Paritok
Spend up to 85% less and run 3x longer coding agent sessions
A non-destructive compression gateway for coding agents. Paritok sits between the agent and the LLM provider: tool schemas are filtered (29K to 8K tokens/turn cited), file reads and command output are summarized (to ~26% of original), and stale conversation history is summarized with recoverable references. Compression is done by a purpose-built 4B model trained on real agent trajectories. Drop-in via a single environment variable. Self-hosted build is Apache-2.0; a hosted GPU endpoint is also offered.
What is Paritok?
Paritok is a non-destructive compression gateway that sits between a coding agent and its LLM provider, filtering tool schemas and summarizing file reads and history to cut token spend before requests leave the machine.
Key features
- Tool-schema filtering (cited: 29K → 8K tokens/turn)
- File read and command output summarization (to ~26% of original)
- Stale history summarized with recoverable references, not discarded
- Compression handled by a purpose-built 4B model trained on agent trajectories
- Drop-in integration via a single environment variable
- Apache-2.0 self-hosted build; hosted GPU endpoint also offered
Who it's for
- Coding agent sessions that hit context limits before the task is finished
- Teams trying to reduce Claude Code / Codex token spend
- Anyone who wants to self-host and independently verify a vendor's compression claim
When not to use it
Short, single-file agent sessions have little to compress, so the benefit is marginal there.
FAQ
Is the 85% savings figure independently verified?
No — it's the vendor's own claim. The gateway is Apache-2.0 and self-hostable, so users can measure their own before/after token counts.
Can compressed content be recovered?
Yes — compressed spans keep reference tags so the agent can pull the original content back when needed.
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