Launch HN: Tokenless (YC S26) – Automatic model switching to save money
Why CEREBRO kept it
Automatic model switching SaaS; core agentic-llm tool.
The text below is an automated extraction of the article at https://usetokenless.com/, stored verbatim in the public cerebro-vault repository. Copyright remains with the original publisher (usetokenless.com).
Tokenless The router that cuts your inference bill in half. A drop-in replacement for your API calls — always routed to the right model. Same quality, half the cost. Most calls don’t need a frontier model. Tokenless fans out your request to a group of models and watches them think. Once a model is clearly on track, we select it and cancel the other models, and you only pay for what you need. We expose an OpenAI and Anthropic compatible endpoint. Point your models at us and get started today! >refactor CLI options into an enum this request$0.0000$0.0000 sent to Fable 5$0.0000$0.0000 −52% · $0.0
Community take
Querying multiple models at once pays input tokens N times; fanning out mostly negates cost savings unless prior cache is warm.
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Shares tags: ai/llm-mechanics · ai/saas · ai/tool-pairing
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