{"data":{"slug":"minimax-ai-minimax-01","name":"MiniMax-01","tagline":"Repository for MiniMax-Text-01 and MiniMax-VL-01 models based on Linear Attention","github_url":"https://github.com/MiniMax-AI/MiniMax-01","owner":"MiniMax-AI","repo":"MiniMax-01","owner_avatar_url":"https://avatars.githubusercontent.com/u/194880281?v=4","primary_language":"Python","stars":3463,"forks":332,"topics":["large-language-models","llm","llms","minimax-text-01","minimax-vl-01","vision-language-model","vlm"],"archived":false,"github_pushed_at":"2025-07-07T12:24:30+00:00","maintenance_label":"Dormant","stars_delta_30d":17,"url":"https://www.graphcanon.com/tools/minimax-ai-minimax-01","markdown_url":"https://www.graphcanon.com/tools/minimax-ai-minimax-01.md","api_url":"https://www.graphcanon.com/api/graphcanon/tools/minimax-ai-minimax-01","graph_url":"https://www.graphcanon.com/api/graphcanon/graph?tool=minimax-ai-minimax-01","description":"The official repo of MiniMax-Text-01 and MiniMax-VL-01, large-language-model & vision-language-model based on Linear Attention","homepage_url":"https://www.minimax.io/","license":"MIT","open_issues":8,"watchers":46,"ai_summary":"Offers deployment guides for production use via vLLM or Transformers for miniaturized large language and vision-language models.","readme_excerpt":"## 5. Deployment Guide\n\nFor production deployment, we recommend using [vLLM](https://docs.vllm.ai/en/latest/) to serve MiniMax-Text-01 and MiniMax-VL-01. vLLM provides excellent performance for serving large language models with the following features:\n\n- 🔥 Outstanding service throughput performance\n- ⚡ Efficient and intelligent memory management\n- 📦 Powerful batch request processing capability\n- ⚙️ Deeply optimized underlying performance\n\nFor detailed vLLM deployment instructions, please refer to our [vLLM Deployment Guide](docs/vllm_deployment_guide.md).\n\nAlternatively, you can also deploy using Transformers directly. For detailed Transformers deployment instructions, you can see our [MiniMax-Text-01 Transformers Deployment Guide](docs/transformers_deployment_guide.md).","github_created_at":"2025-01-14T15:43:28+00:00","created_at":"2026-07-07T17:35:45.807149+00:00","updated_at":"2026-08-18T00:01:55.48958+00:00","categories":[{"slug":"llm-frameworks","name":"LLM Frameworks","url":"https://www.graphcanon.com/categories/llm-frameworks","markdown_url":"https://www.graphcanon.com/categories/llm-frameworks.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/llm-frameworks"},{"slug":"model-training","name":"Model Training","url":"https://www.graphcanon.com/categories/model-training","markdown_url":"https://www.graphcanon.com/categories/model-training.md","api_url":"https://www.graphcanon.com/api/graphcanon/categories/model-training"}],"tags":[{"slug":"large-language-models","name":"large language models"},{"slug":"llm","name":"llm"},{"slug":"vision-language-model","name":"vision-language-model"},{"slug":"vlm","name":"vlm"}],"trust":{"provenance":{"is_fork":false,"github_id":916695726,"owner_type":"Organization","methodology":"github_public_v1","parent_repo":null,"near_duplicate_slugs":[]},"computed_at":"2026-08-18T00:01:54.750Z","maintenance":{"label":"Dormant","score":18,"methodology":"github_public_v1","releases_90d":0,"days_since_push":406,"last_release_at":null,"stars_delta_30d":17,"open_issues_delta_30d":0},"security_summary":{"status":"no_lockfile","scanner":null,"low_count":0,"high_count":0,"last_scan_at":"2026-07-11T11:06:08.175Z","medium_count":0,"scan_profile":"none","critical_count":0}},"capability_facts":{"scan":{"source":"repo_scan","observed_at":"2026-08-18T00:01:55.205Z"},"languages":{"value":["python"],"source":"github.language","observed_at":"2026-08-18T00:01:55.205Z"},"license_spdx":{"value":"MIT","source":"github.license","observed_at":"2026-08-18T00:01:55.205Z"}},"decision_facts":{"hosting":null,"pricing":null,"requirements":null,"constraints":null,"when_to_use":["When high throughput performance is required for model serving","For efficient memory management and batch request handling"],"when_not_to_use":["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"],"source":"enrich:decision_facts","observed_at":"2026-07-14T18:23:53.974Z"},"constraint_facets":null,"decision_summary":[{"label":"Adopt for","value":"MiniMax-01 optimizes Linear Attention for large-language and vision-language models."}]}}