About Tokenwise
Overview
Tokenwise is an AI cost and performance copilot that watches every LLM call through a drop-in edge proxy, reporting cost, latency, errors, and quality in real time. It claims to cut LLM API bills by 20–30% without touching output quality.
Setup takes one line of code: point your app's base URL at proxy.tokenwisehq.com and keep using your existing SDK. The proxy adds under 50 ms of overhead, never stores provider keys, and runs observe-only by default so production stays unchanged.
Key Benefits
- Monitor every call from your app and agents with cost, latency, errors, and tokens sliced by model, app, or tag, plus a 14-day spend forecast.
- Optimize with one-click fixes: model swaps, semantic caching, and prompt trims, each replay-checked against your own quality baseline before applying.
- Protect with cost spike, latency regression, and quality dip alerts routed to email, Slack, or Discord, and budget caps that auto-roll back to the last known-good config.
- One base URL routes to OpenAI, Anthropic, Google Gemini, xAI Grok, and more through the Vercel AI SDK, LangChain, or plain SDKs with no code rewrites.
- Keep data private with prompts and cached completions encrypted at rest, provider keys dropped from memory, and opt-out payload storage per workspace or tag.
How It Works
Plug in one line by pointing your app at the drop-in proxy with an X-Tokenwise-Key header, then watch the dashboard identify oversized prompts, cache misses, and expensive models doing cheap work. Apply the one-click fixes — model swaps, caching, prompt trims — that pass your replay quality checks, or ignore them; nothing changes silently.
Use Cases
- Solo makers shipping LLM apps use the Indie tier to watch spend and apply optimization recommendations without touching code.
- Small teams running LLMs in production use Pro tier alerts, LLM-as-judge evals, and A/B traffic splits before switching models.
- Apps on the Vercel AI SDK or OpenAI client swap their base URL to log, price, and optimize every call in one line.
- Teams using LangChain or plain fetch() and cURL get copy-paste onboarding snippets for each SDK.
- Workspaces with $50–$2,000 monthly LLM bills use Tokenwise to name each leak with the dollar figure attached and the fix next to it.
Why Choose This Product
Tokenwise positions itself against Helicone, Langfuse, and LangSmith with a 5-minute one-URL setup, one-click fixes that need no redeploy, built-in A/B experiments with auto-rollback, and a semantic cache at the edge. It reports median 37 ms proxy overhead across 300+ Cloudflare POPs and has been routing 1.2 billion tokens a month for 48 teams.
Key Capabilities
- Median proxy overhead of 37 ms, p95 under 50 ms, with Cloudflare Workers in 300+ cities.
- Provider keys never persisted — forwarding drops them from memory and payload storage is opt-out.
- Public REST API with tw_api_* keys for workspaces, requests, metrics, and evals.
- 48 teams already route 1.2 billion tokens a month through the service.
Tokenwise Pros & Cons
- One-line drop-in proxy setup in about 5 minutes
- Median 37 ms overhead with p95 under 50 ms
- 20–30% cost cut claims with quality replay checks
- Prompts encrypted at rest and provider keys never stored
- 7-day free trial with no credit card required
Key Features
Drop-in proxy
A drop-in proxy at the edge lets you swap your base URL and log every LLM call without SDK rewrites or redeploys.
Real-time observability
Real-time dashboards show cost, latency, errors, and tokens per call, sliced by model, app, or tag, with a 14-day forecast.
One-click optimizations
One-click fixes such as model swaps, semantic caching, and prompt trims are replay-checked against your quality baseline before apply.
LLM-as-judge evals
LLM-as-judge evals score recent prompts on candidate models, reaching a 96.4% quality match in live testing.
Spike alerts
Cost spikes, latency regressions, and quality dips route to email, Slack, or Discord before they hit your bill.
Auto-rollback watchdog
Budget caps auto-roll back to the last known-good config when spend or quality thresholds are crossed.
Semantic cache
Semantic caching at the edge responds with cached output for near-identical calls instead of re-billing full price.
A/B experiments
A/B traffic splits via proxy rules let you test 5–50% of traffic on a new model with auto-rollback protection.
Weekly insights
A weekly insights email in your timezone summarizes where to save money, with savings already estimated.
Public REST API
A public REST API with tw_api_* keys exposes workspaces, requests, metrics, and evals data.
Tokenwise Pricing
View full pricing →- 200,000 requests per month
- 10 workspaces
- 60-day request retention
- Dashboard, requests log, and What changed
- Cost and latency spike alerts via email
- Weekly insights digest with optimization recommendations and semantic cache
- 2,000,000 requests per month — 10x Indie
- 50 workspaces and 4 role tiers
- 180-day request retention
- LLM-as-judge eval engine and interactive rescore
- A/B traffic splits via proxy rules
- Quality regression detector and auto-rollback watchdog
| Feature | Indie $9.50/mo | Pro $39.50/mo |
|---|---|---|
| 200,000 requests per month | ||
| 10 workspaces | ||
| 60-day request retention | ||
| Dashboard, requests log, and What changed | ||
| Cost and latency spike alerts via email | ||
| Weekly insights digest with optimization recommendations and semantic cache | ||
| 2,000,000 requests per month — 10x Indie | ||
| 50 workspaces and 4 role tiers | ||
| 180-day request retention | ||
| LLM-as-judge eval engine and interactive rescore | ||
| A/B traffic splits via proxy rules | ||
| Quality regression detector and auto-rollback watchdog |
Pricing extracted from the product website and may change. Check the source for current details.
Frequently asked questions about Tokenwise
Who is Tokenwise for?
Developers and small teams running LLM features in production: apps and SaaS that call OpenAI, Anthropic, Google, or other model APIs through the Vercel AI SDK, LangChain, or a plain SDK. If your monthly LLM bill is between $50 and $2,000, Tokenwise is built for you.
Which providers work?
Native path providers: OpenAI, Anthropic, Google Gemini (OpenAI-compatible shim), xAI Grok, Groq, DeepSeek, Mistral, and OpenRouter, which adds 200+ more. On the SDK side, the openai SDK, @anthropic-ai/sdk, ai (Vercel), langchain, plain fetch(), and cURL all work, with copy-paste onboarding snippets.
What happens to my API keys?
They stay in your environment. The proxy forwards your provider key upstream and drops it from memory — never persisting them in databases, logs, or backups. Request metadata is always logged, while full payload storage is on by default and can be turned off per workspace or per tag.
How fast is the proxy?
Median overhead is 37 ms with p95 under 50 ms, served via Cloudflare Workers in 300+ cities. Since the LLM response itself takes 400 to 2,000 ms, the proxy sits in the noise.
What if quality drops after a model switch?
Every recommendation is evaled before it goes live. LLM-as-judge scores recent prompts on the new model, and you can apply directly, run an A/B on 5 to 50% of traffic, or let Watchdog auto-rollback if scores drop more than 10%.
How does the trial work?
No card to start. You get 7 days of full Indie access, and after day 7 the dashboard prompts you to subscribe. The proxy keeps forwarding so your app stays up while you decide.
How Tokenwise compares
TokenwiseThis | ||||
|---|---|---|---|---|
| Starting price | $9.50/mo | Free | — | Free |
| Pricing model | Freemium | Freemium | unknown | Freemium |
| Platforms | Web | — | — | — |
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