DiffuSpace · Diffusion MoE LLM

Clover-35B-A3B-Preview

Clover-35B-A3B-Preview is the first release in DiffuSpace's Clover series. It is a Mixture-of-Experts diffusion language model with 35 billion total and 3 billion active parameters, and it supports a thinking mode. DiffuSpace says it outperforms the similarly sized autoregressive Qwen3.6-35B-A3B on several benchmarks while generating faster. It reports 73.6 on SWE-bench Verified, 51.7 on Terminal-Bench 2.1, 65.3 on τ³ Overall, 83.8 on GPQA Diamond, 95.8 on ZebraLogic and 72.0 on AA-LCR. It also reports the highest score among the compared models on all six agent benchmarks. Speed figures are 680 tokens/s on a single NVIDIA GB300 (BF16, batch size 1, internal agent workloads) and 515 tokens/s on a single H200, against 365 tokens/s for a DFlash2-accelerated Qwen model. An INT4 build on a 16GB RTX 5070 Ti reaches 101.8 tokens/s on MATH-500. The speed and benchmark figures come from the developers' own tests. The model uses block diffusion with a redesigned bidirectional Gated DeltaNet: a recurrent state compresses past context, and bidirectional softmax attention handles tokens within the current block. Weights and code are released under an Apache licence on Hugging Face, ModelScope and GitHub, with SGLang and llama.cpp support. Online access is by application.