MiaAI-Lab/Qwen3.8-27B-16gb-NVIDIA-GPUs-one-click-install

Qwen3.8-27B on a single RTX 3090: 416 tok/s batched or 25 ms/token single-user, 150k context, vLLM

A minimal PyTorch re-implementation of Qwen 3.8

Community recipes for serving LLMs on RTX 3090/4090/5090 CUDA gpus. Multi-engine (vLLM, llama.cpp, ik_llama) and model-agnostic. Currently shipping Qwen3.6-27B Qwen3.6 35B Gemma 4 26B Gemma 4 31B configs for 1× and 2× cards.

Qwen3.8-Flash-Next (125B MoE) on a 12-24 GB NVIDIA GPU + 64 GB RAM: one-click install for Windows / Linux. Strata inference engine, OpenAI/Anthropic API on localhost, optional image input.

LLM model quantization (compression) toolkit with HW acceleration support for Nvidia, AMD, Intel GPU and Intel/AMD/Apple CPU via HF, vLLM, and SGLang.

Qwen3.8 27B on SGLang for DGX Spark

The fastest way to run Qwen3.8-Flash-Next on Strix Halo (gfx1151)

Perplexity open source garden for inference technology

Qwen3.8-Flash-Next on ONE DGX Spark (TP=1)