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pi extension to spend 14x less tokens and achieve 798x more TPS
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GITHUB · launched Sep 19, 2026 · 18 upvotes (top 43%) · 0 views
Niche: llm inference and deployment tools · 188 launches, 6 in the last 7 days · Explore this niche →
Category and tags
- Horizontal
- Model & infra
- Developer
- AI-native
- Hobby / open-source project
Visit website ↗ Source listing ↗
More like this: all 188 launches in llm inference and deployment tools →
Could you build this?
Partial Creating a small plugin or script for an agent harness is straightforward, but achieving extreme token compression and massive TPS improvements relies on sophisticated prompt distillation, speculative decoding, or token cache tricks.
What it would actually take: This project likely implements an aggressive prompt/context optimization strategy (e.g., custom token stripping, semantic prefix reuse, or speculative tool calling) for an agent framework. Building a production version requires deep profiling of model tokenizers, inference server endpoints (vLLM/llama.cpp), and rigorous benchmarking to ensure response fidelity does not collapse under extreme token compression.
Competitors
Other products that read as similar to this one : 1295 launches clear the similarity bar, closest 8 shown.
Attention rank: #539 of 1296 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).
Launched 323 days after the earliest competitor.
- pi-extensions · github · 2026-10-20 · 45 upvotes · similarity 0.53
- Finite · hn · 2026-01-18 · 5 upvotes · similarity 0.52
- pi-pocket · github · 2026-10-04 · 269 upvotes · similarity 0.52
- pi-optchat · github · 2026-10-04 · 193 upvotes · similarity 0.52
- keephaven · github · 2026-09-25 · 43 upvotes · similarity 0.51
- pi-extensions · github · 2026-10-03 · 20 upvotes · similarity 0.51
- RTI · github · 2026-09-10 · 14 upvotes · similarity 0.50
- moegpi · github · 2026-09-16 · 11 upvotes · similarity 0.49
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.