novitalabs / pegaflow
High-performance KV cache storage for LLM inference — GPU offloading, SSD caching, and cross-node sharing via RDMA. Works with vLLM and SGLang.
Why this job: topics: vllm, inference, llm inference
What it does
The default source build targets CUDA 12.8. If your environment uses CUDA 13, disable the default CUDA feature and enable cuda-13 explicitly:
Get started
uv pip install pegaflow-llm
# CUDA 12
uv pip install pegaflow-llm-cu13
# CUDA 13- Maintenance
- Active
- Last commit 6 days ago
- Stars
- 221
- +1 this week
- Licence
- Apache-2.0
- Allows business use
- Downloads for
- Linux
- From the latest release
- Latest version
- v0.25.1
- Released 21 days ago
- Built with
- Rust
- 58% of the code
Is it looked after?
- Contributors
- Not stated
- Last 90 days
- Issues
- 67% closed
- 31 still open
- Pull requests
- 309 merged
- 26 waiting
- Releases
- 51
- 30+ in the last year
- No contributing guide
- No security policy
- No code of conduct
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More: download files, languages, topics and project record
Languages
- Rust 58%
- Python 42%
- Shell <1%
- Dockerfile <1%
Topics
- inference
- kv-cache
- llm
- vllm
Project record
- JobLocal LLMs
- StatusListed
- Commits425
- Forks31
- Watching1
- Stars in 28 days+9
- CreatedJan 5, 2026
- First seen by usNov 7, 2026
- CheckedNov 8, 2026