Qwen3.8 27B
on NVIDIA Jetson AGX Thor 128GB · TensorRT Edge-LLM · 2,048 ctx
Summary
User reports Qwen3.8-27B at 39.6 tok/s decode on a Jetson AGX Thor, with 926 tok/s prompt processing and 23.6 tok/s end-to-end.
Setup is TensorRT Edge-LLM 0.10.1 with INT4 weights, a FlashHead LM head and MTP speculative decoding, at batch 1 with 2,048-token prompts and 128 tokens out, averaged over 20 requests. Peak memory was 24.8 GiB and the weights download is about 20 GiB.
Accuracy against the FP16 model: GSM8K 96.4 vs 96.1, IFEval 83.5 vs 81.9, MMLU-Pro 79.1 vs 79.5. The user notes Jetson AI Lab reports about 35 tok/s decode with llama.cpp Q4_K_M plus MTP, without stating prompt length or accuracy.