---
title: "gpt_academic vs Auto-claude-code-research-in-sleep"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/binary-husky-gpt-academic-vs-wanshuiyin-auto-claude-code-research-in-sleep"
tools: ["binary-husky-gpt-academic", "wanshuiyin-auto-claude-code-research-in-sleep"]
---

# gpt_academic vs Auto-claude-code-research-in-sleep

*GraphCanon updated Jul 11, 2026*

## Verdict

Pick gpt_academic when license: gpt_academic is GPL-3.0, Auto-claude-code-research-in-sleep is MIT; pick Auto-claude-code-research-in-sleep when license: Auto-claude-code-research-in-sleep is MIT, gpt_academic is GPL-3.0.

[gpt_academic](https://github.com/binary-husky/gpt_academic/wiki/online) reports 71k GitHub stars, 8.3k forks, and 329 open issues, last pushed Jan 25, 2026. [Auto-claude-code-research-in-sleep](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep) has 13k stars, 1.2k forks, and 53 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [gpt_academic's repository](https://github.com/binary-husky/gpt_academic) and [Auto-claude-code-research-in-sleep's repository](https://github.com/wanshuiyin/Auto-claude-code-research-in-sleep).

| | [gpt_academic](/tools/binary-husky-gpt-academic.md) | [Auto-claude-code-research-in-sleep](/tools/wanshuiyin-auto-claude-code-research-in-sleep.md) |
| --- | --- | --- |
| Tagline | 提供实用化交互接口，优化论文阅读/润色/写作体验 | ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works wi |
| Stars | 71,056 | 13,264 |
| Forks | 8,350 | 1,193 |
| Open issues | 329 | 53 |
| Language | Python | Python |
| Adopt for | gpt_academic专为增强与GPT/GLM等大语言模型的交互，优化论文写作、润色和阅读体验。它支持自定义模块、多种LLM接入，并且拥有PDF/LaTeX文档处理功能。 | - |
| Persona | - | - |
| Runtime | - | - |
| License | 使用GPL-3.0许可证，这意味着你可以自由地运行、学习、分享和修改这个软件，但是如果你在分发含gpt_academic的程序时，你必须公开整个程序源代码且采用同为GPL许可证 | MIT |
| Categories | LLM Frameworks, Developer Tools | AI Agents, LLM Frameworks, Developer Tools |

## Trust and health

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

| | [gpt_academic](/tools/binary-husky-gpt-academic.md) | [Auto-claude-code-research-in-sleep](/tools/wanshuiyin-auto-claude-code-research-in-sleep.md) |
| --- | --- | --- |
| Maintenance | Slowing (36%) | Very active (96%) |
| Days since push | 166d | 0d |
| Open issues (now) | 329 | 53 |
| Security scan | No lockfile | No MCP manifest |
| Full report | [trust report](/tools/binary-husky-gpt-academic/trust.md) | [trust report](/tools/wanshuiyin-auto-claude-code-research-in-sleep/trust.md) |

## Decision facts: gpt_academic

- **Pricing:** freemium
- **Requirements:** Min 8 GB RAM; 依赖Python环境
- **Adopt for:** gpt_academic专为增强与GPT/GLM等大语言模型的交互，优化论文写作、润色和阅读体验。它支持自定义模块、多种LLM接入，并且拥有PDF/LaTeX文档处理功能。
- **License detail:** 使用GPL-3.0许可证，这意味着你可以自由地运行、学习、分享和修改这个软件，但是如果你在分发含gpt_academic的程序时，你必须公开整个程序源代码且采用同为GPL许可证

## Choose when

### Choose gpt_academic if…

- License: gpt_academic is GPL-3.0, Auto-claude-code-research-in-sleep is MIT.
- Requirements: Min 8 GB RAM; 依赖Python环境.
- Tags unique to gpt_academic: large-language-models, academic, chatglm-6b, gpt-4.
- gpt_academic ships Docker support for self-hosted deployment.
- 需要使用GPT或GLM大语言模型进行高效的学术论文相关任务时

### Choose Auto-claude-code-research-in-sleep if…

- License: Auto-claude-code-research-in-sleep is MIT, gpt_academic is GPL-3.0.
- Tags unique to Auto-claude-code-research-in-sleep: claude-code-skills, aris, autonomous-agent, ai-research.
- Also covers AI Agents.

## When NOT to use gpt_academic

- 主要任务不是围绕论文和学术资料处理时, 特别是不涉及到大语言模型的实际应用情况
- 不需要自定义快捷按钮与高级功能插件，且对通用的大语言模型交互界面已经满意
- 侧重于文本创作以外的开发流程优化（例如：性能调优或低层级编程实现）
- 只需要基本的数据翻译或总结工具，无需连接多个大语言模型来提升任务效率

## When NOT to use Auto-claude-code-research-in-sleep

- AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism.
- LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves.
- Developer Tools: A gateway is overkill when you're pinned to a single provider and model.

## Common questions

### What is the difference between gpt_academic and Auto-claude-code-research-in-sleep?

gpt_academic: 提供实用化交互接口，优化论文阅读/润色/写作体验. Auto-claude-code-research-in-sleep: ARIS ⚔️ (Auto-Research-In-Sleep) — Lightweight Markdown-only skills for autonomous ML research: cross-model review loops, idea discovery, and experiment automation. No framework, no lock-in — works wi. See the comparison table for live GitHub stats and shared categories.

### When should I choose gpt_academic over Auto-claude-code-research-in-sleep?

Choose gpt_academic over Auto-claude-code-research-in-sleep when License: gpt_academic is GPL-3.0, Auto-claude-code-research-in-sleep is MIT; Requirements: Min 8 GB RAM; 依赖Python环境; Tags unique to gpt_academic: large-language-models, academic, chatglm-6b, gpt-4; gpt_academic ships Docker support for self-hosted deployment; 需要使用GPT或GLM大语言模型进行高效的学术论文相关任务时.

### When should I choose Auto-claude-code-research-in-sleep over gpt_academic?

Choose Auto-claude-code-research-in-sleep over gpt_academic when License: Auto-claude-code-research-in-sleep is MIT, gpt_academic is GPL-3.0; Tags unique to Auto-claude-code-research-in-sleep: claude-code-skills, aris, autonomous-agent, ai-research; Also covers AI Agents.

### When should I avoid gpt_academic?

主要任务不是围绕论文和学术资料处理时, 特别是不涉及到大语言模型的实际应用情况 不需要自定义快捷按钮与高级功能插件，且对通用的大语言模型交互界面已经满意 侧重于文本创作以外的开发流程优化（例如：性能调优或低层级编程实现） 只需要基本的数据翻译或总结工具，无需连接多个大语言模型来提升任务效率

### When should I avoid Auto-claude-code-research-in-sleep?

AI Agents: Don't use an agent loop when a deterministic workflow would do; agents add latency, cost, and non-determinism. LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Developer Tools: A gateway is overkill when you're pinned to a single provider and model.

### Is gpt_academic or Auto-claude-code-research-in-sleep more popular on GitHub?

gpt_academic has more GitHub stars (71,056 vs 13,264). Stars measure visibility, not whether either tool fits your constraints.

### Are gpt_academic and Auto-claude-code-research-in-sleep open source?

Yes - both are open-source projects on GitHub (gpt_academic: GPL-3.0, Auto-claude-code-research-in-sleep: MIT).

### Where can I find alternatives to gpt_academic or Auto-claude-code-research-in-sleep?

GraphCanon lists graph-backed alternatives at [gpt_academic alternatives](/tools/binary-husky-gpt-academic/alternatives) and [Auto-claude-code-research-in-sleep alternatives](/tools/wanshuiyin-auto-claude-code-research-in-sleep/alternatives) ([gpt_academic markdown twin](/tools/binary-husky-gpt-academic/alternatives.md), [Auto-claude-code-research-in-sleep markdown twin](/tools/wanshuiyin-auto-claude-code-research-in-sleep/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/binary-husky-gpt-academic-vs-wanshuiyin-auto-claude-code-research-in-sleep.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, gpt_academic or Auto-claude-code-research-in-sleep?

gpt_academic: Slowing. Auto-claude-code-research-in-sleep: 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 gpt_academic and Auto-claude-code-research-in-sleep?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [gpt_academic trust report](/tools/binary-husky-gpt-academic/trust); [Auto-claude-code-research-in-sleep trust report](/tools/wanshuiyin-auto-claude-code-research-in-sleep/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=binary-husky-gpt-academic`](/api/graphcanon/graph?tool=binary-husky-gpt-academic)
- 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/_
