STEPQuant
STEPQuant: When and Where Errors Matter in Delta-Rule Recurrent State Quantization
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GITHUB · launched Sep 29, 2026 · 57 upvotes (top 15%) · 1 view
Niche: machine learning developer tools · 303 launches, 16 in the last 7 days ▼ -6% · Explore this niche →
Category and tags
- Horizontal
- Model & infra
- Developer
- AI-native
- Hobby / open-source project
- large-language-models
- llm
- post-training-quantization
- quantization
Visit website ↗ Source listing ↗
More like this: all 303 launches in machine learning developer tools →
Could you build this?
No This is academic machine learning systems research involving novel mathematical formulations for recurrent state quantization and custom GPU kernel implementations in SGLang.
What it would actually take: Building this requires deep expertise in linear attention mechanics, numerical precision quantization, and low-level GPU programming. The stack involves PyTorch, CUDA/Triton custom kernels, and deep integration into modern LLM inference engines like SGLang or vLLM. It necessitates benchmarking against large open-weight models (e.g., Qwen and Kimi architectures) on high-end GPU clusters.
Competitors
Other products that read as similar to this one : 2037 launches clear the similarity bar, closest 8 shown.
Attention rank: #305 of 2038 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 334 days after the earliest competitor.
- LeapQuant · github · 2026-11-11 · 50 upvotes · similarity 0.72
- hope · github · 2026-10-27 · 26 upvotes · similarity 0.61
- QUAN-Transcribe · github · 2026-10-14 · 27 upvotes · similarity 0.59
- zero2vllm · github · 2026-10-12 · 14 upvotes · similarity 0.57
- Remory · github · 2026-10-07 · 43 upvotes · similarity 0.56
- TurboQuant-WASM · hn · 2026-04-04 · 165 upvotes · similarity 0.56
- TurboQuant · ph · 2026-03-25 · 295 upvotes · similarity 0.55
- open_rknpu2_lm_infer · github · 2026-10-14 · 13 upvotes · similarity 0.55
The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.