repoGitHubTrust 82 · PrimaryPublished 19h agoLive · 19h ago
Tylogi/TyloQuant
Get more intelligence from every bit. Better quantization formats and smarter calibration let larger, stronger models run smoothly on the hardware you already own.
Lineage graph
Paper → model → repo connections mined from source citations (Tier-1 exact match).
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Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- PossiblePossibly related (embedding) · 49%I feel like I'm not using my hardware efficiently →
- PossiblePossibly related (embedding) · 48%Qwen 3.6 27B Speculative Decoding Bench: Pushing ~100 TPS on a single RTX 3090 →
- PossiblePossibly related (embedding) · 48%Local benchmarks with a RTX 3090 - Qwen3.6 27b vs Ornith →
Covers
newsI feel like I'm not using my hardware efficientlynewsQwen 3.6 27B Speculative Decoding Bench: Pushing ~100 TPS on a single RTX 3090newsLocal benchmarks with a RTX 3090 - Qwen3.6 27b vs OrnithnewsIf you are at the lowest budget, which you can think of.Which hardware would you recommend to run? qwen 3.8 27b oWith like 50 tokens per second. I currently have a RTX 5070 Ti.
Related across the graph
newsQwen 3.6 27B Speculative Decoding Bench: Pushing ~100 TPS on a single RTX 3090newsIf you are at the lowest budget, which you can think of.Which hardware would you recommend to run? qwen 3.8 27b oWith like 50 tokens per second. I currently have a RTX 5070 Ti.newsI feel like I'm not using my hardware efficientlynewsLocal benchmarks with a RTX 3090 - Qwen3.6 27b vs Ornith