ALoDLM 8b looped diffusion language model: ~3x inference speed vs its base model

<p>Today Inception Labs dropped <strong>Mercury 3</strong>: a diffusion-based LLM with a 1M-token context window doing <strong>1,068 tokens/sec on NVIDIA GPUs</strong>, claiming

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1thkwgk/bytedance_released_an_open_source_model_that/"> <img alt="bytedance released an open source model

<!-- 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/1s59rct/rys_part_3_llms_think_in_geometry_not_language/"> <img alt="RYS Part 3: LLMs think in geometry, not

<table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1t4jehc/supercharging_llm_inference_on_google_tpus/"> <img alt="Supercharging LLM inference on Google TPUs:

<!-- SC_OFF --><div class="md"><p>I’ve been working on an educational implementation repo for speculative decoding:</p> <p><a

<!-- 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

<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