--- title: "keras vs torchtune" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/keras-team-keras-vs-meta-pytorch-torchtune" tools: ["keras-team-keras", "meta-pytorch-torchtune"] --- # keras vs torchtune *GraphCanon updated Jul 12, 2026* ## Verdict Pick keras when license: keras is Apache-2.0, torchtune is BSD-3-Clause; pick torchtune when license: torchtune is BSD-3-Clause, keras is Apache-2.0. [keras](http://keras.io/) reports 64k GitHub stars, 20k forks, and 228 open issues, last pushed Jul 7, 2026. [torchtune](https://pytorch.org/torchtune/main/) has 5.8k stars, 735 forks, and 445 open issues, last pushed Jul 10, 2026. Figures are from public GitHub metadata via [keras's repository](https://github.com/keras-team/keras) and [torchtune's repository](https://github.com/meta-pytorch/torchtune). | | [keras](/tools/keras-team-keras.md) | [torchtune](/tools/meta-pytorch-torchtune.md) | | --- | --- | --- | | Tagline | Deep Learning for humans | PyTorch native post-training library | | Stars | 64,191 | 5,782 | | Forks | 19,752 | 735 | | Open issues | 228 | 445 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | BSD-3-Clause | | Categories | Model Training | LLM Frameworks, Model Training, Inference & Serving | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [keras](/tools/keras-team-keras.md) | [torchtune](/tools/meta-pytorch-torchtune.md) | | --- | --- | --- | | Days since push | 4d | 0d | | Open issues (now) | 228 | 445 | | Security scan | No criticals | No lockfile | | Full report | [trust report](/tools/keras-team-keras/trust.md) | [trust report](/tools/meta-pytorch-torchtune/trust.md) | ## Shared compatibility - **Python**: [keras](/tools/keras-team-keras.md) - Python runtime; [torchtune](/tools/meta-pytorch-torchtune.md) - Python runtime ## Choose when ### Choose keras if… - License: keras is Apache-2.0, torchtune is BSD-3-Clause. - Tags unique to keras: data-science, neural-networks, deep-learning, machine-learning. - More GitHub stars (64k vs 5.8k) - visibility, not fit. ### Choose torchtune if… - License: torchtune is BSD-3-Clause, keras is Apache-2.0. - Also covers LLM Frameworks, Inference & Serving. - More recently updated (last pushed Jul 10, 2026). ## When NOT to use keras - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ## When NOT to use torchtune - LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. - Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ## Common questions ### What is the difference between keras and torchtune? keras: Deep Learning for humans. torchtune: PyTorch native post-training library. See the comparison table for live GitHub stats and shared categories. ### When should I choose keras over torchtune? Choose keras over torchtune when License: keras is Apache-2.0, torchtune is BSD-3-Clause; Tags unique to keras: data-science, neural-networks, deep-learning, machine-learning; More GitHub stars (64k vs 5.8k) - visibility, not fit. ### When should I choose torchtune over keras? Choose torchtune over keras when License: torchtune is BSD-3-Clause, keras is Apache-2.0; Also covers LLM Frameworks, Inference & Serving; More recently updated (last pushed Jul 10, 2026). ### When should I avoid keras? Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. ### When should I avoid torchtune? LLM Frameworks: Avoid a framework for a single prompt-and-retrieve call; the abstraction can cost more than it saves. Model Training: Try prompting and RAG first; fine-tuning is the answer to style/format, not missing knowledge. Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. ### Is keras or torchtune more popular on GitHub? keras has more GitHub stars (64,191 vs 5,782). Stars measure visibility, not whether either tool fits your constraints. ### Are keras and torchtune open source? Yes - both are open-source projects on GitHub (keras: Apache-2.0, torchtune: BSD-3-Clause). ### Where can I find alternatives to keras or torchtune? GraphCanon lists graph-backed alternatives at [keras alternatives](/tools/keras-team-keras/alternatives) and [torchtune alternatives](/tools/meta-pytorch-torchtune/alternatives) ([keras markdown twin](/tools/keras-team-keras/alternatives.md), [torchtune markdown twin](/tools/meta-pytorch-torchtune/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/keras-team-keras-vs-meta-pytorch-torchtune.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, keras or torchtune? keras: Very active. torchtune: 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 keras and torchtune? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [keras trust report](/tools/keras-team-keras/trust); [torchtune trust report](/tools/meta-pytorch-torchtune/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=keras-team-keras`](/api/graphcanon/graph?tool=keras-team-keras) - 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/_