ReaDy: Recurrent States as Dynamic Context for Speculative Drafting in Hybrid Linear Attention Large Language Models
ReaDy uses recurrent states for speculative drafting, reaching 3.16× speedup on Qwen3.8-27B.
ReaDy uses recurrent states for speculative drafting, reaching 3.16× speedup on Qwen3.8-27B.
On Qwen3.8-27B and one B200, ReaDy averages 3.16 times autoregressive speed and beats DSpark on every benchmark.
JSSA sparse attention stays near full-KV accuracy and raises 128K decoding throughput up to 6.43×.
autotrust released an unofficial pruned NVFP4 GLM-5.3-Flash build that fits two NVIDIA DGX Sparks.
Aleph Alpha released Kolibri, a 78-billion-parameter open-weight German-English mixture-of-experts model.
Aleph Alpha released Kolibri, a 78.1B open-weight English-German MoE with 3.46B active parameters.
LeapQuant nearly matches FP32 quality with training-free 8-bit recurrent-state quantization.
Video DeltaNet combines softmax and linear attention for video generation, cutting DiT denoising of a 14.3-second 768p video to 6.7 seconds.
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