1. Added Support for HQQ Quantization Algorithm

• Integrated HQQ quantization algorithm into MNNConvert tool, which can be enabled via the --hqq parameter
• HQQ quantization supports asymmetric quantization, significantly improving the accuracy of quantized models
• Supports combination with block-wise quantization to further optimize model accuracy

2. Added Support for EAGLE-3 Speculative Decoding Algorithm

• Implemented EAGLE-3 speculative decoding algorithm to improve large language model inference efficiency
• Implemented EagleGeneration class to support draft model-based speculative decoding
• Provided Eagle model export tools supporting export of three components: eagle, eagle_fc, and eagle_d2t

3. Enhanced Support for Qwen Series Models

• Fixed and optimized inference issues with Qwen3-Embedding model
• Added support for Qwen3-VL multimodal large model
• Improved llmexport tool's export support for Qwen series models

Detailed Changes

Model Inference Optimization

• Refactored LLM model loading logic with enhanced error handling in the Llm::load() method
• Optimized KV Cache manager implementation to improve memory management efficiency during inference
• Improved attention mechanism implementation in Metal backend
• Optimized convolution execution efficiency in OpenCL backend

Quantization Tool Improvements

• Integrated HQQ quantizer in WeightQuantAndCoding.cpp for more precise weight quantization
• Optimized quantization parameter configuration logic to automatically set asymmetric quantization when HQQ is enabled
• Fixed bugs in the quantization process, improving quantization stability

Model Export Enhancements

• Improved error handling and log output in llmexport tool
• Optimized model export process to improve export stability
• Revised compression tool documentation with added HQQ quantization usage instructions