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What started as an open source experiment to push models to their limits became something unexpected. 2.7M developers. Inbound from Fortune 100 companies. A $32M bet on the future of coding. The story behind it all, and why our long-term bet is on open-source:

"Inference is not the business model" via @latentspacepod

Imagine if gas stations didn't tell you how many gallons you were getting. The station built your car, but you can't look under the hood. That's the inference subscription dilemma in one image, and the reality of selling commodities on subscription models. 🧵

Imagine if gas stations didn't tell you how many gallons you were getting. The station built your car, but you can't look under the hood. That's the AI subscription crisis in one image, and the reality of selling commodities on subscription models. 🧵

The worst part of @CerebrasSystems inference? You don't time to make an espresso while Cline codes. Join our hackathon next Saturday to explore the new paradigm: instant inference. $5k in prizes → RSVP below

> 2500 tokens per second > 40x faster than Sonnet-4 > 4 trillion transistor wafers (19x Nvidia B200) These are impressive numbers, but nothing beats a live demo. 1 million free tokens per day of lightning-fast qwen3-32b and qwen3-235b from @CerebrasSystems in Cline. Link below.

if you’re a twitter microcelebrity in sf you get pr packages from coding agent startups

Here's why we decided to (1) make Cline open source and (2) not make inference reselling part of our business model: When you control the inference (the AI model calls) and we build the harness (the system directing those calls), neither party can obscure what's happening. You see exactly which models are called, how much context is used, what decisions are made. We can't quietly degrade performance to improve margins because you're paying the inference provider directly. This separation means we succeed only when Cline becomes more capable. Not when we find clever ways to reduce your token usage. Not when we route to cheaper models without telling you. Not when we artificially limit context windows. The result: Cline uses the right model for each task (as defined by you), integrates any tool you need via MCP, and operates without arbitrary constraints. You get pure, unfiltered access to AI capability. We built this way because when incentives align correctly, you don't need to trust us. The architecture itself guarantees we're working toward the same goal: the most powerful AI coding experience possible. The bottom line is that Cline gives you the best possible performance out of the best models, full-stop.

v excited to see where we go from here with os models