I have tried google TurboQuant with ollama hermes3:8b

<p>Building a production-ready, fault-tolerant Retrieval-Augmented Generation system is an exercise in managing harsh tradeoffs. You want massive context, lightning-fast hybrid

<!-- SC_OFF --><div class="md"><p>Hello,</p> <p>Anyone knows what are the differences and if they are really doing the job they say? Because i was watching something about

<!-- SC_OFF --><div class="md"><p>After burning way too much money on GPT-4 API calls, I finally went all-in on local models with Ollama. The progress in 2026 is insane

<!-- SC_OFF --><div class="md"><p>DeepSeek dropped the full V4 paper this week. preview from april was 58 pages, this version adds a lot of technical depth.</p> <p>What stood out

<!-- SC_OFF --><div class="md"><p><a href="https://x.com/i/status/2036533564158910740">https://x.com/i/status/2036533564158910740</a></p> </div><!-- SC_ON --> &#32; submitted by

<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.

<!-- SC_OFF --><div class="md"><p>Seems like Google didn't give credit where it's due for TurboQuant.</p> </div><!-- SC_ON --> &#32; submitted by &#32; <a

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s350sj/implementing_turboquant_to_mlx_studio/"> <img alt="Implementing TurboQuant to MLX Studio"