ClinePass

Run the best open-weights models in Cline

Developer Tools

Artificial Intelligence

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Affordable access! $1.99 intro pricing is such a great way to try this out without hesitation.

Smooth integration! Love how easy it is to plug into both CLI and IDE, super developer‑friendly.

The provider-account juggling part is the real pain point here. In Cline I usually lose more time comparing limits/billing than picking the model. Curious how you decide which open models are “agentic enough” before adding them?

running open-weights in a coding agent is the part most people still sleep on. which ones actually hold up on real agentic tasks, not just benchmarks?

The data path is what I'd want pinned down before routing my agent stack through this — when ClinePass proxies my prompts and codebase context to GLM/Kimi/DeepSeek, is it pass-through with zero retention, or do you log requests for benchmarking and abuse handling? And are you hosting these open weights on your own infra or reselling third-party inference, since that decides where my code actually lands and what the latency floor looks like.

the bring-your-own open-weights angle is the right bet — not being locked to one provider's pricing or privacy terms is underrated. how's GLM/Kimi holding up vs frontier models on the harder agentic tasks?

Great to see this live! Which use case are you seeing the most demand for?

The actual pain point this solves is real, juggling API keys and billing across five different open-weight providers just to try models in Cline is annoying enough that I'd pay $9.99 just to skip that step, separate from whether the rate limits matter.

I love cline! used it for a year now! Is this new subscription you can eat tokens? or is it pay as you go? Its not fully clear from the description.

Open-weights in Cline is interesting for the same reason local tools keep coming back: cost control and privacy both matter once agents become daily infrastructure. The practical test is whether teams can swap models without breaking their workflow.

the SDK option is what separates this from most coding agents. being able to embed an autonomous coding agent into your own tools and workflows instead of only using it through an IDE is a much bigger unlock. most teams don't just need an agent that writes code, they need one that fits into their existing CI pipeline and review process. how does cline handle the review step? does it wait for approval before committing or can you set it to auto-commit on low risk changes?

The open-weights angle here is underrated - when you're working on anything where you can't send your code to an external API, being able to run a capable model locally through Cline changes everything. Curious how the performance compares to the hosted models for actual coding tasks - do the open-weights models hold up on complex refactors or is there still a noticeable gap?

The curated-and-benchmarked-for-agentic-coding angle is what stands out to me here, more than the flat price. New open models drop constantly, so how fast does a model typically go from release to being added to the pool once it clears your benchmarks? Wondering how a GLM 5.2 or a fresh Kimi release makes it in.

For me personally I think that the consolidation angle is the real win. There is so much friction in juggling separate DeepSeek, GLM, and Kimi keys and billing pagesthat hits at the worst possible moment. One sub that just works is a clean pitch. One question: with all these under one harness, does ClinePass route to the best model per task, or do I pick per request? Curious especially whether you can split roles in a single run since that's usually where long-horizon agent runs hold up or fall apart.

the consolidation play here is underrated - managing separate DeepSeek, GLM, and Kimi API keys, rate limits, and billing pages is friction that burns time at exactly the wrong moment (middle of a coding session). $9.99 to have one thing that just works is a clean value prop. curious whether there's any intelligent routing under the hood - like if DeepSeek hits capacity does it silently fall back to GLM, or does the user explicitly choose which model runs?

The "no juggling provider accounts / API keys / billing pages" angle is the real pain point here. Two questions: with GLM, Kimi and DeepSeek under one sub, does ClinePass auto-route to the best model per task, or do I pick per request? And are the 2–5x rate limits relative to hitting the providers directly, or to Cline's default tier?

The flat price is the headline, but the thing I'd actually stress-test is long-horizon behavior. Open weights like GLM or DeepSeek can match frontier on a single completion and still drift over a 40-tool-call autonomous run, re-reading the same file or losing the original task. We hit exactly that building agent loops, the failure was never one bad call, it was accumulation across many. Does ClinePass let you mix models inside one session, say a stronger one for planning and a cheaper one to execute, or are you on one model per run?

An agent that can work across the editor terminal and browser feels much closer to how developers actually work day to day.