--- title: "Caveman comparisons" description: "Caveman comparisons for LLM gateways, prompt compression, model routing, and agent observability. See where each tool fits and what changes when you add Caveman." canonical: https://caveman.so/compare last-updated: 2026-09-07 --- # Caveman comparisons Caveman comparisons for LLM gateways, prompt compression, model routing, and agent observability. See where each tool fits and what changes when you add Caveman. - [Caveman vs AgentOps for multi-agent costs](https://caveman.so/compare/agentops): Compare AgentOps agent tracking with Caveman context compression and its private Platform. Follow handoffs, repeated context, retries, and full-task cost. - [Caveman vs Arize Phoenix for LLM tracing and optimization](https://caveman.so/compare/arize-phoenix): Compare Arize Phoenix tracing and evaluations with Caveman local compression and its private Platform. Inspect data boundaries, task quality, and cost evidence. - [Caveman vs Bifrost for AI gateway and agent costs](https://caveman.so/compare/bifrost): Compare Bifrost gateway infrastructure with Caveman recoverable context compression. Separate gateway overhead, caching, governance, and complete agent-task cost. - [Caveman vs Braintrust for agent evaluation and cost improvement](https://caveman.so/compare/braintrust): Compare Braintrust evaluations, observability, and Loop with Caveman compression and its private Platform. Choose using task outcomes and complete cost evidence. - [Caveman vs Cloudflare AI Gateway for agent costs](https://caveman.so/compare/cloudflare-ai-gateway): Compare Caveman and Cloudflare AI Gateway on caching, local compression, deployment, and agent-cost measurement. See what each layer can change. - [Caveman vs Headroom for recoverable context compression](https://caveman.so/compare/headroom): Compare Caveman and Headroom on recovery, storage limits, agent setup, and a published benchmark. Choose using complete tasks, not payload ratios. - [Caveman vs Helicone for agent observability and costs](https://caveman.so/compare/helicone): Compare Caveman and Helicone on gateway logging, agent usage, context compression, and the work required to evaluate an optimization. - [Caveman vs Langfuse for agent costs and observability](https://caveman.so/compare/langfuse): Compare Langfuse tracing, prompt management, and evaluations with Caveman context compression and its private Platform. Decide what to keep and what to test. - [Caveman vs LangGraph: graph execution and cost evidence](https://caveman.so/compare/langgraph): Compare LangGraph durable agent execution with Caveman observation and compression. Understand checkpoints, JavaScript adapter limits, usage gaps, and migration scope. - [Caveman vs LangSmith for agent evaluation and optimization](https://caveman.so/compare/langsmith): Compare LangSmith tracing, evaluation, and agent improvement with Caveman local compression and its private Platform. Keep graph execution and cost evidence clear. - [Caveman vs LiteLLM: keep your gateway, cut agent waste](https://caveman.so/compare/litellm): Compare Caveman and LiteLLM for agent costs, local compression, routing, and traces. Learn when to keep LiteLLM and where Caveman adds value. - [Caveman vs LLMLingua for prompt compression](https://caveman.so/compare/llmlingua): Compare Caveman with Microsoft LLMLingua on learned compression, local tool output, recovery, runtime cost, and integration effort. - [Caveman vs Martian for model routing and agent costs](https://caveman.so/compare/martian): Compare Caveman with Martian Gateway and routing on model access, local compression, gateway integration, and complete-task evaluation. - [Caveman vs Mastra: agent runtime, processors, and cost evidence](https://caveman.so/compare/mastra): Compare Mastra agent and workflow execution with Caveman native processors. See what the adapter observes, where context changes belong, and what remains experimental. - [Caveman vs Not Diamond for model routing](https://caveman.so/compare/not-diamond): Compare Caveman and Not Diamond on model selection, prompt optimization, cache effects, and the evidence needed to lower agent-task cost. - [Caveman vs OpenRouter for AI agent costs](https://caveman.so/compare/openrouter): Compare Caveman and OpenRouter on model access, context compression, billing, and agent workflows. See what changes if you keep or replace the gateway. - [Caveman vs Portkey for AI cost optimization](https://caveman.so/compare/portkey): Compare Caveman and Portkey on gateway controls, guardrails, local compression, and agent-cost investigation. Find the right first experiment. - [Caveman vs PromptLayer for prompts, evaluations, and agent costs](https://caveman.so/compare/promptlayer): Compare PromptLayer prompt and workflow management with Caveman context compression. Understand runtime dependencies before planning a private Platform migration. - [Caveman vs Pydantic AI for typed agents and context costs](https://caveman.so/compare/pydanticai): Compare Pydantic AI Python agents with Caveman local compression and its TypeScript SDK. Understand validation, context management, integration boundaries, and migration effort. - [Caveman vs RouteLLM for cost-aware model routing](https://caveman.so/compare/routellm): Compare Caveman and RouteLLM on router evaluation, model pairs, gateway integration, and the extra costs of long-running agent tasks. - [Caveman vs RTK for coding-agent token costs](https://caveman.so/compare/rtk): Compare Caveman and Rust Token Killer on command output, request context, recovery, and token reporting. Pick the boundary that matches your agent. - [Caveman vs Vercel AI Gateway for agent efficiency](https://caveman.so/compare/vercel-ai-gateway): Compare Caveman and Vercel AI Gateway on model access, local compression, AI SDK integration, and total agent-task cost. - [Caveman vs Vercel AI SDK: keep the agent, add cost evidence](https://caveman.so/compare/vercel-ai-sdk): Compare Vercel AI SDK agent execution with Caveman adapters and local compression. Understand middleware, usage gaps, exact version support, and evaluation limits.