archify vs Paritok: Features, Pricing & Which Is Better (2026)
A side-by-side comparison of archify and Paritok — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.
a
archify
tt-a1i
Agent skill for Claude, Codex, and opencode that turns a plain-English description into a polished, themeable architecture diagram in a single HTML file.
Key features
- Prompt-to-Diagram: Describe your system in English and get a polished technical diagram back.
- Multiple Diagram Types: Handles architecture, workflow, sequence, data-flow, lifecycle, CI/CD, and state-machine diagrams.
- Single-File HTML Output: Diagrams are self-contained HTML files you can open, share, or embed anywhere.
- Dark / Light Theme Toggle: One-click theme toggle inside the diagram, with the choice persisted across sessions.
- Multi-Format Export: Copy PNG to clipboard plus download as PNG, JPEG, WebP, or SVG at up to 4x source resolution.
- Semantic Tech Labels: Recognizes labels like aws.lambda, postgres, redis, github-actions, openai and maps them to the right visual category without a manual icon library.
- Multi-Agent Compatibility: Installs as a skill for Claude, Codex CLI, and opencode with a single command.
Best for
- System Design Sketches: Turn a rough design description into a shareable architecture diagram in minutes.
- Runbook & Incident Docs: Generate sequence and data-flow diagrams for runbooks and incident reviews on the fly.
- CI/CD Documentation: Draw pipeline and workflow diagrams from an English description of your build/deploy flow.
- Onboarding Materials: Produce lifecycle and request-chain diagrams to onboard new engineers to a service.
- Slide-Ready Visuals: Export high-resolution PNG or SVG diagrams straight from your agent for decks and blog posts.
P
Paritok
Paritok
Non-destructive compression gateway that drops between coding agents and LLMs to cut input tokens by up to 85% without changing the agent.
Key features
- Drop-In Gateway: One environment variable (ANTHROPIC_BASE_URL) reroutes your agent through Paritok — no agent, prompt, or tool changes.
- Tool Schema Compression: 46-schema tool blocks (~29K tokens) drop to ~8K per turn by keeping relevant tools and stubbing the rest, frozen per conversation for cache stability.
- Code-Native 4B Model: A 4B compression model trained on 45K real agent trajectories keeps identifiers, paths, and errors while shrinking file reads and outputs to ~26% of original.
- read_original Recall: Every compressed segment is tagged; the agent asks read_original(ref) and gets the exact bytes locally without spending an extra turn.
- Stale History Summarization: Turns beyond a configurable recent window get summarized once when your context budget fills, so recent turns stay pristine and overflows drop to zero.
- Multi-Agent Compatibility: Works today with Claude Code, Cursor, Codex, OpenHands, and any OpenAI-compatible upstream — Anthropic and OpenAI both supported.
- Compounding Savings: Saved share grows across a session — 25% at 1 turn, 54% at 10 turns, 63% at 20 turns — against a 96,500-token baseline.
- Open Weights and Benchmark: SWE-bench Lite floor of 86.5% quality retained at 25.7% compression rate, with weights and training pipeline published.
Best for
- MCP-Heavy Workflows: Cut input bills for agents that ship 70+ MCP tool schemas on every turn.
- Long Coding Sessions: Run 3× longer coding-agent sessions before context saturation forces a hard compact.
- Bill Reduction: Estimate 54% off input tokens on a 5-developer team at 20-turn Claude Sonnet sessions (~$6,550/year).
- Self-Hosted Privacy: Route agent traffic through your own hardware with no data leaving your network — 8GB GPU is enough.
- Enterprise Cost Governance: Add compression at the gateway layer so all coding agents on the team benefit without engineering per-agent.
- Cursor/Codex/Claude Code Fleet: Standardize compression across a mixed toolchain of coding agents behind one gateway.