January 2026 Monthly Summary for PaddlePaddle/FastDeploy focused on expanding GPT-OSS quantization capabilities and strengthening production readiness. Delivered MXFP4 quantization support for GPT-OSS, along with configuration, environment, and testing scaffolding to enable faster, smaller-footprint inferences and improved FlashInfer compatibility. Work included code cleanup to remove Torch dependencies, environment variable enhancements, and tests that validate the full MXFP4 path and end-to-end flows. Prepared deployment readiness with updated dependencies and testing coverage for FlashInfer workflows.

December 2025 monthly summary for PaddlePaddle/FastDeploy focused on API simplification and maintainability. Delivered a key API simplification in the Linear layers by removing the add_bias option and unifying bias handling through the with_bias parameter. The change is implemented in commit e397c4fba6df8c9ac7976b546da96c090ac7304e, reducing API surface area and enforcing consistent bias semantics across modules.

2025-11 Monthly Summary: Focused stability and deployment efficiency across PaddlePaddle projects, with targeted OCR reliability improvements and memory management optimizations for TensorRT deployments. Delivered enhanced testing coverage, critical bug fixes, and code cleanup to improve maintainability and business value.

October 2025 (PaddlePaddle/FastDeploy) monthly summary: Delivered GPT-OSS BF16 support and attention enhancements, enabling BF16 precision for GPT-OSS models with sinks and sliding-window attention. Updated CUDA kernels and Python interfaces to improve performance and flexibility for large language models. No major bugs were documented for this period; the focus was on feature delivery and performance optimization to support scalable, production-ready LLM deployments.