Developer fixes vLLM KV-cache offloading bug affecting DeepSeek and Gemma-4 models

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A software engineer identified and fixed a bug in vLLM, the open-source LLM inference engine, related to KV-cache offloading for models with mixed KV-cache groups. The existing logic assumed a single KV-cache group layout and used a single block_size value for chunking calculations, which broke for architectures like DeepSeek-V4-Flash and Gemma-4. The fix introduced a new parameter, blocks_per_chunk, to handle varied chunking requirements while preserving backward compatibility for existing users. The patch was submitted as PR #48878 to the upstream vLLM repository on GitHub. The case highlights how LLM infrastructure bugs can stem from outdated internal assumptions rather than visible runtime failures.

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