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The Full 2.8-Trillion-Parameter Kimi K3 Now Runs on Sixteen Desktop Boxes News
An operator has the complete Kimi K3 checkpoint running across sixteen GB10 mini-workstations wired through a single 400G switch, producing roughly 21 to 25 tokens per second for one user, on hardware with a verifiable floor around $57,200.
The 'Ternary' 20B Model Everyone Downloaded Today Ships as a Two-Bit Package News
DeepGrove's Maple-Preview is being shared as a 20-billion-parameter ternary model that fits in about 5 gigabytes, but its native release is a 40GB BF16 repository and the small footprint belongs to a separate two-bit MLX build with no published ternary training recipe.
High Bandwidth Flash Became a Spec Today, Not a Product You Can Buy News
SK hynix and Sandisk published the first standard for High Bandwidth Flash at FMS 2026, defining a NAND memory tier of up to 512GB per stack with a top bandwidth grade near three terabytes a second - with no named accelerator, price or availability date.
A llama.cpp Patch Learns Which Experts to Keep in VRAM While You Type News
An open pull request to llama.cpp tracks which mixture-of-experts submodels get used most during inference and promotes them to GPU memory on the fly, roughly doubling decode speed on an 8GB card in the author's own tests - while slowing other models down.
Meituan open-sources LongCat-2.0, a trillion-parameter model it says was trained end-to-end on Chinese chips News
Meituan released LongCat-2.0, a 1.6-trillion-parameter open-weight (MIT) model that ran anonymously as 'Owl Alpha' for two months and was, the company says, both trained and served entirely on domestic Chinese AI ASICs with no Nvidia GPUs.
Maple-Preview (2-bit MLX build) Tool
DeepGrove's 20B mixture-of-experts model with about 1B active parameters per token, packaged for Apple Silicon at roughly 5.3GB. The build uses affine two-bit group quantisation with four-bit embeddings and output head, and its loader packs ternary values into two-bit codes. Note that the native BF16 repository is about 40.4GB, and DeepGrove publishes no ternary training recipe or independent evaluation.
LongCat-2.0 Tool
Meituan's 1.6T-parameter MoE model tuned for coding and agentic work, MIT-licensed weights plus a cheap hosted API (launch promo $0.30/$1.20 per million tokens) that self-hosts to avoid data-jurisdiction concerns.
Ling-3.0-flash Tool
inclusionAI's 124B mixture-of-experts model with about 5.1B parameters activated per token. Sparse routing genuinely cuts per-token compute, but this is a server-class artifact, not a laptop one: the BF16 repository is roughly 255GB and the official serving path calls for custom SGLang or vLLM forks with tensor parallelism across four GPUs.
Kimi K2.6 weights (Hugging Face) Tool
The actual Kimi K2.6 model weights, published under a modified-MIT license for anyone to download, run, and build on; large enough that full-strength use needs a multi-GPU node.