Why We Built VIBE Bench: Rethinking Evaluation for Real Workloads
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Towards Scalable Pre-training of Visual Tokenizers for Generation
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MiniMaxAI/VTP-Small-f16d64
Image Feature Extraction β’ 0.2B β’ Updated β’ 16.4k β’ 11 -
MiniMaxAI/VTP-Base-f16d64
Image Feature Extraction β’ 0.3B β’ Updated β’ 15.6k β’ 18 -
MiniMaxAI/VTP-Large-f16d64
Image Feature Extraction β’ 0.7B β’ Updated β’ 18.3k β’ 13 -
Towards Scalable Pre-training of Visual Tokenizers for Generation
Paper β’ 2512.13687 β’ Published β’ 99
Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
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SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
Paper β’ 2505.19641 β’ Published β’ 68 -
MiniMaxAI/SynLogic
Viewer β’ Updated β’ 49.3k β’ 702 β’ 97 -
MiniMaxAI/SynLogic-7B
Text Generation β’ 8B β’ Updated β’ 116 β’ β’ 23 -
MiniMaxAI/SynLogic-Mix-3-32B
Text Generation β’ 33B β’ Updated β’ 90 β’ β’ 16
MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.
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MiniMax M1
π¬350Generate code from text prompts
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MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Paper β’ 2506.13585 β’ Published β’ 273 -
MiniMaxAI/MiniMax-M1-80k
Text Generation β’ 456B β’ Updated β’ 218 β’ β’ 687 -
MiniMaxAI/MiniMax-M1-40k
Text Generation β’ 456B β’ Updated β’ 12.8k β’ 182
One RL to See Them All: Visual Triple Unified Reinforcement Learning. GitHub: https://github.com/MiniMax-AI/One-RL-to-See-Them-All
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One RL to See Them All: Visual Triple Unified Reinforcement Learning
Paper β’ 2505.18129 β’ Published β’ 61 -
One-RL-to-See-Them-All/Orsta-Data-47k
Updated β’ 388 β’ 17 -
One-RL-to-See-Them-All/Orsta-7B
Image-Text-to-Text β’ 8B β’ Updated β’ 36 β’ 11 -
One-RL-to-See-Them-All/Orsta-32B-0321
Image-Text-to-Text β’ 33B β’ Updated β’ 21 β’ 1
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MiniMaxAI/MiniMax-Text-01
Text Generation β’ 456B β’ Updated β’ 1.75k β’ 652 -
MiniMaxAI/MiniMax-VL-01
Image-Text-to-Text β’ 456B β’ Updated β’ 69.4k β’ 282 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper β’ 2501.08313 β’ Published β’ 300 -
MiniMaxText01
π¬118Generate responses to text and images in a chat interface
Towards Scalable Pre-training of Visual Tokenizers for Generation
-
MiniMaxAI/VTP-Small-f16d64
Image Feature Extraction β’ 0.2B β’ Updated β’ 16.4k β’ 11 -
MiniMaxAI/VTP-Base-f16d64
Image Feature Extraction β’ 0.3B β’ Updated β’ 15.6k β’ 18 -
MiniMaxAI/VTP-Large-f16d64
Image Feature Extraction β’ 0.7B β’ Updated β’ 18.3k β’ 13 -
Towards Scalable Pre-training of Visual Tokenizers for Generation
Paper β’ 2512.13687 β’ Published β’ 99
MiniMax-M1, the world's first open-weight, large-scale hybrid-attention reasoning model.
-
MiniMax M1
π¬350Generate code from text prompts
-
MiniMax-M1: Scaling Test-Time Compute Efficiently with Lightning Attention
Paper β’ 2506.13585 β’ Published β’ 273 -
MiniMaxAI/MiniMax-M1-80k
Text Generation β’ 456B β’ Updated β’ 218 β’ β’ 687 -
MiniMaxAI/MiniMax-M1-40k
Text Generation β’ 456B β’ Updated β’ 12.8k β’ 182
Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
-
SynLogic: Synthesizing Verifiable Reasoning Data at Scale for Learning Logical Reasoning and Beyond
Paper β’ 2505.19641 β’ Published β’ 68 -
MiniMaxAI/SynLogic
Viewer β’ Updated β’ 49.3k β’ 702 β’ 97 -
MiniMaxAI/SynLogic-7B
Text Generation β’ 8B β’ Updated β’ 116 β’ β’ 23 -
MiniMaxAI/SynLogic-Mix-3-32B
Text Generation β’ 33B β’ Updated β’ 90 β’ β’ 16
One RL to See Them All: Visual Triple Unified Reinforcement Learning. GitHub: https://github.com/MiniMax-AI/One-RL-to-See-Them-All
-
One RL to See Them All: Visual Triple Unified Reinforcement Learning
Paper β’ 2505.18129 β’ Published β’ 61 -
One-RL-to-See-Them-All/Orsta-Data-47k
Updated β’ 388 β’ 17 -
One-RL-to-See-Them-All/Orsta-7B
Image-Text-to-Text β’ 8B β’ Updated β’ 36 β’ 11 -
One-RL-to-See-Them-All/Orsta-32B-0321
Image-Text-to-Text β’ 33B β’ Updated β’ 21 β’ 1
-
MiniMaxAI/MiniMax-Text-01
Text Generation β’ 456B β’ Updated β’ 1.75k β’ 652 -
MiniMaxAI/MiniMax-VL-01
Image-Text-to-Text β’ 456B β’ Updated β’ 69.4k β’ 282 -
MiniMax-01: Scaling Foundation Models with Lightning Attention
Paper β’ 2501.08313 β’ Published β’ 300 -
MiniMaxText01
π¬118Generate responses to text and images in a chat interface