Comparison
torchtune vs DeepLearningExamples
Verdict
Pick torchtune if a PyTorch-native post-training library focused on finetuning multimodal LLMs using state-of-the-art quantization techniques; pick DeepLearningExamples if curated facts for DeepLearningExamples, tailored to its unique features and offerings.
Markdown twin · torchtune alternatives · DeepLearningExamples alternatives
GraphCanon updated 1w
vs
Trust & integrity
| Signal | torchtune | DeepLearningExamples |
|---|---|---|
| Maintenance | Very active (0d since push) As of 2w · github_public_v1 | Dormant (734d since push) As of 1w · github_public_v1 |
| Provenance | Not a fork · Organization account As of 2w · github_public_v1 | Not a fork · Organization account As of 1w · github_public_v1 |
| OSV dependency advisories | No lockfile (source not queried) As of 1mo · osv@v1 | No lockfile (source not queried) As of 1mo · 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
- torchtune
- PyTorch native post-training library
- DeepLearningExamples
- State-of-the-Art Deep Learning scripts for various applications
Stars
- torchtune
- 5.8k
- DeepLearningExamples
- 15k
Forks
- torchtune
- 743
- DeepLearningExamples
- 3.4k
Open issues
- torchtune
- 455
- DeepLearningExamples
- 321
Language
- torchtune
- Python
- DeepLearningExamples
- Jupyter Notebook
Adopt for
- torchtune
- A PyTorch-native post-training library focused on finetuning multimodal LLMs using state-of-the-art quantization techniques.
- DeepLearningExamples
- Curated facts for DeepLearningExamples, tailored to its unique features and offerings.
Persona
- torchtune
- -
- DeepLearningExamples
- -
Runtime
- torchtune
- -
- DeepLearningExamples
- -
License
- torchtune
- BSD-3-Clause
- DeepLearningExamples
- -
Last pushed
- torchtune
- Aug 6, 2026
- DeepLearningExamples
- Aug 12, 2024
Categories
- torchtune
- Inference & Serving, Model Training
- DeepLearningExamples
- Inference & Serving, Model Training
Trust and health
Maintenance
- torchtune
- Very active (96%)
- DeepLearningExamples
- Dormant (18%)
Days since push
- torchtune
- 0d
- DeepLearningExamples
- 734d
Open issues (now)
- torchtune
- 455
- DeepLearningExamples
- 321
Stars delta
- torchtune
- Unknown
- DeepLearningExamples
- +14 (30d)
Open issues delta
- torchtune
- Unknown
- DeepLearningExamples
- -1 (30d)
Full report
- torchtune
- Trust report
- DeepLearningExamples
- Trust report
Choose torchtune if…
- torchtune is primarily Python; DeepLearningExamples is Jupyter Notebook.
- Tags unique to torchtune: multimodal-llms, post-training, pytorch, quantization techniques.
- - When you are working with the latest stable or preview nightly versions of PyTorch and need advanced finetuning for multimodal large language models (LLMs).
When NOT to use torchtune
- - If you rely on a fixed, older version of PyTorch as Torchtune only supports the latest stable and preview nightly versions.
- - For scenarios where custom or non-PyTorch-native optimization methods are preferred over torchao’s quantization techniques.
Choose DeepLearningExamples if…
- DeepLearningExamples is primarily Jupyter Notebook; torchtune is Python.
- Tags unique to DeepLearningExamples: computer-vision, deep-learning, drug-discovery, forecasting.
- The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance.
When NOT to use DeepLearningExamples
- Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores.
- If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n
Explore
Sources
Every stat on this page traces to a dated GitHub sync, license file, enrichment field, or trust scan.
- GitHub stars (meta-pytorch/torchtune) · observed Aug 7, 2026
- GitHub forks (meta-pytorch/torchtune) · observed Aug 7, 2026
- Last push (meta-pytorch/torchtune) · observed Aug 6, 2026
- License file (BSD-3-Clause) · observed Aug 7, 2026
- Decision facts (enrichment) · observed Jul 12, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
- GitHub stars (NVIDIA/DeepLearningExamples) · observed Aug 17, 2026
- GitHub forks (NVIDIA/DeepLearningExamples) · observed Aug 17, 2026
- Last push (NVIDIA/DeepLearningExamples) · observed Aug 12, 2024
- License file (unknown) · observed Aug 17, 2026
- Decision facts (enrichment) · observed Jul 11, 2026
- Trust scan (lockfile / OSV) · observed Jul 11, 2026
GitHub stars on cards: torchtune 5.8k · DeepLearningExamples 15k (synced Aug 7, 2026).
Common questions
- What is the difference between torchtune and DeepLearningExamples?
- torchtune: PyTorch native post-training library. DeepLearningExamples: State-of-the-Art Deep Learning scripts for various applications. See the comparison table for live GitHub stats and shared categories.
- When should I choose torchtune over DeepLearningExamples?
- Choose torchtune over DeepLearningExamples when torchtune is primarily Python; DeepLearningExamples is Jupyter Notebook; Tags unique to torchtune: multimodal-llms, post-training, pytorch, quantization techniques; - When you are working with the latest stable or preview nightly versions of PyTorch and need advanced finetuning for multimodal large language models (LLMs).
- When should I choose DeepLearningExamples over torchtune?
- Choose DeepLearningExamples over torchtune when DeepLearningExamples is primarily Jupyter Notebook; torchtune is Python; Tags unique to DeepLearningExamples: computer-vision, deep-learning, drug-discovery, forecasting; The NVIDIA GPU Cloud (NGC) Container Registry that integrates with this tool offers the latest updates every month along with rigorous quality assurance.
- When should I avoid torchtune?
- - If you rely on a fixed, older version of PyTorch as Torchtune only supports the latest stable and preview nightly versions. - For scenarios where custom or non-PyTorch-native optimization methods are preferred over torchao’s quantization techniques.
- When should I avoid DeepLearningExamples?
- Avoid using DeepLearningExamples if you do not have access to NVIDIA GPUs, as it is heavily optimized for these specific hardware configurations to provide maximum utilization of Tensor Cores. If your project requires frameworks that are less common (e.g., MXNet or PaddlePaddle) without the same level of support as PyTorch and TensorFlow on this platform, consider other repositories that n
- Is torchtune or DeepLearningExamples more popular on GitHub?
- DeepLearningExamples has more GitHub stars (14,844 vs 5,793). Stars measure visibility, not whether either tool fits your constraints.
- Are torchtune and DeepLearningExamples open source?
- Yes - both are open-source projects on GitHub.
- Where can I find alternatives to torchtune or DeepLearningExamples?
- GraphCanon lists graph-backed alternatives at torchtune alternatives and DeepLearningExamples alternatives (torchtune markdown twin, DeepLearningExamples 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, torchtune or DeepLearningExamples?
- torchtune: Very active. DeepLearningExamples: 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 torchtune and DeepLearningExamples?
- GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: torchtune trust report; DeepLearningExamples trust report.