Quantization
- NVIDIA ModelOpt:
0.47.0
- Recipe:
general/ptq/nvfp4_default-kv_fp8_cast
- Calibration prompts: 1,024
- Calibration sequence length: 4,096
- KV cache: FP8
- Vision tower: BF16
The checkpoint is stored in ModelOpt's Hugging Face format and includes hf_quant_config.json.
Hugging Face's automated safetensors metadata may display an 8-bit tag and a lower parameter total for this checkpoint because packed FP4 tensors are stored in uint8 containers. The model architecture remains the 27B Smaug-Mini architecture.
Serving
Example vLLM invocation:
vllm serve WiktorMatuszek/smaug-mini-nvfp4 \ --quantization modelopt_fp4 \ --kv-cache-dtype fp8 \ --reasoning-parser qwen3 \ --enable-auto-tool-choice \ --tool-call-parser qwen3_coder
vLLM selects an NVFP4 linear backend according to the GPU and available kernels.
Evaluation
The full capability evaluation for the unquantized model is published on the Smaug-Mini model card. This repository does not claim an independent rerun of that benchmark suite. Quantization can change outputs, so evaluate the checkpoint on your own workload before deployment.
License and attribution
Apache-2.0, following the source checkpoint. Smaug-Mini is published by Abacus.AI; this quantization is an independent community conversion.