Dynamis-Labs / spectralquant
SpectralQuant: Calibrated Eigenbasis Rotation and Water-Filled Bit Allocation for KV-Cache Compression
Why this job: topics: llm-inference, quantization
What it does
This is the canonical private full SpectralQuant repository: niashwin/spectralquant-full. It consolidates the original public release (Dynamis-Labs/spectralquant) with the expanded paper-valid evidence layer developed afterwards. The current paper is the NeurIPS 2026 submission under paper_neurips2026/ (root-level convenience copies: SpectralQuant_main.pdf and SpectralQuant_supplement.pdf). The earlier consolidated technical report under paper_output_consolidated/ and the original NeurIPS-format manuscript under paper_output/ are retained as historical artifacts only.
Get started
No single install command. Read the steps in the README (opens in new tab)
- Maintenance
- Active
- Last commit 5 months ago
- Stars
- 204
- On GitHub
- Licence
- MIT
- Allows business use
- Downloads for
- None listed
- No release files
- Latest version
- None yet
- No releases
- Built with
- Python
- 93% of the code
Is it looked after?
- Contributors
- 0
- Last 90 days
- Issues
- 0% closed
- 2 still open
- Pull requests
- 0 merged
- 1 waiting
- Releases
- None
- Never published
- No contributing guide
- No security policy
- No code of conduct
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More: languages, topics and project record
Languages
- Python 93%
- TeX 6%
- Shell 1%
- Makefile <1%
Topics
- compression
- kv-cache
- large-language-models
- llm-inference
- machine-learning
- pytorch
- quantization
- research-paper
- spectral-analysis
- transformer
Project record
- JobLocal LLMs
- StatusListed
- Commits4
- Forks24
- Watching2
- Stars in 28 days+1
- CreatedApr 5, 2026
- First seen by usNov 7, 2026
- CheckedNov 7, 2026