Changelog#
[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 (aries, regulus, aries2)
[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