---
title: "LLM-RL-Visualized vs DeepSeek-R1"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/changyeyu-llm-rl-visualized-vs-deepseek-ai-deepseek-r1"
tools: ["changyeyu-llm-rl-visualized", "deepseek-ai-deepseek-r1"]
---

# LLM-RL-Visualized vs DeepSeek-R1

*GraphCanon updated Aug 8, 2026*

## Verdict

Pick LLM-RL-Visualized if lLM-RL-Visualized offers over 100 diagrams for understanding LLM, RL algorithms, and training methods including SFT, DPO and optimization techniques; pick DeepSeek-R1 if deepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use.

[LLM-RL-Visualized](https://book.douban.com/subject/37331056/) reports 4.8k GitHub stars, 455 forks, and 3 open issues, last pushed Jul 27, 2026. [DeepSeek-R1](https://github.com/deepseek-ai/DeepSeek-R1) has 92k stars, 12k forks, and 38 open issues, last pushed Jun 27, 2025. Figures are from public GitHub metadata via [LLM-RL-Visualized's repository](https://github.com/changyeyu/LLM-RL-Visualized) and [DeepSeek-R1's repository](https://github.com/deepseek-ai/DeepSeek-R1).

| | [LLM-RL-Visualized](/tools/changyeyu-llm-rl-visualized.md) | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) |
| --- | --- | --- |
| Tagline | Provides over 100 diagrams illustrating LLM and RL algorithms | Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses. |
| Stars | 4,750 | 91,982 |
| Forks | 455 | 11,706 |
| Open issues | 3 | 38 |
| Language | Python | - |
| Adopt for | LLM-RL-Visualized offers over 100 diagrams for understanding LLM, RL algorithms, and training methods including SFT, DPO and optimization techniques. | DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use. |
| Persona | - | - |
| Runtime | - | - |
| License | Other | MIT |
| Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training |

## Trust and health

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

| | [LLM-RL-Visualized](/tools/changyeyu-llm-rl-visualized.md) | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) |
| --- | --- | --- |
| Maintenance | Active (82%) | Dormant (18%) |
| Days since push | 11d | 405d |
| Open issues (now) | 3 | 38 |
| Owner type | User | Organization |
| Full report | [trust report](/tools/changyeyu-llm-rl-visualized/trust.md) | [trust report](/tools/deepseek-ai-deepseek-r1/trust.md) |

## Decision facts: LLM-RL-Visualized

- **Adopt for:** LLM-RL-Visualized offers over 100 diagrams for understanding LLM, RL algorithms, and training methods including SFT, DPO and optimization techniques.

## Decision facts: DeepSeek-R1

- **Pricing:** freemium - The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository.
- **Requirements:** Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs.
- **Adopt for:** DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use.

## Choose when

### Choose LLM-RL-Visualized if…

- License: LLM-RL-Visualized is Other, DeepSeek-R1 is MIT.
- Tags unique to LLM-RL-Visualized: ai, algorithm, deep-learning, llm.
- When detailed visual explanations of LLM and RL algorithms are needed

### Choose DeepSeek-R1 if…

- License: DeepSeek-R1 is MIT, LLM-RL-Visualized is Other.
- Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository..
- Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs..
- Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit-license.
- When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics.

## When NOT to use LLM-RL-Visualized

- If looking for executable code or tools rather than diagrams and visual explanations alone
- For datasets or large-scale experimental setups that require more interactive coding environments

## When NOT to use DeepSeek-R1

- Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments.
- If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series.

## Common questions

### What is the difference between LLM-RL-Visualized and DeepSeek-R1?

LLM-RL-Visualized: Provides over 100 diagrams illustrating LLM and RL algorithms. DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. See the comparison table for live GitHub stats and shared categories.

### When should I choose LLM-RL-Visualized over DeepSeek-R1?

Choose LLM-RL-Visualized over DeepSeek-R1 when License: LLM-RL-Visualized is Other, DeepSeek-R1 is MIT; Tags unique to LLM-RL-Visualized: ai, algorithm, deep-learning, llm; When detailed visual explanations of LLM and RL algorithms are needed.

### When should I choose DeepSeek-R1 over LLM-RL-Visualized?

Choose DeepSeek-R1 over LLM-RL-Visualized when License: DeepSeek-R1 is MIT, LLM-RL-Visualized is Other; Pricing: The repository allows for commercial use under the MIT License or respective original licenses with no explicit monetary costs outlined in the repository.; Requirements: Min 4 GB RAM; This is a rough estimate based on common model requirements. Specific models within DeepSeek-R1 may have different resource needs.; Tags unique to DeepSeek-R1: commercial use, derived models, distilled models, mit-license; When you need to work with pre-trained models derived specifically from the Qwen-2.5 and Llama3.x series, benefiting from their unique characteristics.

### When should I avoid LLM-RL-Visualized?

If looking for executable code or tools rather than diagrams and visual explanations alone For datasets or large-scale experimental setups that require more interactive coding environments

### When should I avoid DeepSeek-R1?

Avoid if you need foundational models rather than distilled versions, as DeepSeek-R1 specializes in providing smaller, more efficient models suitable for resource-constrained environments. If your project is tightly regulated or requires models from a different lineage, as DeepSeek-R1 exclusively provides derivatives of Qwen and LLaMA series.

### Is LLM-RL-Visualized or DeepSeek-R1 more popular on GitHub?

DeepSeek-R1 has more GitHub stars (91,982 vs 4,750). Stars measure visibility, not whether either tool fits your constraints.

### Are LLM-RL-Visualized and DeepSeek-R1 open source?

Yes - both are open-source projects on GitHub (LLM-RL-Visualized: Other, DeepSeek-R1: MIT).

### Where can I find alternatives to LLM-RL-Visualized or DeepSeek-R1?

GraphCanon lists graph-backed alternatives at [LLM-RL-Visualized alternatives](/tools/changyeyu-llm-rl-visualized/alternatives) and [DeepSeek-R1 alternatives](/tools/deepseek-ai-deepseek-r1/alternatives) ([LLM-RL-Visualized markdown twin](/tools/changyeyu-llm-rl-visualized/alternatives.md), [DeepSeek-R1 markdown twin](/tools/deepseek-ai-deepseek-r1/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/changyeyu-llm-rl-visualized-vs-deepseek-ai-deepseek-r1.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.

### Which is better maintained, LLM-RL-Visualized or DeepSeek-R1?

LLM-RL-Visualized: Active. DeepSeek-R1: Dormant. 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-RL-Visualized and DeepSeek-R1?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [LLM-RL-Visualized trust report](/tools/changyeyu-llm-rl-visualized/trust); [DeepSeek-R1 trust report](/tools/deepseek-ai-deepseek-r1/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=changyeyu-llm-rl-visualized`](/api/graphcanon/graph?tool=changyeyu-llm-rl-visualized)
- 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/_