NVIDIA's looped Dory 4B lifts SWE-bench to 61.8
Why it matters
NVIDIA released Nemotron-Labs Dory1.0-4B on Hugging Face on Oct 16, 2026, a 4B-parameter looped (latent-recurrent) model: 8 input layers, a shared 20-layer block that repeats with the input reinjected every loop, and 8 output layers. One checkpoint serves different compute budgets with no retraining: by NVIDIA's own numbers SWE-bench Verified rises from 50.3 at 1 loop to 61.8 at 4 loops (Qwen3.5-9B scores 61), and Terminal-Bench 2.1 from 12.5 to 22.2 with about half the output tokens. Optional last-loop KV caching avoids extra KV-cache memory as loops grow, and it was pre-trained in 4-bit NVFP4 for the first ~4.5T of 6T tokens, with a 256K context. Caveats: extra loops cost compute per token, and Qwen3.5-4B still leads GPQA Diamond (77.7 vs 72.4). Weights under OpenMDW-1.1; vLLM support is under review.
Read the source: NVIDIA on Hugging Face (opens in a new tab)
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