HyperQwen alternatives

syv-ai/HyperQwen (2k stars, +63 this week): Serve large Qwen models fast on the GPUs you actually own. Qwen3.8-27B on a single 24 GB card with vLLM: 127 tok/s single-user (381 when the… Why it matters: useful plumbing for shipping LLM-powered features.

Below are 7 other LLM tooling repos tracked by OSS Radar that share at least two GitHub topics with HyperQwen, ordered by how many topics overlap, then by stars gained in the last 7 days. Topic overlap means a similar problem space, not a drop-in replacement, so check each project's README.

1. 1. mw00/project-maya

   +736/wkest.

   Project Maya - run GLM-5.3-Flash (321B MoE) privately on your own GPU(s), from one card to 16, NVIDIA or AMD, Linux or Windows. Why it matters: useful plumbing for shipping LLM-powered features.

   766 stars · C++ · shared topics: cuda, llm-inference, local-llm, quantization

2. 2. vllm-project/vllm

   +56/wkest.

   A high-throughput and memory-efficient inference and serving engine for LLMs. Why it matters: useful plumbing for shipping LLM-powered features.

   94k stars · Python · shared topics: cuda, qwen, qwen3

3. 3. MakazhanAlpamys/Soup

   +315/wkest.

   Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU. Why it matters: useful plumbing for shipping LLM-powered features.

   8.9k stars · Python · shared topics: consumer-gpu, local-llm

4. 4. bojieli/ai-infra-book

   +196/wkest.

   Open-source book that derives LLM inference and training system design from hardware limits, with calculation tools. Why it matters: useful plumbing for shipping LLM-powered features.

   6.5k stars · Python · shared topics: kv-cache, llm-inference

5. 5. sgl-project/sglang

   +77/wkest.

   SGLang is a high-performance serving framework for large language models and multimodal models. Why it matters: useful plumbing for shipping LLM-powered features.

   37k stars · Python · shared topics: cuda, qwen

6. 6. hiyouga/LlamaFactory

   +49/wkest.

   Unified Efficient Fine-Tuning of 100+ LLMs & VLMs (ACL 2024). Why it matters: useful plumbing for shipping LLM-powered features.

   75k stars · Python · shared topics: quantization, qwen

7. 7. amitshekhariitbhu/ai-engineering-interview-questions

   +42/wkest.

   Your Cheat Sheet for AI Engineering Interview – Questions and Answers. Why it matters: useful plumbing for shipping LLM-powered features.

   3.4k stars · Markdown · shared topics: llm-inference, quantization

More: all trending LLM tooling repos · compare HyperQwen with the top 2