Changelog

Changelog#

[Unreleased]#

CLI#

  • Renamed python -m qbcompiler mblt_compile → parse and python -m qbcompiler mxq_compile → quantize. The compile end-to-end pipeline and all flags are unchanged. The check capabilities list now advertises parse / quantize in place of the old names.

[v1.2.0] - 2026-06-26#

API#

  • Unified qbcompiler support for multiple hardware targets, including REGULUS and ARIES, into a single compiler.

[v1.1.0] - 2026-03-31#

API#

  • The configuration of the mxq_compile function has been structurally refactored.

  • For ONNX model parsing, graph optimization is now handled by the newly refactored parser based on mblt-graph.

  • Improved quantization accuracy for non-linear activation functions.

[v1.0.2] - 2026-02-12#

API#

  • Added support for all in inference_scheme.

  • Fixed an issue where the optimize option was not being applied correctly.

[v1.0.0] - 2026-01-30#

API#

  • Introduced support for Qwen3 LLMs.

  • Expanded compatibility to include the YOLO26 series.

  • Removed the deprecated singlecore compile and startdramoffset options.

  • Added support for custom masks and dynamic RoPE.

  • Added NPU-accelerated execution for parts of the pre-processing pipeline, along with new input process configuration.

    • Added support for uint8 inputs.

    • Added NPU-based normalization.

  • Added support for Torch tensors and image files as calibration data.

  • Removed redundant quantization configuration options and unified Percentile, MSE, and KL into a histogram-based observer.

  • Added support for dynamic core and memory allocation for all models.

[v0.12.0.0] - 2026-01-02#

API#

  • Refactored compilation and quantization configuration.

  • Optimized CPU memory usage during compilation.

  • Added support for Transformers v4.57.1 (aligned with the 0.12 Mobilint Docker release).

  • Added support for the MiniCPM model.

[v0.11.0.0] - 2025-09-10#

API#

  • Added support for Torch parser

  • Added support for Yolo12l and Yolo12x

  • Expanded support range for ViT models

  • Fixed minor bugs for GRU/RNN/LSTM

[v0.10.0.0] - 2025-07-24#

API#

  • Added Inference_scheme global4/global8 modes

  • Added support for Yolov10 series, Yolo11 series, Yolo12n, Yolo12s, and Yolo12m

  • Added LLM config options

  • Added support for GRU/RNN/LSTM

[v0.9.0.5] - 2025-06-25#

API#

  • Changed YOLO model decoding to be linked with the model zoo

  • Added layer config options

[v0.9.0.4] - 2025-05-22#

API#

  • Added support for direct compilation of HuggingFace LLM models

[v0.9.0.3] - 2025-04-02#

API#

  • Added support for saving mblt using mmap

  • Added support for diverse visualization types

[v0.9.0.2] - 2025-01-16#

API#

  • Added API for saving model architecture

  • Added support for Visualization tool

  • Added support for Run min output difference QAT mode

[v0.9.0.1] - 2024-12-13#

API#

  • Added API for global core (beta)

  • Added API for YOLO post (beta)

  • Added support for diverse hardware

[v0.9.0.0] - 2024-11-27#

API#

  • Updated the high-level parsing processes

Docker#

  • ONNX: 1.13.0 -> 1.16.2

  • TensorFlow: 2.9.0 -> 2.17.0

  • Torch: 1.13.0 -> 2.4.1

[v0.8.5] - 2024-06-20#

API#

  • Added support for FastPercentile quantization method

[v0.8.4] - 2024-05-20#

API#

  • Connected TF backend to ONNX backend by TF2ONNX

  • Enabled compilation of models with custom input shape

  • Supported more operations

Docker#

  • ONNX: 1.12.0 -> 1.13.0

[v0.8.3] - 2024-03-07#

API#

  • Added support for TF Lite backend

[v0.8.2] - 2024-02-23#

[v0.8.1] - 2023-12-08#

[v0.8.0] - 2023-11-02#

API#

  • Deprecated TVM backend

[v0.7.12] - 2023-09-12#

[v0.7.11] - 2023-08-31#

API#

  • Added support for TorchScript backend

[v0.7.10] - 2023-08-11#

[v0.7.9] - 2023-08-11#

[v0.7.8] - 2023-08-08#

[v0.7] - 2023-03-23#

  • Added multi-channel quantization

  • Supported more operations

API#

  • Improved calibration dataset processing

  • Added support for CPU offloading (beta version)

[v0.6] - 2022-08-10#

  • Made minor updates

[v0.5] - 2022-07-01#

Docker#

  • Switched from Conda to Virtualenv

  • Python: 3.7.7 -> 3.8.10

  • Torch: 1.8.1 -> 1.10.1

  • TensorFlow: 1.15.0 -> 2.3.0

  • ONNX:1.6.0 -> 1.11.0

Parser#

  • Refactored code

API#

  • Enabled saving sample inference results (inputs and outputs)

[v0.4] - 2022-02-23#

Optimizer#

  • Made minor updates in fusing reshape

[v0.3] - 2022-02-05#

Parser#

  • Identified preprocess and postprocess of the model

  • Excluded preprocess and postprocess if they were unsupported by the NPU

API#

  • Added integer inference simulation in the Python API

[v0.2] - 2021-12-01#

  • First release