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hybrid_play_32b-nvfp4
Firworks/hybrid_play_32b-nvfp4
hybrid_play_32b-nvfp4 is a machine learning model from Firworks. Use it for the machine learning task on the model card, and read the license before you ship it in a product.
Format: NVFP4 — weights & activations quantized to FP4 with dual scaling. Base model: synthetic-code-training/hybridplay32b How it was made: One-shot calibration with LLM Compressor (NVFP4 recipe), long-seq calibratio…
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From the Hugging Face model README
hybrid_play_32b-nvfp4
Format: NVFP4 — weights & activations quantized to FP4 with dual scaling.
Base model: synthetic-code-training/hybrid_play_32b
How it was made: One-shot calibration with LLM Compressor (NVFP4 recipe), long-seq calibration (256 samples of 4096 length) with nvidia/OpenCodeInstruct.
Notes: Keep
lm_headin high precision; calibrate on long, domain-relevant sequences.
Check the original model card for information about this model.
Running the model with VLLM in Docker
sudo docker run --runtime nvidia --gpus all -p 8000:8000 --ipc=host vllm/vllm-openai:latest Firworks/hybrid_play_32b-nvfp4 --dtype auto --max-model-len 32768
This was tested on an RTX Pro 6000 Blackwell cloud instance.
If there are other models you're interested in seeing quantized to NVFP4 for use on the DGX Spark, or other modern Blackwell (or newer) cards let me know. I'm trying to make more NVFP4 models available to allow more people to try them out.
- Type
- qwen2
- Created
- Jan 20, 2026
- Updated
- Jan 20, 2026