The Runpod Blog

Qwen 3.8 is punching well above its weight for its relatively small size compared to big foundational models. Is there a such thing as a free lunch?

Our pricing philosophy in one line: we move prices to keep GPUs available.

Deploy Qwen3.8-27B on Runpod Serverless with vLLM, then send your first request with curl and the OpenAI Python SDK.

vLLM cold start optimization on Runpod Serverless: compile cache, weight prefetch, CUDA graph config

Which kind of AI actually solves my problem?

Python versions carry a security clock and a performance upgrade you're leaving on the table — here's what changes when you move off an old interpreter, and when it's fine to wait.

By optimizing test architecture through pool-mode parallelization and isolated worker identities rather than increasing compute resources, the team successfully reduced merge-queue CI times by 55%.