GPU-poor long-context players, this one’s for you.
This is a dev post classified by AGK Intelligence as AI dev tools (a tool drop), kept by the Dev Radar because it carries real work, not commentary.
GPU-poor long-context players, this one’s for you. Latent Sparse Attention just made ultra-long context dramatically 70× cheaper on Qwen-3.8-27B - 72.4× faster prefill attention - 42.5× faster decode - End-to-end first token 9× quicker No full retraining required you can distill an indexer and drop it on the existing model. Accuracy stays essentially the same. This is one of the cleaner open efficiency wins we’ve seen for real 1M–10M token workloads. Repo and distilled weights are public. - http://github.com/Prefrontal-AI/latent-sparse-attention
Posted by Md Ismail Šojal 🕷️ (64.7k followers) 1 h ago · 4 likes · 515 views · view the original post on X. Kept by the Dev Radar as AI dev tools. Tools mentioned: latent-sparse-attention.
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