Ministral 3 8B Reasoning 2512 AWQ INT4 Model Details Quantization Details Quantization Method: AWQ Bits: 4 Group Size: 32 Calibration Dataset: 5CD AI/LLaVA CoT o1 Instruct Quantization Tool: llm compressor Memory Usage Type Ministral 3 8B Reasoning 2512 Ministral 3 8B Reasoning 2512 AWQ 4bit : : : : : : Memory Size 33.2 GB 13.4 GB Evaluations Benchmarks Ministral 3 8B Reasoning 2512 Ministral 3 8B Reasoning 2512 AWQ 4bit : : : : : : Perplexity 1.55808 1.56552 Evaluation Context Length: 16384 Inference Prerequisite Basic Usage Additional Information Changelog v1.0.0 Initial quantized release Authors Name: Ton Cao Contacts: ton@cyan.kiwi Ministral 3 8B Reasoning 2512 A balanced model in the Ministral 3 family, Ministral 3 8B is a powerful, efficient tiny language model with vision capabilities. This model is the reasoning post trained version, trained for reasoning tasks, making it ideal for math, coding and stem related use cases. The Ministral 3 family is designed for edge deployment, capable of running on a wide range of hardware. Ministral 3 8B can even be deployed locally, capable of fitting in 24GB of VRAM in BF16, and less than 12GB of RAM/VRAM when quantized. Key Features Min…
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