7MB binary-weight Mamba LLM — zero floating-point at inference, runs in browser

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1s5g2zh/cohere_transcribe_webgpu_stateoftheart/"> <img alt="Cohere Transcribe WebGPU: state-of-the-art

<!-- SC_OFF --><div class="md"><blockquote> <p><strong>WARNING: wait before download from HF: I just realised my upload of the new versions with the additional fix in the chat

<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.

<p>A few months ago I got obsessed with a question: can you run a real LLM entirely inside a browser tab, with zero backend, zero GPU, and zero install?</p> <p>The answer is yes.

<a href="https://news.ycombinator.com/item?id=48811644">Comments</a>

<!-- SC_OFF --><div class="md"><p>Wrote a deep dive on <strong>FlashAttention-4 (03/05/2026)</strong> that's relevant for anyone thinking about inference performance.</p>

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1t0ea9u/i_built_a_fully_local_meeting_ai_that_runs/"> <img alt="I built a fully local meeting AI that runs

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1st8l2u/kimi_k26_takes_1st_overall_of_open_weights_models/"> <img alt="Kimi K2.6 takes 1st overall of open