Inference & serving
TurboQuant (0xSero)
A third-party KV-cache quantization implementation for language-model inference, with Python and GPU-kernel integrations rather than a standalone agent.
Overview
Research summary
This TurboQuant repository implements techniques for reducing the memory footprint of the key-value cache used during language-model inference. It includes Python-facing code and GPU-oriented integration work relevant to inference stacks such as vLLM. The entry represents this particular third-party implementation; the shared algorithm name should not be read as proof that the repository is the original research authors’ official release.
It is a low-level inference optimization component, not an agent, model family, or complete serving platform. Compatibility, numerical behavior, throughput, and memory use depend on the supported model, backend, hardware, and configuration, so published speed or compression figures should be evaluated in the target workload. The repository is GPL licensed.
Model checkpoints and the inference frameworks into which it is integrated retain their own licensing and operational requirements.
Repository summary
- Stars
- 1,771
- Open issues
- Unavailable
- Last push
- 2026-09-03
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Version
- Unavailable
Recorded catalogue figures. View repository data and provenance →
Classification
Pricing & services
Paid services unknown
Whether the provider offers paid products or services has not been established.
Licence scope
Implementation
Recorded implementation details and interfaces for TurboQuant (0xSero).
Implementation details
Python KV-cache quantization code with Triton/inference-stack integrations
- Languages
- Python
- Repository type
- source
Recorded interfaces and capabilities
Licence scope
Repository
Repository snapshots, release information and recorded maintenance signals.
Repository snapshot
- Stars
- 1,771
- Open issues
- Unavailable
- Last push
- 2026-09-03
- Commits, 90 days
- Unavailable
- Repository activity
- Not scored
- Archived
- Not recorded
Repository activity is a snapshot, not a quality or popularity ranking. It combines recent-push freshness (50%), 90-day commits (30%) and issue pressure (20%).
Maintenance and provenance
- Catalogue snapshot
- 2026-10-06
- Stars source
- Recorded fallback
- Last push source
- Recorded fallback
Documentation
Recorded references and research provenance for this entry.
Recorded sources 4
- https://github.com/0xSero/turboquant Project page · Linked repository · Research reference
- https://github.com/0xSero/turboquant/blob/main/README.md Research reference
- https://github.com/0xSero/turboquant/blob/main/LICENSE Research reference
- https://github.com/stars/angelcervera/lists/ai Research reference
Research metadata
- Research date
- 2026-09-16
- Catalogue snapshot
- 2026-10-06