Launching today
Paritok
Spend up to 85% less and run 3× longer coding agent sessions
87 followers
Spend up to 85% less and run 3× longer coding agent sessions
87 followers
Paritok compresses the tools, files, and history your coding agent sends. Save up to 85% on your token bill and run 3× longer sessions. Two commands, nothing lost, fully local.
Paritok
Hey PH community!
We're Jiayu and Luzhuo, two engineers who got tired of watching our coding agents burn through tokens.
Here's what we kept seeing: your agent ships far more than the model actually needs. Full JSON for seventy tools when it will call two. An entire file when it needed one function. Debug output nobody will ever read again. And because the API is stateless, all of it goes back on every single turn, so the waste doesn't just cost you once, it compounds.
So we built Paritok, a non-destructive compression gateway powered by a code-native 4B model we trained on 45K real agent trajectories. It sits between your agent and the API and cuts three things before they leave:
• Tool schemas — 29K down to 8K per turn, no model involved, this one runs on CPU
• File reads and tool output — compressed to about a quarter of their size
• Stale history — turns beyond a recent window get summarized once your context budget fills, so the session never overflows into a lossy compaction
With Paritok, you can cut your token bills 25% on turn 1 to past 85% in long or saturated sessions, and run ~3× more turns in the same context window. Paritok now works with Claude code, Codex, Cursor, and anything OpenAI or Anthropic compatible.
Paritok will continue to enhance functionality and adapt user scenarios, while deepening its model capabilities.
We’re excited to share this with the PH community and would love your honest feedback.
Try Paritok: https://www.paritok.com/
Join our Discord to talk with the team: https://discord.gg/SeBJE5Eucp
Thanks for checking us out, and huge thanks to our hunter Chris Messina for hunting us!
— Jiayu & Luzhuo
AdAnt AI
@jazzwind Congrats on the launch! Very useful and interesting product~ I am highly rely on my coding agents for everything, will try it out.
Paritok
@iris_tu Thanks Iris!
Triforce Todos
Paritok
@abod_rehman Thanks Abdul, great question!
Quick clarification: the "past 85%" number is the total end-to-end saving for context-saturated deployments specifically. It splits into two mechanisms:
1. Tool schema filter
2. 4B model compression which covers file reads + tool results + stale history summaries. All three go through the same [REF:id] path and share the same stats bucket.
Split of the total saving by config:
Default (~40 tools):
- Turn 1: tool filter 86% / 4B 14%
- Turn 5: tool 56% / 4B 44%
- Turn 15+: tool 37% / 4B 63%
MCP-heavy (70+ tools), turn 20: tool filter 57% / 4B 43%, because tool filter saves ~52K per turn (60K → 8K) instead of the default ~21K per turn (29K → 8K), so tool filter shoulders more of the total.
Context-saturated: 4B compression dominates, no-Paritok baseline saturates at ~200K/turn, so there's much more content to compress relative to the fixed tool block.
Full turn-by-turn breakdown + formulas in our README Compounding section.
Thanks for the well wishes!
Mom Clock
Great job! The 3× turns per context window benefit is actually valuable to me. My Claude Code sessions hit compaction on big codebases. Excited to see how much longer they can run with this.
Paritok
@justin2025 Thanks Justin! Your Mom Clock is also a great product, will try it!
Heym
Congratulations on the launch! Context bloat is becoming a real bottleneck for coding agents, so a fully local way to compress tools, files, and history feels both practical and privacy-conscious. Looking forward to trying Paritok.
Paritok
@ceren_kaya_akgun Thanks Ceren! Really appreciate your support!
NexaSDK for Mobile
Really like this product and I went to your github. The compounding savings math in the README is refreshingly honest. This is how AI infra should be marketed.
Paritok
@power_valsha Thanks Power!
CapCut AI Suite
Non-destructive compression via a code-native 4B model is a genuinely clever architecture. Adding to my to-try list.
Paritok
@lavana_cricko Thanks Lavana!