---
title: "DeepSeek-R1 vs CodeGen"
type: "comparison"
canonical_url: "https://www.graphcanon.com/compare/deepseek-ai-deepseek-r1-vs-salesforce-codegen"
tools: ["deepseek-ai-deepseek-r1", "salesforce-codegen"]
---

# DeepSeek-R1 vs CodeGen

*GraphCanon updated Jul 12, 2026*

## Verdict

Pick DeepSeek-R1 if deepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use; pick CodeGen if codeGen is a series of open-source large language models designed for program synthesis. Trained on TPUs, CodeGen offers several versions with varying capabilities from basic code generation to advanced infill sampling.

[DeepSeek-R1](https://github.com/deepseek-ai/DeepSeek-R1) reports 92k GitHub stars, 12k forks, and 45 open issues, last pushed Jun 27, 2025. [CodeGen](https://github.com/salesforce/CodeGen) has 5.2k stars, 423 forks, and 48 open issues, last pushed Jun 2, 2026. Figures are from public GitHub metadata via [DeepSeek-R1's repository](https://github.com/deepseek-ai/DeepSeek-R1) and [CodeGen's repository](https://github.com/salesforce/CodeGen).

| | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) | [CodeGen](/tools/salesforce-codegen.md) |
| --- | --- | --- |
| Tagline | Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses. | Family of open-source models for program synthesis. |
| Stars | 91,991 | 5,177 |
| Forks | 11,711 | 423 |
| Open issues | 45 | 48 |
| Language | - | Python |
| Adopt for | DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use. | CodeGen is a series of open-source large language models designed for program synthesis. Trained on TPUs, CodeGen offers several versions with varying capabilities from basic code generation to advanced infill sampling. |
| Persona | - | - |
| Runtime | - | - |
| License | MIT | Apache-2.0 |
| Categories | LLM Frameworks, Model Training | LLM Frameworks, Model Training |

## Trust and health

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

| | [DeepSeek-R1](/tools/deepseek-ai-deepseek-r1.md) | [CodeGen](/tools/salesforce-codegen.md) |
| --- | --- | --- |
| Maintenance | Dormant (18%) | Steady (60%) |
| Days since push | 379d | 39d |
| Open issues (now) | 45 | 48 |
| Full report | [trust report](/tools/deepseek-ai-deepseek-r1/trust.md) | [trust report](/tools/salesforce-codegen/trust.md) |

## 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.

## Decision facts: CodeGen

- **Adopt for:** CodeGen is a series of open-source large language models designed for program synthesis. Trained on TPUs, CodeGen offers several versions with varying capabilities from basic code generation to advanced infill sampling.

## Choose when

### Choose DeepSeek-R1 if…

- License: DeepSeek-R1 is MIT, CodeGen is Apache-2.0.
- 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.

### Choose CodeGen if…

- License: CodeGen is Apache-2.0, DeepSeek-R1 is MIT.
- Tags unique to CodeGen: codex, generativemodel, languagemodel, llm.
- When you require high-performance model training and code generation that matches or exceeds the performance of OpenAI Codex on specific tasks

## 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.

## When NOT to use CodeGen

- In scenarios where the model's primary use is not centered around code generation or program synthesis, as its specialized training may limit its effectiveness for other types of generative tasks
- If your project strictly requires a smaller memory footprint or simpler deployment because advanced models like CodeGen2.5 require significant computational resources and setup

## Common questions

### What is the difference between DeepSeek-R1 and CodeGen?

DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. CodeGen: Family of open-source models for program synthesis.. See the comparison table for live GitHub stats and shared categories.

### When should I choose DeepSeek-R1 over CodeGen?

Choose DeepSeek-R1 over CodeGen when License: DeepSeek-R1 is MIT, CodeGen is Apache-2.0; 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 choose CodeGen over DeepSeek-R1?

Choose CodeGen over DeepSeek-R1 when License: CodeGen is Apache-2.0, DeepSeek-R1 is MIT; Tags unique to CodeGen: codex, generativemodel, languagemodel, llm; When you require high-performance model training and code generation that matches or exceeds the performance of OpenAI Codex on specific tasks.

### 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.

### When should I avoid CodeGen?

In scenarios where the model's primary use is not centered around code generation or program synthesis, as its specialized training may limit its effectiveness for other types of generative tasks If your project strictly requires a smaller memory footprint or simpler deployment because advanced models like CodeGen2.5 require significant computational resources and setup

### Is DeepSeek-R1 or CodeGen more popular on GitHub?

DeepSeek-R1 has more GitHub stars (91,991 vs 5,177). Stars measure visibility, not whether either tool fits your constraints.

### Are DeepSeek-R1 and CodeGen open source?

Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, CodeGen: Apache-2.0).

### Where can I find alternatives to DeepSeek-R1 or CodeGen?

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

### Which is better maintained, DeepSeek-R1 or CodeGen?

DeepSeek-R1: Dormant. CodeGen: Steady. 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 DeepSeek-R1 and CodeGen?

GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [DeepSeek-R1 trust report](/tools/deepseek-ai-deepseek-r1/trust); [CodeGen trust report](/tools/salesforce-codegen/trust).

---

**Machine-readable endpoints**

- JSON: [`/api/graphcanon/graph?tool=deepseek-ai-deepseek-r1`](/api/graphcanon/graph?tool=deepseek-ai-deepseek-r1)
- 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/_