Mistral Models
This page provides detailed technical specifications for the Mistral model family supported by NeMo Customizer. For information about supported features and capabilities, refer to Tested Models.
Deployment configurations on this page that use the multi-LLM NIM (nvcr.io/nim/nvidia/llm-nim:1.15.5) cannot serve merged LoRA checkpoints (finetuning_type: lora_merged). Deploy merged LoRA models with vLLM or the model-free NIM; see Choose an Inference Engine.
Mistral-7B-Instruct-v0.3
Training Options
- LoRA: 1x 80GB GPU, tensor parallel size 1
- Full SFT: 1x 80GB GPU, tensor parallel size 1
Deployment Configuration
- LoRA:
- NIM Image:
nvcr.io/nim/nvidia/llm-nim:1.15.5 - GPU Count: 1x 80GB
- Full SFT:
- NIM Image:
nvcr.io/nim/nvidia/llm-nim:1.15.5 - GPU Count: 1x 80GB
- Additional Environment Variables:
NIM_MODEL_PROFILE:vllm
Ministral-3-3B-Instruct-2512
Training Options
- LoRA: 1x 80GB GPU, tensor parallel size 1
- Full SFT: 2x 80GB GPU, tensor parallel size 1
Deployment using NIM is not supported for this model.
Ministral-3-3B-Reasoning-2512
Training Options
- LoRA: 1x 80GB GPU, tensor parallel size 1
- Full SFT: 2x 80GB GPU, tensor parallel size 1
Deployment using NIM is not supported for this model.