[tt726259]

After seeing the Docker image for vllm jump +5Gb (to 10Gb!) over the past five months, I grew suspicious of vllm's development practices [1]. It's not easy, for sure, to deal with all those flaky python modules [2].

But having the CUDA packages four times in different layers is questionable! [3]

Yet again, as a college mate of mine used to say, "Don't change it. It works."

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[1]: https://hub.docker.com/r/vllm/vllm-openai/tags

[2]: https://github.com/vllm-project/vllm/issues/13306

[3]: These kinds of workarounds tend to end up accumulating and never get reviewed back:

- https://github.com/vllm-project/vllm/commit/b07d741661570ef1...

- https://github.com/vllm-project/vllm/commit/68d37809b9b52f4d... (this one in particular probably accounts for +3Gb)