation. honcho: Memory library for building stateful agents. See the comparison table for live GitHub stats and shared categories.

### When should I choose khoj over honcho?

Choose khoj over honcho when Pricing: Khoj is free to use, but users may incur costs related to hosting and the LLMs they choose to integrate.; Requirements: Min 4 GB RAM; Requires Docker; Khoj requires Docker for setup and operation.; Users must have a Python environment and the necessary dependencies installed.; Tags unique to khoj: agent, ai, assistant, chat; Also covers Developer Tools, Inference & Serving, Model Training; When you need a self-hosted solution for personalized research and automation that can integrate with a variety of LLMs, including GPT, Claude, Gemini, LLaMA, Qwen, and Mistral.

### When should I choose honcho over khoj?

Choose honcho over khoj when Tags unique to honcho: agent-memory, ai-agents, embeddings, langchain; Requires managing long-term and contextual memory in AI agents for statefulness; More recently updated (last pushed Aug 18, 2026).

### When should I avoid khoj?

If you are looking for a cloud-based service without the need for self-hosting, Khoj may not be the best fit. Khoj might not be ideal if you are seeking a tool that does not support a wide range of LLMs and requires a more specialized integration. If your research and automation needs are simple and do not require deep integration with local documents or web sources, a more straightforward tool might be more appropriate.

### When should I avoid honcho?

Do not need complex SDK support or a customizable framework approach. Not interested in using stateful capabilities leveraging multiple APIs such as Gemini, Anthropic, and OpenAI.

### Is khoj or honcho more popular on GitHub?

khoj has more GitHub stars (37,399 vs 6,703). Stars measure visibility, not whether either tool fits your constraints.

### Are khoj and honcho open source?

Yes - both are open-source projects on GitHub (khoj: AGPL-3.0, honcho: AGPL-3.0).

### Where can I find alternatives to khoj or honcho?

GraphCanon lists graph-backed alternatives at [khoj alternatives](/tools/khoj-ai-khoj/alternatives) and [honcho alternatives](/tools/plastic-labs-honcho/alternatives) ([khoj markdown twin](/tools/khoj-ai-khoj/alternatives.md), [honcho markdown twin](/tools/plastic-labs-honcho/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/khoj-ai-khoj-vs-plastic-labs-honcho.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, khoj or honcho?

khoj: Steady. honcho: 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 khoj and honcho?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [khoj trust report](/tools/khoj-ai-khoj/trust); [honcho trust report](/tools/plastic-labs-honcho/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=khoj-ai-khoj`](/api/graphcanon/graph?tool=khoj-ai-khoj)
- 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/_
