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Tokenwise

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In short

Tokenwise is an AI LLM observability tool that watches every model call for cost, latency, and quality, then cuts spend 20–30% via a drop-in proxy.

What is Tokenwise?

Tokenwise is an AI LLM observability tool that gives developers production visibility into every large language model call and then cuts spend without touching quality. It installs as a drop-in proxy with under 50ms overhead, so it tracks cost, latency, errors, and output quality in real time across providers like OpenAI, Anthropic, and Google without requiring code changes. Once it surfaces inefficiencies, Tokenwise offers one-click fixes such as model swaps, semantic caching, and prompt trimming, each replayed against a quality baseline before deployment, with automatic rollback if a regression is detected. It also supports A/B testing on live traffic and sends alerts to Slack or Discord. The product targets developers and small teams running LLM features in production with monthly bills between $50 and $2,000, and claims to reduce cost 20–30% while holding quality steady. A 7-day free trial requires no card, and early subscribers can lock in a permanent discount. For teams that want to understand and control their model spend rather than guess at it, Tokenwise is positioned as the monitoring and optimization layer between the application and the model APIs.

What is Tokenwise used for?

Developers and small teams scaling LLM API usage use it to analyze real request traffic and cut model costs without a full observability setup.

How much does Tokenwise cost?

Paid

Price not published

Pricing not published — visit the website for details.

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Pros and cons

Pros

• Installs as a one-line baseURL swap in any OpenAI-compatible stack — no SDK changes or refactoring • Analyzes your own request traffic instead of generic public benchmarks to find real overspend • One-click model or config swaps, with savings tracked in actual dollars • Built for makers and small teams who want cost visibility without a full observability stack

Cons

• Only works with OpenAI-compatible endpoints, so non-standard providers may not be supported • As a proxy, it sits in your request path — a step some teams hesitate to route production traffic through • Public pricing is not listed

Questions about Tokenwise

How does Tokenwise reduce LLM costs?

It records your real API traffic, runs quality checks on your own use cases, and flags cheaper models or configs that hold up, which you can apply in one click.

How hard is Tokenwise to install?

It's a single baseURL change in an OpenAI-compatible stack — no SDK swap or code refactor.

Does Tokenwise rely on public benchmarks?

No, it evaluates cheaper options against your own traffic patterns rather than generic benchmarks.

Who is Tokenwise best for?

Makers and small teams scaling API usage who want cost control without standing up a full observability platform.

What are the best alternatives to Tokenwise?

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