LangSmith alternative
A LangSmith alternative without the per-seat tax
LangSmith bills per seat and shines inside LangChain. Tokenwise is usage-based, works with any OpenAI-compatible stack in one line, and is built to lower your bill — not just trace it.
Where they differ
LangSmith is best-in-class for debugging LangChain/LangGraph agents, but it’s closed-source, priced per seat, and gives auto-tracing mainly inside the LangChain world. Tokenwise is for makers on the Vercel AI SDK, the raw OpenAI/Anthropic SDKs, or cURL who want costs down with no instrumentation.
If you live in LangChain and your main problem is debugging agent traces, LangSmith is a strong tool. This page is for everyone else: small teams who feel the per-seat pricing, or makers who aren’t on LangChain and don’t want to hand-instrument every call.
Tokenwise charges at the owner level, not per chair, so you can invite your whole team on one $19 plan. It auto-captures across eight providers from a single baseURL change, and its job is to make the bill smaller — something LangSmith doesn’t do at all.
LangSmith vs Tokenwise
| Tokenwise | LangSmith | |
|---|---|---|
| Pricing model | Owner-level / usage-based — whole team for $19 | $39 per seat / mo |
| Setup | baseURL swap, auto-captures 8 providers | SDK wrap; auto-tracing best inside LangChain |
| Framework | Any OpenAI-compatible stack | LangChain-house (others via manual OTel) |
| Free / entry retention | 60 days on the $19 Indie tier | 14 days on the free tier |
| Cost optimization | Model-switch, cache, verified savings | No cost-optimization layer |
| Best for | Cutting your LLM bill | Agent trace debugging & evals |
| Source | Cloud | Closed-source |
No wrapping, no per-seat math
LangSmith’s best experience needs LangChain or manual instrumentation. Tokenwise captures everything from one baseURL, whatever SDK you use.
Before — LangSmith
import { wrapOpenAI } from "langsmith/wrappers";
import OpenAI from "openai";
// LANGCHAIN_TRACING_V2=true, billed per seat
const openai = wrapOpenAI(new OpenAI());After — Tokenwise
import OpenAI from "openai";
const openai = new OpenAI({
baseURL: "https://proxy.tokenwisehq.com/openai/v1",
defaultHeaders: { "X-Tokenwise-Key": "tw_..." },
});When LangSmith is the better choice
- You’re all-in on LangChain/LangGraph. The native integration and agent trace debugging are best-in-class there.
- Deep eval workflows are your priority.LangSmith’s eval and dataset tooling is more extensive than Tokenwise’s maker-grade evals.
- Otherwise, if you want framework-agnostic capture, team-friendly pricing, and a tool that actually lowers your spend, Tokenwise fits better.
Frequently asked
Does Tokenwise work without LangChain?
Yes — that's the point. It's a baseURL swap on the OpenAI SDK, Anthropic SDK (JS + Python), Vercel AI SDK, or cURL, and it auto-captures across 8 providers with no manual instrumentation.
How does the pricing compare for a team?
LangSmith is $39 per seat — a 5-person team is ~$195/mo before overage. Tokenwise is owner-level: invite the whole team on the $19 Indie plan or $79 Pro, with no per-seat charge.
Will Tokenwise help me debug agents?
Tokenwise gives you full request payloads, prompt grouping, and a requests drawer, which covers most debugging. For deep step-by-step LangChain agent tracing, LangSmith goes further — they're optimized for different jobs.
Does Tokenwise reduce cost or just show it?
It reduces it: model-switch recommendations, semantic caching, fallback chains, and A/B traffic splits, with the savings verified against your real traffic. LangSmith records traces but doesn't optimize cost.
It’s a one-line change
Point your baseURL at Tokenwise, keep your keys and your code, and get a weekly email with the changes that cut your bill — proven on your own traffic before we recommend them.