Qwen3 30B A3B FP8 block Model Overview Model Architecture: Qwen3MoeForCausalLM Input: Text Output: Text Model Optimizations: Weight quantization: FP8 Activation quantization: FP8 Release Date: Version: 1.0 Model Developers: : Red Hat Quantized version of Qwen/Qwen3 30B A3B. Model Optimizations This model was obtained by quantizing the weights and activations of Qwen/Qwen3 30B A3B to FP8 data type. This optimization reduces the number of bits per parameter from 16 to 8, reducing the disk size and GPU memory requirements by approximately 50%. Only the weights and activations of the linear operators within transformers blocks of the language model are quantized. Deployment Use with vLLM 1. Initialize vLLM server: 2. Send requests to the server: Creation This model was quantized using the llm compressor library as shown below. Creation details Evaluation The model was evaluated on the OpenLLM leaderboard task, using lm evaluation harness. vLLM was used for all evaluations. Evaluation details Openllm V1 Openllm V2 Coding Benchmarks Accuracy Category Metric Qwen/Qwen3 30B A3B RedHatAI/Qwen3 30B A3B FP8 block Recovery (%) OpenLLM V1 ARC Challenge (Acc Norm, 25 shot) 69.28 69.88 100.86 GSM…
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