Qwen3.5 122B A10B NVFP4 GB10 Qwen3.5 122B A10B optimized for NVIDIA DGX Spark (GB10, SM12.1) — all quantizations baked in. This checkpoint is derived from Sehyo/Qwen3.5 122B A10B NVFP4 with additional post quantizations applied and saved permanently into the weights. The result loads and serves immediately on GB10 without any runtime quantization overhead. Why this exists The base NVFP4 checkpoint leaves several layer types in BF16 to keep it hardware agnostic. On GB10 (NVIDIA Grace Blackwell, SM12.1), those BF16 layers are a significant bottleneck: GDN (GatedDeltaNet) layers are Qwen3.5's linear attention mechanism. They run on every token and constitute ~33% of decode compute time at BF16. Quantizing them to FP4/FP8 roughly halves their memory bandwidth cost with minimal accuracy impact. The lm head projects hidden states to a 248,320 token vocabulary at every decode step. At BF16 this reads ~1.5 GB of weights per token generated. Quantizing to FP8 halves this to ~750 MB/token — a direct throughput gain. These optimizations are implemented in scottgl9/sglang spark gb10 optimizations as runtime post quantization hooks. This checkpoint bakes them in so: 1. Startup is faster (no qua…
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