--- title: "litgpt vs MiniMax-01" type: "comparison" canonical_url: "https://www.graphcanon.com/compare/lightning-ai-litgpt-vs-minimax-ai-minimax-01" tools: ["lightning-ai-litgpt", "minimax-ai-minimax-01"] --- # litgpt vs MiniMax-01 *GraphCanon updated Aug 18, 2026* ## Verdict Pick litgpt if litGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment; pick MiniMax-01 if miniMax-01 optimizes Linear Attention for large-language and vision-language models. [litgpt](https://lightning.ai) reports 14k GitHub stars, 1.5k forks, and 272 open issues, last pushed Jul 20, 2026. [MiniMax-01](https://www.minimax.io/) has 3.5k stars, 332 forks, and 8 open issues, last pushed Jul 7, 2025. Figures are from public GitHub metadata via [litgpt's repository](https://github.com/Lightning-AI/litgpt) and [MiniMax-01's repository](https://github.com/MiniMax-AI/MiniMax-01). | | [litgpt](/tools/lightning-ai-litgpt.md) | [MiniMax-01](/tools/minimax-ai-minimax-01.md) | | --- | --- | --- | | Tagline | High-performance LLMs with recipes for pretraining, finetuning and deployment | Repository for MiniMax-Text-01 and MiniMax-VL-01 models based on Linear Attention | | Stars | 13,605 | 3,463 | | Forks | 1,483 | 332 | | Open issues | 272 | 8 | | Language | Python | Python | | Adopt for | LitGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment. | MiniMax-01 optimizes Linear Attention for large-language and vision-language models. | | Persona | - | - | | Runtime | - | - | | License | LitGPT operates under the open-source Apache-2.0 license, providing permissive terms for use and modification. | MIT | | Categories | Inference & Serving, LLM Frameworks, Model Training | LLM Frameworks, Model Training | ## Trust and health _Sourced signals - not a safety guarantee. No winner column._ | | [litgpt](/tools/lightning-ai-litgpt.md) | [MiniMax-01](/tools/minimax-ai-minimax-01.md) | | --- | --- | --- | | Maintenance | Active (82%) | Dormant (18%) | | Days since push | 17d | 406d | | Open issues (now) | 272 | 8 | | Stars delta | +137 (30d) | +17 (30d) | | Open issues delta | +6 (30d) | 0 (30d) | | Full report | [trust report](/tools/lightning-ai-litgpt/trust.md) | [trust report](/tools/minimax-ai-minimax-01/trust.md) | ## Decision facts: litgpt - **Pricing:** freemium - The core LitGPT framework is free to use under an open source license, but users might encounter costs when deploying at scale or using high-performance models. - **Requirements:** Min 16 GB RAM - **Adopt for:** LitGPT offers extensive support for high-performance LLMs with comprehensive workflows for pretraining, fine-tuning, and deployment. - **License detail:** LitGPT operates under the open-source Apache-2.0 license, providing permissive terms for use and modification. ## Decision facts: MiniMax-01 - **Adopt for:** MiniMax-01 optimizes Linear Attention for large-language and vision-language models. ## Choose when ### Choose litgpt if… - License: litgpt is Apache-2.0, MiniMax-01 is MIT. - Pricing: The core LitGPT framework is free to use under an open source license, but users might encounter costs when deploying at scale or using high-performance models.. - Requirements: Min 16 GB RAM. - Tags unique to litgpt: ai, artificial-intelligence, deep-learning, llm-inference. - Also covers Inference & Serving. - If you are focusing on a project that requires rapid prototyping or experimentation with over 20 different LLMs to find the best fit for your application. ### Choose MiniMax-01 if… - License: MiniMax-01 is MIT, litgpt is Apache-2.0. - Tags unique to MiniMax-01: llm, vision-language-model, vlm. - When high throughput performance is required for model serving ## When NOT to use litgpt - If you need a tool specifically optimized for resource-constrained devices, as LitGPT focuses on high-performance LLMs and may require more resources. - When your project is strictly limited to only one or two types of specific LLMs; in this case, another specialized framework that caters narrowly might be preferable. ## When NOT to use MiniMax-01 - If deep customization of attention mechanisms aside from Linear Attention is needed - In favor of frameworks lacking vLLM's optimization features, when efficiency or memory use are secondary to flexibility ## Common questions ### What is the difference between litgpt and MiniMax-01? litgpt: High-performance LLMs with recipes for pretraining, finetuning and deployment. MiniMax-01: Repository for MiniMax-Text-01 and MiniMax-VL-01 models based on Linear Attention. See the comparison table for live GitHub stats and shared categories. ### When should I choose litgpt over MiniMax-01? Choose litgpt over MiniMax-01 when License: litgpt is Apache-2.0, MiniMax-01 is MIT; Pricing: The core LitGPT framework is free to use under an open source license, but users might encounter costs when deploying at scale or using high-performance models.; Requirements: Min 16 GB RAM; Tags unique to litgpt: ai, artificial-intelligence, deep-learning, llm-inference; Also covers Inference & Serving; If you are focusing on a project that requires rapid prototyping or experimentation with over 20 different LLMs to find the best fit for your application. ### When should I choose MiniMax-01 over litgpt? Choose MiniMax-01 over litgpt when License: MiniMax-01 is MIT, litgpt is Apache-2.0; Tags unique to MiniMax-01: llm, vision-language-model, vlm; When high throughput performance is required for model serving. ### When should I avoid litgpt? If you need a tool specifically optimized for resource-constrained devices, as LitGPT focuses on high-performance LLMs and may require more resources. When your project is strictly limited to only one or two types of specific LLMs; in this case, another specialized framework that caters narrowly might be preferable. ### When should I avoid MiniMax-01? If deep customization of attention mechanisms aside from Linear Attention is needed In favor of frameworks lacking vLLM's optimization features, when efficiency or memory use are secondary to flexibility ### Is litgpt or MiniMax-01 more popular on GitHub? litgpt has more GitHub stars (13,605 vs 3,463). Stars measure visibility, not whether either tool fits your constraints. ### Are litgpt and MiniMax-01 open source? Yes - both are open-source projects on GitHub (litgpt: Apache-2.0, MiniMax-01: MIT). ### Where can I find alternatives to litgpt or MiniMax-01? GraphCanon lists graph-backed alternatives at [litgpt alternatives](/tools/lightning-ai-litgpt/alternatives) and [MiniMax-01 alternatives](/tools/minimax-ai-minimax-01/alternatives) ([litgpt markdown twin](/tools/lightning-ai-litgpt/alternatives.md), [MiniMax-01 markdown twin](/tools/minimax-ai-minimax-01/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/lightning-ai-litgpt-vs-minimax-ai-minimax-01.md) mirrors this page for agents and LLM crawlers, with the same stats table and FAQ answers. ### Which is better maintained, litgpt or MiniMax-01? litgpt: Active. MiniMax-01: 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 litgpt and MiniMax-01? GraphCanon publishes per-repo trust reports with dated maintenance, provenance, and scan summaries: [litgpt trust report](/tools/lightning-ai-litgpt/trust); [MiniMax-01 trust report](/tools/minimax-ai-minimax-01/trust). --- **Machine-readable endpoints** - JSON: [`/api/graphcanon/graph?tool=lightning-ai-litgpt`](/api/graphcanon/graph?tool=lightning-ai-litgpt) - 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/_