Model Card: NVIDIA Nemotron Labs Dory 1.0
NVIDIA-Nemotron-Labs-Dory1.0-4B: a 4B looped (latent-recurrent) normalized-GPT — 8 input layers + a shared 20-layer recurrent block (run 1/2/4 times) + 8 output layers, 256K context, OpenMDW-1.1 license (MIT-like); shipped quietly to Hugging Face on 2026-10-16 with no official blog post. SWE-bench Verified at 1/2/4 loops: 50.3%/57.4%/73.4% (the 4-loop figure is a cited score, not fully NVIDIA-measured), with the 2-loop setting roughly matching similarly sized dense models Qwen3.5-4B/3.5-9B. The pitch is that one checkpoint can trade inference compute for accuracy at serving time by changing the loop count, no retraining or model swap needed; vLLM/llama.cpp support is still under PR review, and there's no official or third-party API pricing yet.