--- title: "keras vs inference" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/keras-team-keras-vs-xorbitsai-inference" tools: ["keras-team-keras", "xorbitsai-inference"] --- # keras vs inference *GraphCanon updated Jul 12, 2026* ## Verdict Pick keras when tags unique to keras: data-science, deep-learning, jax, machine-learning; pick inference when tags unique to inference: artificial-intelligence, chatglm, deployment, flan-t5. [keras](http://keras.io/) reports 64k GitHub stars, 20k forks, and 228 open issues, last pushed Jul 7, 2026. [inference](https://inference.readthedocs.io) has 9.4k stars, 846 forks, and 50 open issues, last pushed Jul 11, 2026. Figures are from public GitHub metadata via [keras's repository](https://github.com/keras-team/keras) and [inference's repository](https://github.com/xorbitsai/inference). | | [keras](/tools/keras-team-keras.md) | [inference](/tools/xorbitsai-inference.md) | | --- | --- | --- | | Tagline | Deep Learning for humans | Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source, speech, and multimodal models on cloud, on-prem, or your laptop — all through one unified, production-ready | | Stars | 64,191 | 9,423 | | Forks | 19,752 | 846 | | Open issues | 228 | 50 | | Language | Python | Python | | Adopt for | - | - | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Model Training | Inference & Serving, LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [keras](/tools/keras-team-keras.md) | [inference](/tools/xorbitsai-inference.md) | | --- | --- | --- | | Days since push | 4d | 0d | | Open issues (now) | 228 | 50 | | Security scan | No criticals | No lockfile | | Full report | [trust report](/tools/keras-team-keras/trust.md) | [trust report](/tools/xorbitsai-inference/trust.md) | ## Shared compatibility - **Python**: [keras](/tools/keras-team-keras.md) - Python runtime; [inference](/tools/xorbitsai-inference.md) - Python runtime ## Choose when ### Choose keras if… - Tags unique to keras: data-science, deep-learning, jax, machine-learning. - More GitHub stars (64k vs 9.4k) - visibility, not fit. ### Choose inference if… - Tags unique to inference: artificial-intelligence, chatglm, deployment, flan-t5. - Also covers Inference & Serving, LLM Frameworks. - More recently updated (last pushed Jul 11, 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 inference - Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. - 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. ## Common questions ### What is the difference between keras and inference? keras: Deep Learning for humans. inference: Swap GPT for any LLM by changing a single line of code. Xinference lets you run open-source, speech, and multimodal models on cloud, on-prem, or your laptop — all through one unified, production-ready. See the comparison table for live GitHub stats and shared categories. ### When should I choose keras over inference? Choose keras over inference when Tags unique to keras: data-science, deep-learning, jax, machine-learning; More GitHub stars (64k vs 9.4k) - visibility, not fit. ### When should I choose inference over keras? Choose inference over keras when Tags unique to inference: artificial-intelligence, chatglm, deployment, flan-t5; Also covers Inference & Serving, LLM Frameworks; More recently updated (last pushed Jul 11, 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 inference? Inference & Serving: Self-hosting rarely beats a hosted API on cost until you have steady, high-volume traffic. 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. ### Is keras or inference more popular on GitHub? keras has more GitHub stars (64,191 vs 9,423). Stars measure visibility, not whether either tool fits your constraints. ### Are keras and inference open source? Yes - both are open-source projects on GitHub (keras: Apache-2.0, inference: Apache-2.0). ### Where can I find alternatives to keras or inference? GraphCanon lists graph-backed alternatives at [keras alternatives](/tools/keras-team-keras/alternatives) and [inference alternatives](/tools/xorbitsai-inference/alternatives) ([keras markdown twin](/tools/keras-team-keras/alternatives.md), [inference markdown twin](/tools/xorbitsai-inference/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-xorbitsai-inference.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, keras or inference? keras: Very active. inference: 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 inference? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [keras trust report](/tools/keras-team-keras/trust); [inference trust report](/tools/xorbitsai-inference/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/_