Caveman vs Forall

Caveman and Forall are both cli coding agents tracked by AIDiveForge. Below is a side-by-side comparison of pricing, capabilities, platforms, and ownership — sourced from each tool's live website and verified before publishing.

Caveman

The vendor claims roughly 65% token reduction across four compression layers — proxy, memory, code, and eval-gated rollout — without altering the bytes the model actually sees. Caveman Code is a terminal agent that plans before it ships, running one autonomous loop across 20+ providers at roughly half the token cost of comparable agents. Cavemem adds a local SQLite store with full-text search and a vector index over MCP, so agents recall prior context instead of re-sending it. The cloud gateway, which would extend these savings across any LLM traffic via a base URL swap, is waitlist-only — it is not available yet. Teams who need the proxy layer today are blocked.

Forall

Forall is an Apache-2.0 CLI agent from Astrio that generates spec-driven code alongside machine-checkable proofs, running entirely in your terminal or wiring into Cursor, Claude Code, or Codex via MCP. You describe what the code must do; the agent produces both the implementation and a formal proof you can verify independently. The verification step is not optional decoration — it runs against the spec, so a failing proof surfaces a real logical flaw before the code ships. The docs describe Rust, TypeScript, and Java as the supported targets, which covers a specific but meaningful slice of production codebases. Teams outside those languages hit a hard wall.

Attribute	Caveman	Forall
Pricing	Paid	Paid
Free trial	No	No
Open source	Yes	Yes
Has API	No	Yes
Self-hosted option	Yes	Yes
Platforms	CLI, browser extension, npm packages	CLI, terminal, MCP clients
Released	—	2026-07-17
Pros	Four-layer local compression stack reduces billed tokens without changing what the model sees, so you cut costs without introducing prompt drift or accuracy risk. Cavemem persists agent memory in a local SQLite store with vector search over MCP, which means agents stop re-sending full context on every call — the single biggest source of redundant token spend in multi-session workflows. Plan-first execution in Caveman Code means the agent ranks moves before shipping, so you avoid the costly re-run loops that happen when an agent discovers mid-task that its approach was wrong. MIT-licensed and self-hostable with no API dependency for the local stack, so your token data and agent history stay on your infrastructure rather than routing through a third-party service. Cave Architect converts live telemetry into a ranked optimization plan split by dollars-per-day and application change cost, so you prioritize the cheapest wins first instead of guessing where token waste lives.	Generates machine-checkable proofs alongside code, so correctness is verifiable by a tool rather than trusted on faith — eliminating the class of bugs that pass all tests but violate the spec. Apache-2.0 license with a self-hosted CLI path, which means the proof pipeline runs on your infrastructure without sending proprietary specs to a third-party service. MCP integration drops the agent directly into Cursor, Claude Code, or Codex via a config block, so teams avoid a context switch to a separate tool when they want verification mid-session. Spec-driven generation disciplines the coding workflow upfront, which means the spec ambiguities that normally surface in code review get resolved before the first line is written. Agentic execution runs specs-to-proof autonomously in the terminal, so verification does not require manual orchestration between separate tools for generation and checking.
Cons	The cloud gateway — the component that compresses arbitrary LLM traffic via a base URL swap across your whole stack — is waitlist-only and not available. Teams who need organization-wide compression across multiple services or providers, not just terminal agent sessions, have no path forward here and will look at alternatives that ship a working proxy today. Caveman Code is a terminal-first agent. Teams building GUI-driven workflows, notebook-based pipelines, or non-terminal agent architectures get no compression benefit from the Code layer — they are limited to the browser extension and whatever the waitlisted proxy eventually delivers. The vendor's 65% token reduction claim is stated as live and cited, but it reflects the tool's own metering on its own workloads. Teams with different prompt structures, retrieval patterns, or provider mixes will see different numbers — there is no documented methodology for estimating savings on a novel codebase before committing to integration.	Language support is limited to Rust, TypeScript, and Java — a Python, Go, or C++ team gets zero proof generation, and the vendor page describes no roadmap for expansion, leaving those teams with no path forward except switching to a different verification approach entirely. Spec-driven development requires writing formal specifications before generating code; teams without prior exposure to this discipline spend non-trivial time learning to write specs that are precise enough for the proof system to use, at which point the productivity argument against traditional TDD weakens. Teams whose correctness requirements are satisfied by property-based testing tools — like QuickCheck for Haskell or Hypothesis for Python — have an established, language-native alternative that does not require adopting a new agent layer and may switch there rather than retrofit Forall into an incompatible stack.

Bottom line

Only Forall exposes a public API. Choose based on which difference matters most for your workflow.

Frequently asked questions

What is the difference between Caveman and Forall?

Caveman is Paid and open source, while Forall is Paid and open source. Compare pricing, free trial, API, platforms, and pros/cons in the table above on AIDiveForge.

Is Caveman better than Forall?

It depends on your workflow. Use the side-by-side attributes (pricing, open source, API, self-hosted, platforms) to decide. AIDiveForge does not rank a universal winner — we publish verified facts so you can choose.