Pattern preview · 12 of 4,089 sample rules shown · site-specific intelligence stays private
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cuda_compatibility
infrastructure-cuda-compatibility-using-vllm-0-9-0-with-fp8-quantized-llama4-models--3a5b6c22
IFUsing vLLM 0.9.0 with FP8 quantized Llama4 models on H100 GPUs triggers CUDA error 'no kernel image is available for execution on the device'.
THENDowngrade to vLLM 0.8.4 or 0.8.5.post1 (e.g., use docker image `vllm/vllm-openai:v0.8.5.post1`) to restore functionality. Alternatively, use a non-FP8 quantized version of the Llama4 model or switch to Llama4 Scout (which works with 0.9.0). Verify the model is fully supported with your environment.
Tier 170%
cuda_compatibility
infrastructure-cuda-compatibility-importerror-undefined-symbol-nvjitlinkcomplete-12--a3bda292
IFImportError: undefined symbol __nvJitLinkComplete_12_4 in libcusparse.so.12 when importing torch after installing vllm with torch 2.5.0 or 2.5.1 on CUDA 12.x.
THENDowngrade torch to version 2.4.0, which is compatible with vllm, or ensure the nvjitlink library (libnvJitLink.so.12) provides the required symbol. Pin torch<2.5 in your environment to avoid forced upgrades by vllm.
Tier 170%
cuda_compatibility
infrastructure-cuda-compatibility-running-vllm-openai-docker-image-version-0-9-0-on--93d19866
IFRunning vllm-openai Docker image version 0.9.0 on H100 GPUs with FP8 quantized Llama-4 Maverick or Scout models raises 'CUDA error: no kernel image is available for execution on the device'.
THENDowngrade the vllm-openai Docker image to version 0.8.5.post1 or earlier (e.g., v0.8.4) to resolve the CUDA kernel mismatch. The issue is a regression in v0.9.0 for FP8 quantized models on H100 GPUs; Scout and Maverick FP8 quantizations both fail. Monitor for a future fix.
Tier 170%
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