March 2026 monthly summary for vllm-gaudi: Delivered two high-impact changes that improve multimodal input handling and stabilize training-time inference. Implemented Multimodal Input Options Management by replacing dummy options with limit-per-prompt configurations, enabling finer control of input modalities and reducing configuration drift. Fixed Inference Warmup Decorator by restoring the torch inference decorator to the warmup function, resolving an assertion error related to optimized softmax mode in recompute training. These efforts improved reliability, reduced risk of training interruptions, and demonstrated end-to-end execution from code changes to runtime stability.

Concise monthly summary for 2026-01 focusing on key business value and technical achievements across two vLLM GAUDI repositories. Delivered performance and compatibility improvements for 3D convolution, and aligned multimodal embeddings handling with the v0.14.0 release to broaden model applicability and stability.

July 2025 — Focused on performance-oriented feature delivery for HabanaAI/vllm-fork. Implemented Gemma3: Split QKV optimization to improve workload pipelining and potential throughput for Gemma3 models; added SplitQKVParallelLinear to handle Q/K/V projections and updated Gemma3 attention layer to conditionally use the new class. Updated documentation to include Gemma3 among supported models. All changes linked to commit 27fdc807ab1dc89f5189bd06c835e7df2982479b ("add split qkv to gemma3 (#1517)").