Ministral 3 14B 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 14B Reasoning 2512 Ministral 3 14B Reasoning 2512 AWQ 4bit : : : : : : Memory Size 51.9 GB 19.4 GB Evaluations Benchmarks Ministral 3 14B Reasoning 2512 Ministral 3 14B Reasoning 2512 AWQ 4bit : : : : : : Perplexity 1.52771 1.5367 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 14B Reasoning 2512 The largest model in the Ministral 3 family, Ministral 3 14B offers frontier capabilities and performance comparable to its larger Mistral Small 3.2 24B counterpart. A powerful and efficient 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 14B can even be deployed locally,…
We use cookies for essential functionality and analytics. You can accept or reject analytics cookies.Cookie policy