Caveman vs NoMac: Features, Pricing & Which Is Better (2026)

A side-by-side comparison of Caveman and NoMac — features, pricing, and ideal use cases — to help you decide which AI tool fits your workflow.

Caveman

Julius Brussee

Freemium

Efficiency stack that caches, compresses, and routes AI traffic to cut LLM output tokens by up to 65% with verified savings.

Caveman Skill: MIT-licensed Claude Code skill that teaches 30+ agents (Claude Code, Codex, Cursor, and more) to answer in a compressed dialect, cutting output tokens ~65% while keeping code and errors byte-exact.
Local Proxy Wrap: One command (`caveman claude`) launches your agent with recoverable local context compression — no account required, BYOK, engine stores original bytes before lossy replacement.
Recoverable Context Compression: Engine recognizes logs, JSON, code, diffs, and tables, then sends smaller eligible context to the model and can restore the originals on demand.
Agent SDK: `@caveman-ai/agent` TypeScript SDK adds catalog-price guards, per-request token bills, and eval-gated context plans to production agents.
Cave Score & Ledger: Inferred local savings score and a verified 'causal-cache' ledger on paid tiers so you can prove cut tokens and cut dollars.
Managed Cloud Gateway: Point traffic at one URL and caching / compression / routing run eval-gated on autopilot, with a synced savings dashboard.
Browser Extension: Ships for ChatGPT, Claude, and Gemini so end-user chats benefit from the same output compression without any code changes.
Enterprise & OEM: Same stack self-hosted in your cloud or datacenter with signed savings receipts, zero data retention, and OEM embed options.

LLM Bill Reduction: Cap OpenAI, Anthropic, or Google spend without changing model choice by cutting output tokens per response across your agent fleet.
Coding Agent Efficiency: Install the skill to make Claude Code, Codex, Cursor, and other CLI agents produce terse, byte-exact answers so long tasks fit in context.
Provider Wrap for Production Agents: Use the SDK to add per-call token bills, catalog-price guards, and eval-gated context plans to LangChain / custom agents.
Central Cost Gateway: Point every agent in the org at Caveman Cloud so caching and routing are enforced from one URL with a shared dashboard.
On-Prem or OEM Embed: Ship the Enterprise stack inside a regulated network or embed it in your own AI product with signed savings receipts and zero data retention.
Chat-App Compression: Install the browser extension for ChatGPT, Claude, or Gemini to keep casual chats short, cheaper, and inside the context window.

Paid

Cloud-based iOS build, TestFlight, and App Store submission pipeline that AI agents can drive through a CLI or MCP — no Mac required.

Cloud-Mac Signed Builds: Produces signed iOS release builds on remote Macs so developers never need Xcode or local certificates.
TestFlight Preview in Minutes: Uploads and distributes builds to TestFlight, delivering the app to your iPhone in about three minutes.
Automated App Store Submission: Handles metadata, screenshots, review-readiness checks, and the actual App Store submission call.
MCP Server for Agents: Ships a Model Context Protocol server that any MCP-speaking agent (Claude Code, Codex, Cursor) can drive end-to-end.
CLI and HTTP API: Offers npx @nomac/cli plus a public API for agents or scripts that prefer not to use MCP.
Certificate and Signing Autopilot: Manages provisioning profiles, signing identities, and API-key rotation without exposing your Apple ID password.
Crash and Feedback Loopback: Crashes and tester feedback flow back to the calling agent so it can iterate without a human copy-paste step.
Setup Wizard: Walks through the one-time Apple gates (Developer account, App Store Connect API key, App Privacy form) and verifies each step live.

Solo Indie Development: Ship iOS apps from a Windows or Linux machine without buying a Mac.
Agent-Driven Releases: Let a Claude Code or Codex agent handle the whole build-test-submit loop while the developer supervises.
Continuous Delivery: Push every merge to TestFlight automatically for internal QA and beta feedback.
AI-Generated Apps: Use it as the deployment leg for AI-built mobile apps that need to land on the App Store.
Cross-Platform Teams: Give backend or web engineers a hands-free path to publish an iOS build without Xcode expertise.
Rapid Prototyping: Iterate on iOS prototypes and ship them to real devices in minutes rather than hours.