eOptShrinkQ: Near-Lossless KV Cache Compression for LLMs
eOptShrinkQ offers near-lossless KV cache compression for LLMs, leveraging spectral denoising and quantization to reduce memory overhead and improve long-context inference.
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eOptShrinkQ offers near-lossless KV cache compression for LLMs, leveraging spectral denoising and quantization to reduce memory overhead and improve long-context inference.
Read the briefing
Unsloth's new API inference endpoint allows operators to run local LLMs like Qwen and Gemma with advanced agentic features, integrating...
A new arXiv paper introduces Reinforced Agent, an inference-time feedback mechanism that uses a secondary reviewer LLM to validate tool...
Google launched TPU 8t and TPU 8i, eighth-generation AI chips specialized for training and inference in the agentic era. Two...