---
title: "Caveman vs Vercel AI SDK: keep the agent, add cost evidence"
description: "Keep Vercel AI SDK if you want its provider interfaces, streaming tools, and agent loop. Caveman's native adapter attaches to that loop to observe usage and expose a request transformation hook. It is"
canonical: https://caveman.so/compare/vercel-ai-sdk
last-updated: 2026-09-07
---

# Caveman vs Vercel AI SDK: keep the agent, add cost evidence

Keep Vercel AI SDK if you want its provider interfaces, streaming tools, and agent loop. Caveman's native adapter attaches to that loop to observe usage and expose a request transformation hook. It is an addition to the framework, not a replacement UI or runtime.

Choose the Caveman Agent SDK itself only if you want to author agents against its own contract. That is a separate migration decision from adding the AI SDK adapter.

## What each layer owns

| Responsibility | Owner with the native adapter |
| --- | --- |
| Agent loop, tools, retries, and streaming | Vercel AI SDK |
| Provider model and credentials | Your existing model client |
| Request middleware seam | Caveman adapter on the wrapped model |
| Usage normalization | Caveman observations from native evidence |
| Context transformation policy | Middleware you explicitly supply |
| Budget enforcement | Not supplied by the adapter |

[AI SDK](https://ai-sdk.dev/docs/introduction) is a TypeScript toolkit for building AI applications. The [Caveman adapter source](https://github.com/caveman-ai/agent-sdk/tree/main/packages/adapters/vercel-ai-sdk) targets `ai@7.0.84` exactly. That pin describes supported integration evidence, not a claim about the latest AI SDK release.

## The useful difference is visible uncertainty

A framework can provide token usage without providing every cache or reasoning field. Filling missing values with zero makes a record look more complete than it is.

Caveman's adapter keeps missing counters as unknown and separates non-cached input, cache reads, cache writes, and output when the source supports that separation. This is useful when you compare models or providers whose usage objects have different meanings.

It does not turn those records into verified savings. An incomplete record remains incomplete, and a complete but unpriced model is still unpriced. Use [the measurement guide](/guides/measure-agent-cost) when aggregating multiple calls into a task.

## An empty boundary does not compress anything

The model boundary lets your code inspect and return a transformed request before the native provider call. It does not ship an automatic compression policy merely because you instantiate the adapter.

Start with observation. Then add one tested transformation if you need it. Preserve tool identifiers, multimodal content, structured-output constraints, and any data required by the next step. The framework still owns model I/O and retries.

If your goal is reducing context in a coding agent you did not build, the [local CLI path](/guides/coding-agent-setup) may be the smaller experiment. That proxy path and the native adapter solve different integration problems.

## Check support before adding it to production

The adapter's capabilities are experimental and its certification map is empty. Tracing, durable observation, replay awareness, and compilation are unsupported. The native seam also does not prove every run-error lifecycle event.

The source SDK API is newer than the published npm SDK at this review. Follow [the source setup guide](/guides/agent-sdk-migration); do not assume installing the latest registry package supplies these exports.

## When Caveman earns its place

Add Caveman when you need consistent usage records with explicit gaps, or a controlled request hook inside an existing AI SDK agent. Keep upstream execution and use the same tests to judge any context change.

A full runtime migration needs a stronger reason, such as adopting Caveman's agent definition and build workflow. Do not rewrite a working streaming application merely to collect token counts.

The [AI SDK switching guide](/switch/vercel-ai-sdk) shows the adapter attachment, callback composition, stream checks, and rollback. For the hosted gateway product, read [Caveman vs Vercel AI Gateway](/compare/vercel-ai-gateway) instead.