tuan3w / qwen-warp
Fast Qwen3.8-27B for one RTX 3090. 200k context, 100+ tok/s. Custom CUDA decode engine, OpenAI-compatible API.
Why this job: topics: llm-inference, vllm, quantization
What it does
Against HyperQwen on the same card: 1.2x to 1.3x faster at 32k to 130k context, 3.6x faster at 190k, and level to 13% ahead with the same DFlash2 drafter on short prompts. Every measurement, method and caveat: docs/PERFORMANCE.md.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 2 days ago
- Stars
- 24
- +24 this week
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- v0.9.1
- Released today
- Built with
- Python
- 51% of the code
Is it looked after?
- Contributors
- 1
- Last 90 days
- Issues
- 0% closed
- 1 still open
- Pull requests
- 10 merged
- 1 waiting
- Releases
- 9
- 7 in the last year
- Contributing guide (opens in new tab)
- Security policy (opens in new tab)
- No code of conduct
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| syv-ai / HyperQwen | 2,626 | 6 days ago | Apache-2.0 | No downloads |
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More: languages, topics and project record
Languages
- Python 51%
- Cuda 33%
- C++ 10%
- C 5%
Topics
- autoresearch
- cuda
- deltanet
- llm-inference
- qwen
- rtx-3090
- speculative-decoding
- int4
- kv-cache
- long-context
- openai-compatible
- quantization
Project record
- JobLocal LLMs
- StatusNew to our list
- Commits137
- Forks4
- Watching1
- CreatedNov 1, 2026
- First seen by usNov 7, 2026
- CheckedNov 9, 2026