Qwen3.5 122B A10B NVFP4 Model Overview Model Architecture: Qwen3NextForCausalLM Input: Text Output: Text Model Optimizations: Weight quantization: FP4 Activation quantization: FP4 Release Date: Version: 1.0 Model Developers: : Red Hat Quantized version of Qwen/Qwen3.5 122B A10B. Model Optimizations This model was obtained by quantizing the weights and activations of Qwen/Qwen3.5 122B A10B to FP4 data type. This optimization reduces the number of bits per parameter from 16 to 4, reducing the disk size and GPU memory requirements by approximately 75%. Only the weights and activations of the linear operators within transformers blocks of the language model are quantized. Deployment Use with vLLM This model can be deployed efficiently using vLLM. 1. Text Only : Skip the vision encoder to free up memory for additional KV cache: 2. Multimodal (Text + Image) : Serve with full vision support: 3. Tool Call : Enable tool use support: 4. Multi Token Prediction (MTP) : For speculative decoding: 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 ifeval, mmlu pro and gsm8k plat…
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