Pattern preview · 12 of 4,089 sample rules shown · site-specific intelligence stays private
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model_quantization_compatibility
performance-model-quantization-c-vllm-fails-with-assert-self-quant-method-is-not-no-f8b7cad3
IFvLLM fails with 'assert self.quant_method is not None' when loading a bitsandbytes 4-bit quantized MoE model (e.g., unsloth/Llama-4-Scout-17B-16E-Instruct-unsloth-bnb-4bit)
THENAvoid using bitsandbytes quantization with MoE models in vLLM. Either use a different quantization method (like AWQ) that has a corresponding FusedMoE kernel, or select a model that does not use MoE. If the model's config.json specifies quant_method: bitsandbytes, you may need to convert the model to AWQ or wait for vLLM to support bitsandbytes for MoE architectures.
Tier 170%
model_quantization_compatibility
infrastructure-model-quantization-c-vllm-raises-assert-self-quant-method-is-not-none-w-beb8427d
IFvLLM raises 'assert self.quant_method is not None' when loading a bitsandbytes quantized Mixture-of-Experts (MoE) model such as Llama-4-Scout.
THENSwitch to a different quantization method (e.g., AWQ) that vLLM supports for MoE architectures, or wait for a vLLM update that adds FusedMoE kernels for bitsandbytes. Currently, vLLM lacks a FusedMoE kernel for bitsandbytes, causing the loading failure.
Tier 170%
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