Comparison
DeepSeek-R1 vs MegEngine
Verdict
Pick DeepSeek-R1 if deepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use; pick MegEngine if megEngine是一个快速、可扩展且支持自动求导的深度学习框架，适用于多种平台和环境。它主要用C++编写，并以Apache-2.0许可分发。.
Markdown twin · DeepSeek-R1 alternatives · MegEngine alternatives
GraphCanon updated Oct 10, 2026
9views this month
vs
Trust & integrity
| Signal | DeepSeek-R1 | MegEngine |
|---|---|---|
| Maintenance | Dormant (469d since push) As of Oct 10, 2026 · github_public_v1 | Dormant (701d since push) As of Sep 26, 2026 · github_public_v1 |
| Provenance | Not a fork · Organization account As of Oct 10, 2026 · github_public_v1 | Not a fork · Organization account As of Sep 26, 2026 · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 | No lockfile (source not queried) As of Jul 11, 2026 · osv@v1 |
| deps.dev advisories | Not queried deps.dev@v1 | Not queried deps.dev@v1 |
| OpenSSF Scorecard | Not queried openssf-scorecard@v1 | Not queried openssf-scorecard@v1 |
Tagline
- DeepSeek-R1
- Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.
- MegEngine
- 一个快速、可拓展、易于使用且支持自动求导的深度学习框架
Stars
- DeepSeek-R1
- 92k
- MegEngine
- 4.8k
Forks
- DeepSeek-R1
- 12k
- MegEngine
- 544
Open issues
- DeepSeek-R1
- 42
- MegEngine
- 173
Language
- DeepSeek-R1
- -
- MegEngine
- C++
Adopt for
- DeepSeek-R1
- DeepSeek-R1 provides a set of distilled LLMs from Qwen and LLaMA series that support commercial use.
- MegEngine
- MegEngine是一个快速、可扩展且支持自动求导的深度学习框架，适用于多种平台和环境。它主要用C++编写，并以Apache-2.0许可分发。
Persona
- DeepSeek-R1
- -
- MegEngine
- -
Runtime
- DeepSeek-R1
- -
- MegEngine
- -
License
- DeepSeek-R1
- MIT
- MegEngine
- Apache-2.0
Last pushed
- DeepSeek-R1
- Jun 27, 2025
- MegEngine
- Oct 24, 2024
Categories
- DeepSeek-R1
- LLM Frameworks, Model Training
- MegEngine
- Model Training
Trust and health
Days since push
- DeepSeek-R1
- 469d
- MegEngine
- 701d
Open issues (now)
- DeepSeek-R1
- 42
- MegEngine
- 173
Stars delta
- DeepSeek-R1
- -118 (30d)
- MegEngine
- 0 (30d)
Open issues delta
- DeepSeek-R1
- +9 (30d)
- MegEngine
- 0 (30d)
Full report
- DeepSeek-R1
- Trust report
- MegEngine
- Trust report
Choose DeepSeek-R1 if…
- License: DeepSeek-R1 is MIT, MegEngine 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.
- Also covers LLM Frameworks.
- 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 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.
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (deepseek-ai/DeepSeek-R1) · observed Oct 10, 2026
- GitHub forks (deepseek-ai/DeepSeek-R1) · observed Oct 10, 2026
- Last push (deepseek-ai/DeepSeek-R1) · observed Jun 27, 2025
- License file (MIT) · observed Oct 10, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (MegEngine/MegEngine) · observed Sep 26, 2026
- GitHub forks (MegEngine/MegEngine) · observed Sep 26, 2026
- Last push (MegEngine/MegEngine) · observed Oct 24, 2024
- License file (Apache-2.0) · observed Sep 26, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: DeepSeek-R1 92k · MegEngine 4.8k (synced Oct 10, 2026).
Common questions
- What is the difference between DeepSeek-R1 and MegEngine?
- DeepSeek-R1: Repository contains distilled LLM models derived from Qwen and LLaMA series for various commercial uses.. MegEngine: 一个快速、可拓展、易于使用且支持自动求导的深度学习框架. See the comparison table for live GitHub stats and shared categories.
- When should I choose DeepSeek-R1 over MegEngine?
- Choose DeepSeek-R1 over MegEngine when License: DeepSeek-R1 is MIT, MegEngine 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; Also covers LLM Frameworks; 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 MegEngine over DeepSeek-R1?
- Choose MegEngine over DeepSeek-R1 when License: MegEngine is Apache-2.0, DeepSeek-R1 is MIT; Tags unique to MegEngine: autograd, deep-learning, gpu, machine-learning; - 当您需要在Linux、Windows（WSL或直接）、MacOS（仅限CPU）和Android设备（仅限CPU）上使用Python进行深度学习项目时.
- 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 MegEngine?
- - Python3.63.9，，MegEnginePython
- Is DeepSeek-R1 or MegEngine more popular on GitHub?
- DeepSeek-R1 has more GitHub stars (91,902 vs 4,809). Stars measure visibility, not whether either tool fits your constraints.
- Are DeepSeek-R1 and MegEngine open source?
- Yes - both are open-source projects on GitHub (DeepSeek-R1: MIT, MegEngine: Apache-2.0).
- Where can I find alternatives to DeepSeek-R1 or MegEngine?
- GraphCanon lists graph-backed alternatives at DeepSeek-R1 alternatives and MegEngine alternatives (DeepSeek-R1 markdown twin, MegEngine markdown twin), 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 mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers.
- Which is better maintained, DeepSeek-R1 or MegEngine?
- DeepSeek-R1: Dormant. MegEngine: 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 DeepSeek-R1 and MegEngine?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: DeepSeek-R1 trust report; MegEngine trust report.