March 2026 monthly summary for aobolensk/openvino focusing on Whisper inference and NPUW plugin work. Key features and fixes delivered: - End-of-sequence handling and EOS support for Whisper inference: fixed a crash when the model repeats tokens by returning eos_token and continuing processing across chunks; EOS handling remains robust across serialization changes. Commits: 2de7eacb51fc77216382da708eb8e6850a454db8 and 9d77cc4b16615f63ab7cc12d978abf6a4cc79765. - Disable weights sharing for int8 Whisper models to optimize performance and correctness for this configuration. Commit: 04f948ce8c435b56bc33e7e4ca34b1459da738d4. - NPUW plugin: added missing caching properties to improve reliability and functionality. Commit: 7566337152838dbab78c012eb585319faac0b5dc. Overall impact and accomplishments: - Increased stability and resilience of Whisper inference in edge-like scenarios with repeated tokens, reducing downtime and manual intervention. - Improved performance and correctness for int8 Whisper deployments by disabling weights sharing. - Enhanced NPUW plugin reliability through complete caching property support, leading to smoother operation and easier maintenance. Technologies/skills demonstrated: - Whisper inference lifecycle, End-of-Sequence handling, token EOS semantics, and serialization compatibility - Model quantization considerations (int8) and performance tuning - NPUW plugin development, caching strategies, and reliability improvements Business value: - Fewer crashes, more robust inference, and more predictable deployments for Whisper-based solutions; better utilization of efficient int8 paths; improved plugin stability, reducing operational overhead.

December 2025 monthly summary focusing on reliability improvements for the NPU Whisper pipeline in openvino.genai. Implemented default stateful initialization, updated tests to validate the new behavior, and prepared release notes and documentation alignment. This change reduces initialization-related instability and aligns startup semantics with runtime behavior.

Concise monthly summary for 2025-11 focusing on delivering performance optimization for Whisper models in OpenVINO. Implemented a targeted change to disable V-tensors transpose in LLMCompiledModel, addressing a performance bottleneck observed with transposed V-tensors and enabling faster Whisper-based inference. The work is tracked in commit 24654ef2cd561b579c45d618c46e310d74d16ead (NPUW: Disable V-tensors transpose for Whisper models) and linked to E-190315 (#33053). Repository involved: openvinotoolkit/openvino.

October 2025 performance snapshot for openvinotoolkit/openvino.genai: Delivered Whisper Model Pipeline Enhancements for NPU and Transformer Compatibility. Enabled WhisperStatefulImpl for NPU, fixed compatibility with transformer versions 4.53.3 and 4.55, introduced new configurations and logic to optimize NPU performance, and improved pipeline robustness and efficiency. This work reduces integration risk for downstream Whisper workloads and enables smoother deployments on updated transformer stacks. Technologies demonstrated include NPU-optimized stateful pipelines, OpenVINO GenAI integration, and transformer-version compatibility tuning.

Concise monthly summary for Sep 2025 focusing on business value and technical achievements. Delivered a critical bug fix and robustness improvements for attention mask handling in the Whisper pipeline within the openvino.genai repository. Implemented a new matcher pass AttentionMaskInput_2 and refined the existing AttentionMaskInput pass to support varying input sizes/types for ScaledDotProductAttention, tied to a targeted commit.

August 2025 performance summary for openvino.genai: Focused on reliability and correctness in the Whisper FP8 cross-attention path. No new features were shipped this month; a critical bug fix improved runtime state handling and ScaledDotProductAttention (SDPA) interactions for FP8 Whisper models, enhancing stability and correctness in production deployments. The change addressed an extra FakeConvert node in the f8e4m3 path that could mis-expose runtime states, ensuring proper processing of key/value tensors even with additional conversion nodes. This reduces risk of incorrect results and supports more robust FP8 deployment in OpenVINO GenAI.

July 2025 monthly summary for openvinotoolkit/openvino.genai: Focused on delivering performance enhancements and architecture improvements for Whisper-based decoding integration. Key work centered on introducing an attention mask for the decoder to support variable-length sequences and on refactoring the decoder cache to directly leverage compiled models, streamlining the OpenVINO GenAI pipeline.

May 2025 monthly summary for the openvinotoolkit/openvino.genai work, focusing on key accomplishments and business impact. Primary effort this month was a critical bug fix for FP8 model compatibility in the Whisper static pipeline, restoring correct operation and enabling FP8-based inference workflows.

March 2025 Monthly Summary for openvino.genai: Whisper Inference Enhancements with Dual-Model Support and Sampler-based Token Generation. Delivered dual-model Whisper support by updating the decoder and KV cache handling, exposing cache states for stateful inference, removing the cache_position input, and integrating StatefulToStateless. Refactored StaticWhisperPipeline to integrate a Sampler for token generation, improving sampling parameter handling, RNG usage, and introducing new logits processing and decoding functions to use the Sampler for flexible and correct token generation. This work is tracked by commits 50c45f0a2cfefad1c7dfe85a0532abbe97525855 and 83f2eb0f149f9dfae031efdb64c7afa74c321b9b. The changes enhance capability and flexibility for Whisper-based deployments in openvino.genai, enabling richer voice-enabled experiences and streamlined experimentation with sampling strategies.

January 2025: Delivered performance optimization and broad test coverage for Whisper Static Pipeline in openvino.genai. Implemented decoder input handling refactor (set_decoder_input_ids instead of set_decoder_input_ids_attention_mask) and introduced a DecoderCache to tailor decoder models to input sequence length, yielding improved efficiency and correctness. Added comprehensive tests for the Whisper static pipeline and extended CI to validate across configurations and languages, with output comparisons against CPU-based execution. These changes enhance inference speed, reliability, and maintainability across multilingual configurations.

December 2024 performance and stability summary for the openvino.genai repository. Key outcomes focus on reliability, observability, and data-driven optimization for Whisper-based pipelines.

November 2024: Delivered a stability-focused fix to the Whisper pipeline in openvino.genai by correcting hidden state size inference in StaticWhisperPipeline. The change derives encoder output dimensions for decoder models, preventing runtime errors during sequence processing and improving overall reliability of Whisper-based workloads. This work aligns with ongoing quality improvements for openvinotoolkit/openvino.genai (#1179) and reduces churn in downstream ASR pipelines, enabling more consistent throughput.

Month: 2024-10 — OpenVINO GenAI Whisper pipeline delivered with static optimization and corrected attention mask handling in the openvinotoolkit/openvino.genai repository. The work focused on static model reshaping, input shape alignment, and encoder/decoder element type configuration to improve hardware compatibility and static execution. A dedicated fix to the attention mask setting was completed and debug logs were removed to reduce noise and improve reliability. This set of changes enhances deployment readiness for ASR workloads and strengthens the pipeline’s robustness across target backends.