# Caveman vs Promptr Caveman records 171,826 monthly visits with -15.5% month-over-month growth and Freemium, Contact for Pricing pricing. Promptr records 0 monthly visits with 0% growth and Pay-as-you-go pricing. | Metric | [Caveman](https://openaitools.app/tool/caveman) | [Promptr](https://openaitools.app/tool/promptr) | | :--- | :--- | :--- | | Website URL | https://caveman.so | https://promptr.dev | | Categories | AI Developer Tools, AI Agent, AI Monitor, AI Productivity Tools | Other | | Pricing Model | Freemium, Contact for Pricing | Pay-as-you-go | | Monthly Visits | 171,826 | 0 | | MoM Growth Rate | -15.5% | 0% | | Primary Market | United States | Global | | Direct Visits | 64,225 | 0 | | Review Score | 4.7 | 3.6 | | Saved Count | 0 | 1 | | Supported Platforms | Website | Website | ## Caveman Caveman addresses a very concrete problem for teams running AI agents: token bills grow faster than the value the agents produce. The core agent and SDK are free and MIT-oriented, sitting entirely on your machine or inside your production app. When a turn happens, Caveman scans logs, test output, JSON, diffs and documents, shrinks them before the model ever sees them, and keeps the original on disk so the model can ask for it when it genuinely needs the exact text. Beyond reading, Caveman also trims what the agent writes and picks the model per turn. Its output compressor strips filler prose while returning code, commands and error text byte-for-byte, and its routing layer hands each sub-agent task to the cheapest model and effort level that still gets it right. The company publishes benchmark figures such as around 33% fewer input tokens across full sessions and roughly 0.46x cost per task compared with always-frontier-model routing. Caveman Cloud is the paid, hosted layer. It watches live traffic, surfaces where tokens are still wasted, tests each proposed fix against your own work, and only then ships it with proof. The Cloud Free plan covers a single developer, Team is $300 a month with $300 of usage included, and Enterprise runs inside your own VPC via a Helm chart with your KMS and storage. **Pricing & Plans:** Freemium, Contact for Pricing [Profile (Markdown)](https://openaitools.app/tool/caveman.md) ## Promptr Promptr targets a very specific cost problem: long prompts sent to large language models are billed by the token, and repeating the same lengthy instructions hundreds of times adds up quickly. Its API takes the text of a prompt and returns a denser, compressed form that keeps the meaning while dropping redundant wording. The site's own example compresses a 136-token instruction about an AI agent designing a toy company website down to roughly 75 tokens, which it reports as a 45% reduction. Integration is deliberately minimal. You POST your prompt as a JSON string to the compress endpoint with an API token in the header, and you receive the compressed text back as plain text. Documentation provides ready-made snippets for curl, Python, JavaScript and C#, so the service can be inserted as one extra step before your existing model call. You can also control behaviour inline with tags: wrap text in a promptr compress="false" block to leave it untouched and unbilled, or set an explicit ratio such as 0.5 or 0.8 to decide how aggressively a section is shortened. The pricing page frames the value in terms of savings. At $1 per 1M input tokens processed by Promptr, it illustrates a one-off gpt-4-turbo prompt costing $10 without compression versus $7 with it, roughly 30% saved, and larger savings when a prompt is reused many times. Access currently runs through a waitlist. Because compression is lossy by nature and output quality is task-dependent, the sensible approach is to benchmark Promptr on your own prompts before rolling it out broadly. **Pricing & Plans:** Pay-as-you-go at $1 per 1M input tokens processed, with no hidden costs according to the site. Sections marked as uncompressed are not billed. Access is currently gated behind a waitlist. - **One-call prompt compression:** Send your prompt to a single REST endpoint and receive a shorter version back as plain text, ready to pass to your model. - **Up to ~40% cost savings:** The vendor reports up to 40% lower LLM input cost, with a worked example showing a 45% reduction on a sample prompt. - **Multi-language snippets:** Copy-paste examples are provided for curl, Python, JavaScript and C#, so integration takes minutes rather than days. - **Inline ratio control:** Wrap sections in tags to exclude them from compression or to set a specific compression ratio for that block. - **Uncompressed sections are free:** Text marked to be left alone is not billed, letting you protect critical instructions from being altered. **Strengths:** Simple single-endpoint API that is easy to slot into existing code; Clear, explicit pay-as-you-go price of $1 per 1M input tokens; Code snippets for four common languages reduce integration effort; Inline tags let you protect sensitive or critical text from compression **Limitations:** Access requires joining a waitlist rather than signing up directly; Compression is inherently lossy, so it can change model output quality; Real savings depend on your prompt length and reuse, so benefits must be tested case by case [Profile (Markdown)](https://openaitools.app/tool/promptr.md) ## Frequently Asked Questions ### How do Caveman and Promptr compare in monthly traffic? Caveman has 171,826 monthly visits, while Promptr has 0. Traffic estimates describe audience size, not product quality. ### How do their growth rates compare? Caveman has a month-over-month growth rate of -15.5%; Promptr has 0%. ### How does pricing compare? Caveman: Freemium, Contact for Pricing. Freemium, Contact for Pricing Promptr: Pay-as-you-go. Pay-as-you-go at $1 per 1M input tokens processed, with no hidden costs according to the site. Sections marked as uncompressed are not billed. Access is currently gated behind a waitlist. ## Alternatives | # | Tool Name | Monthly Visits | MoM Growth Rate | Pricing Model | Summary | Profile (Markdown) | | :--- | :--- | :--- | :--- | :--- | :--- | :--- | | 1 | [Orca](https://openaitools.app/tool/orca) | 1,025,891 | +1% | Free, Open Source, Enterprise on request | Runs parallel CLI coding agents in isolated worktrees, lacking dedicated context compression and cost routing tools. | [.md](https://openaitools.app/tool/orca.md) | | 2 | [Unsloth AI](https://openaitools.app/tool/unsloth-ai) | 887,457 | -17.6% | Free | Open-source, memory-efficient fine-tuning and local model running | [.md](https://openaitools.app/tool/unsloth-ai.md) | | 3 | [Augment Code](https://openaitools.app/tool/augment-code) | 326,215 | +24.1% | Freemium, Free Trial, Contact for Pricing | Provides an enterprise context engine for coding agents, but lacks open-source token compression and custom model routing. | [.md](https://openaitools.app/tool/augment-code.md) | | 4 | [Agno](https://openaitools.app/tool/agno) | 140,302 | -3.3% | Contact for Pricing, Free | Provides an open-source Python framework for building model-agnostic agents without built-in context compression. | [.md](https://openaitools.app/tool/agno.md) | | 5 | [Honcho](https://openaitools.app/tool/honcho) | 137,752 | +2.2% | Paid, Contact for Pricing | Open-source AI memory that reasons, not just stores | [.md](https://openaitools.app/tool/honcho.md) | | 6 | [Coworker AI](https://openaitools.app/tool/coworker-ai) | 129,346 | -1.8% | Free Trial, Paid, Contact for Pricing | Builds permission-aware context graphs and routes tasks to models, though targeted specifically at enterprise agent workflows. | [.md](https://openaitools.app/tool/coworker-ai.md) | | 7 | [Maxim AI](https://openaitools.app/tool/maxim-ai) | 121,351 | +10% | Contact for Pricing, Free Open Source | Offers an enterprise LLM gateway and monitoring tools, but focuses less on local context compression and agent routing. | [.md](https://openaitools.app/tool/maxim-ai.md) | | 8 | [Bito](https://openaitools.app/tool/bito) | 63,829 | +9.8% | Freemium, Paid, Contact for Pricing | Includes a context-driven model router and code review tools, but operates more as an all-around developer assistant. | [.md](https://openaitools.app/tool/bito.md) | | 9 | [Open Interpreter](https://openaitools.app/tool/open-interpreter) | 57,487 | -29% | Free | Executes language model instructions locally via terminal sandbox, without built-in token optimization or model routing. | [.md](https://openaitools.app/tool/open-interpreter.md) | | 10 | [Wokey](https://openaitools.app/tool/wokey) | 55,092 | +202.2% | Paid | One verifiable API key for Claude, GPT, Kimi and Grok at a fraction of list price | [.md](https://openaitools.app/tool/wokey.md) | --- Source: https://openaitools.app/compare/caveman-vs-promptr More Markdown: [Categories](https://openaitools.app/categories.md) · [Traffic rankings](https://openaitools.app/rankings.md) · [llms.txt](https://openaitools.app/llms.txt)