--- title: "mlx-tune vs SPIN" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/arahim3-mlx-tune-vs-uclaml-spin" tools: ["arahim3-mlx-tune", "uclaml-spin"] --- # mlx-tune vs SPIN *GraphCanon updated Aug 24, 2026* ## Verdict Pick mlx-tune if mlx-tune targets Mac users with Apple Silicon for fine-tuning LLMs across SFT, RLHP, GRPO, vision, TTS, STT, embeddings, and OCR using tools compatible with the UnSloth API; pick SPIN if sPIN is specialized for self-play fine-tuning in large language models through deep learning. [mlx-tune](https://arahim3.github.io/mlx-tune/) reports 1.4k GitHub stars, 88 forks, and 11 open issues, last pushed Jun 23, 2026. [SPIN](https://uclaml.github.io/SPIN/) has 1.3k stars, 106 forks, and 24 open issues, last pushed May 8, 2024. Figures are from public GitHub metadata via [mlx-tune's repository](https://github.com/ARahim3/mlx-tune) and [SPIN's repository](https://github.com/uclaml/SPIN). | | [mlx-tune](/tools/arahim3-mlx-tune.md) | [SPIN](/tools/uclaml-spin.md) | | --- | --- | --- | | Tagline | Fine-tune LLMs on your Mac with Apple Silicon for various tasks including SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR. | Official implementation of Self-Play Fine-Tuning | | Stars | 1,372 | 1,254 | | Forks | 88 | 106 | | Open issues | 11 | 24 | | Language | Python | Python | | Adopt for | mlx-tune targets Mac users with Apple Silicon for fine-tuning LLMs across SFT, RLHP, GRPO, vision, TTS, STT, embeddings, and OCR using tools compatible with the UnSloth API. | SPIN is specialized for self-play fine-tuning in large language models through deep learning. | | Persona | - | - | | Runtime | - | - | | License | Apache-2.0 | Apache-2.0 | | Categories | Computer Vision, LLM Frameworks, Model Training, Speech & Audio | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [mlx-tune](/tools/arahim3-mlx-tune.md) | [SPIN](/tools/uclaml-spin.md) | | --- | --- | --- | | Maintenance | Steady (60%) | Dormant (18%) | | Days since push | 36d | 837d | | Open issues (now) | 11 | 24 | | Stars delta | Unknown | +6 (30d) | | Open issues delta | Unknown | 0 (30d) | | Full report | [trust report](/tools/arahim3-mlx-tune/trust.md) | [trust report](/tools/uclaml-spin/trust.md) | ## Decision facts: mlx-tune - **Adopt for:** mlx-tune targets Mac users with Apple Silicon for fine-tuning LLMs across SFT, RLHP, GRPO, vision, TTS, STT, embeddings, and OCR using tools compatible with the UnSloth API. ## Decision facts: SPIN - **Adopt for:** SPIN is specialized for self-play fine-tuning in large language models through deep learning. ## Choose when ### Choose mlx-tune if… - Tags unique to mlx-tune: apple-silicon, huggingface, llm, llm-finetuning. - Also covers Computer Vision, Speech & Audio. - You need to fine-tune large language models on a Mac with Apple Silicon hardware ### Choose SPIN if… - Tags unique to SPIN: fine-tuning, self-play. - When implementing self-play algorithms aimed at enhancing performance of large language models within constrained domains. ## When NOT to use mlx-tune - Your development environment is not based on macOS running on Apple Silicon - The specific tasks you are targeting do not align with the capabilities of mlx-tune such as those exclusive to alternative platforms or tools ## When NOT to use SPIN - If your project strictly adheres to frameworks that do not incorporate self-play techniques for training or fine-tuning models. - When prioritizing a model training framework that relies on supervised learning rather than the self-play methodology SPIN is based upon. ## Common questions ### What is the difference between mlx-tune and SPIN? mlx-tune: Fine-tune LLMs on your Mac with Apple Silicon for various tasks including SFT, DPO, GRPO, Vision, TTS, STT, Embedding, and OCR.. SPIN: Official implementation of Self-Play Fine-Tuning. See the comparison table for live GitHub stats and shared categories. ### When should I choose mlx-tune over SPIN? Choose mlx-tune over SPIN when Tags unique to mlx-tune: apple-silicon, huggingface, llm, llm-finetuning; Also covers Computer Vision, Speech & Audio; You need to fine-tune large language models on a Mac with Apple Silicon hardware. ### When should I choose SPIN over mlx-tune? Choose SPIN over mlx-tune when Tags unique to SPIN: fine-tuning, self-play; When implementing self-play algorithms aimed at enhancing performance of large language models within constrained domains. ### When should I avoid mlx-tune? Your development environment is not based on macOS running on Apple Silicon The specific tasks you are targeting do not align with the capabilities of mlx-tune such as those exclusive to alternative platforms or tools ### When should I avoid SPIN? If your project strictly adheres to frameworks that do not incorporate self-play techniques for training or fine-tuning models. When prioritizing a model training framework that relies on supervised learning rather than the self-play methodology SPIN is based upon. ### Is mlx-tune or SPIN more popular on GitHub? mlx-tune has more GitHub stars (1,372 vs 1,254). Stars measure visibility, not whether either tool fits your constraints. ### Are mlx-tune and SPIN open source? Yes - both are open-source projects on GitHub (mlx-tune: Apache-2.0, SPIN: Apache-2.0). ### Where can I find alternatives to mlx-tune or SPIN? GraphCanon lists graph-backed alternatives at [mlx-tune alternatives](/tools/arahim3-mlx-tune/alternatives) and [SPIN alternatives](/tools/uclaml-spin/alternatives) ([mlx-tune markdown twin](/tools/arahim3-mlx-tune/alternatives.md), [SPIN markdown twin](/tools/uclaml-spin/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/arahim3-mlx-tune-vs-uclaml-spin.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, mlx-tune or SPIN? mlx-tune: Steady. SPIN: 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 mlx-tune and SPIN? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [mlx-tune trust report](/tools/arahim3-mlx-tune/trust); [SPIN trust report](/tools/uclaml-spin/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=arahim3-mlx-tune`](/api/graphcanon/graph?tool=arahim3-mlx-tune) - 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/_