Updated Qwen3.5-9B Quantization Comparison

<!-- SC_OFF --><div class="md"><p>I applied video compression to LLM inference and got <strong>10,000x less quantization error at the same storage cost</strong></p> <p><a

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s5cggh/google_turboquant_blew_up_for_kv_cache_heres/"> <img alt="Google TurboQuant blew up for KV cache.

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1v78me1/beellamacpp_v041_kvarn_kv_precision_tail_q2_0q3_1/"> <img alt="BeeLlama.cpp v0.4.1: KVarN, KV

<blockquote> <p><em>Originally published at <a href="https://llmkube.com/blog/turboquant-m5-max-quality-and-asymmetric" rel="noopener

<table> <tr><td> <a href="https://www.reddit.com/r/singularity/comments/1s7rcwr/qwen35_omni_qwens_latest_generation_of_fully/"> <img alt="Qwen3.5 Omni - Qwen’s latest generation

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1szrbub/qwenscope_official_sparse_autoencoders_saes_for/"> <img alt="Qwen-Scope: Official Sparse

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s5qdf6/qwopus_v2_nvfp4_quantization/"> <img alt="Qwopus v2 nvfp4 quantization"

<!-- SC_OFF --><div class="md"><p>So in response to the Great Token Reconning of 2026, I decided to try out Qwen 3.6 as a daily driver, and although it's only been about a day, I