Built in Python, HyperQwen is an open-source LLM inference tool maintained by syv-ai. With 2.1k stars on GitHub, it was last updated in October 2026. Related topics: consumer-gpu, cuda and inference-optimization.
“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 answer quotes the prompt), ~1,035 tok/s at 64 concurrent, 150k-262k context. vLLM patches, requant pipeline, benchmarks.”
— syv-ai, project description on GitHub
Details
| Category | Local LLMs & Inference |
|---|---|
| GitHub stars | 2,067 |
| Forks | 282 |
| Language | Python |
| License | Apache-2.0 |
| Last updated | |
| Owner | syv-ai |
| Repository | syv-ai/HyperQwen |
Tags
consumer-gpucudainference-optimizationkv-cachellm-inferencelocal-llmquantizationqwen
Repository facts from the GitHub public API, refreshed October 18, 2026. The quoted tagline is written by the project owner; the summary above is generated from public facts.