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IFLoading Phi-3-mini-128k-instruct model in vLLM version 0.4.0.post1 fails with AssertionError: assert 'factor' in rope_scaling.

THENUpgrade vLLM to a version that includes the fix from pull request #4298 (e.g., v0.5.0 or later). As a temporary workaround, edit the model's config.json to add a 'factor' key (e.g., 'factor': 1.0) inside the rope_scaling dictionary before loading with vLLM.

IFNotImplementedError: The class UnquantizedLinearMethod must implement the 'embedding' method when loading GLM-4.5-FP8 model in vLLM 0.10.0.

THENUpgrade to a vLLM version that includes the fix from PR #22257, or manually apply the patch by implementing the 'embedding' method in the UnquantizedLinearMethod class. Alternatively, use a different model version or downgrade to an earlier vLLM release that does not have this regression.

IFvLLM engine fails to start when serving DeepSeek-R1-Distill-Qwen-32B model, while the smaller 14B variant works; issue persists on v0.7.3 and RTX A6000 GPUs.

THENReduce model arguments: set --gpu-memory-utilization to 0.5, --max-model-len to 1024, use --tp 2 (tensor parallelism across 2 GPUs), --dtype float16, and --swap-space 4. Enable DEBUG logging with VLLM_LOGGING_LEVEL=DEBUG to capture detailed startup errors. If the problem persists, incrementally remove other CLI flags to isolate the conflicting feature.

IFLoading Qwen2.5-VL models with AutoProcessor raises ValueError: Unrecognized image processor.

THENRemove the 'image_processor_type' key from preprocessor_config.json or update the hub files to include the slow image processor. Alternatively, revert to a transformers version before the breaking commit (e.g., 1931a351408dbd1d0e2c4d6d7ee0eb5e8807d7bf) or force the model to use the Qwen2VL slow processor.