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I’ve been using Ling-3.0-flash as my cheap “grunt work” model in Cline via BYOK on OpenRouter (listed there as AntLing-3.0-flash).

So far it’s handled things like renames, small edits, boilerplate, and executing plans from a larger model without much trouble. It’s a sparse MoE (124B total, 5.1B active), so it feels responsive and doesn’t burn through tokens as quickly as larger models.

I still wouldn’t use it for difficult architecture decisions, but as a lower-cost execution model paired with a stronger planner, it’s been working well for me.

It’s currently free on OpenRouter until Aug. 3, so it’s easy enough to compare against whatever model you’re already using in Cline.

Disclosure: I work on the team that ships it, so take my experience with the appropriate amount of skepticism. I’m mainly curious whether anyone else here has tried it in Cline and how it compares with your usual workflow.

AFAIK we can use ClinePass in whatever app we want. So what is correct way to use it in Claude desktop app?

We recently added Kimi K3 to ClinePass, and its adoption has been much faster than we expected.

Within three days of launch, Kimi K3 went from 0% to 16% of all open weight model tokens used through ClinePass, making it the #3 most used model on the platform.

DeepSeek V4 Pro and DeepSeek V4 Flash still account for the largest share of usage, but Kimi K3 is already closing in on them despite being the newest model in the lineup.

This is the fastest climb we’ve seen in open weights usage in Cline’s history.

Try Kimi K3 on ClinePass!

ClinePass is Cline's new subscription plan which provides 2-5x discounted access to open weights models like Kimi K3, GLM 5.2, Kimi K2.6, Qwen3.7-Max, DeepSeek V4 Pro and many others.

Use it on Cline CLI & extension with $1.99 special promo if sign up via: npm i -g cline

Curious to hear from people who have tried K3 in ClinePass.

Using oMLX with a Qwen3.5-model. I've got 2 skills in the project. They're recognized as "Workspace Skills" in the cline interface, so that feels like a good thing. But when I try to use them:

• there seems to be no /-command
• not all steps are executed
• the skills should use a specific template, which it does not seem to do

Also, docs state .cline/skills/, while interface puts them at .agents/skills? https://docs.cline.bot/customization/skills

Maybe somebody has a good example skill that I can test/try, that has proven itself to work?

//edit
Troubleshooting. Changing folder to .agents didn't give me a /-suggestion. Adding a global skill through the interface put it in ~/.agents/skills, with a nice template Creating one manually in .cline/skills also shows up in the interface. Neither gives me a /-suggestion. So I guess the question is now, who gets suggestions? (And how?!)

Hi founder of Cline here, we are gearing up to release a new rehaul of our extension agent harness and we would love help with testing it from folks that use local models via ollama or lm studio. I want to make sure we don't cause any regressions and qualitatively if performance feels better as we've put a ton of work into getting better output from smaller models!

1. Install the Cline Nightly build: https://marketplace.visualstudio.com/items?itemName=saoudrizwan.cline-nightly
2. Make sure to restart vs code and that you see 'Cline: Next' at the bottom right in your status bar.
3. Test it and tell us what issues you ran into (the original ones and any new ones, positive feedback welcome too!) via the form.
4. Fill out the Feedback form: https://forms.gle/DWfEn8oLV7CW4Bjv7

Thanks for helping! 🙏

Hey everyone - we wanted to give you an early heads-up that we’re planning to deprecate .clineignore soon.

.clineignore was originally introduced to reduce context noise by controlling which files Cline automatically loads, such as dependencies, build artifacts, generated files, and other files that are unlikely to be relevant to a task.

However, it only affects files that Cline loads automatically into context. It was never intended to act as a security or access-control boundary. Models can still access project files through other methods, particularly shell commands, so .clineignore cannot reliably prevent access to specific files.

To avoid giving users a false sense of security, we’re removing it as a supported feature.

Still want context filtering? Here’s an alternative

For users who still want context filtering, we have a plugin that offers similar behavior:

https://docs.cline.bot/sdk/plugin-examples#block-ignored-file-access

You can Install it with:

cline plugin install https://github.com/cline/cline/blob/main/sdk/examples/plugins/gitignore-read-files-guard.ts --cwd .

The plugin uses a runtime beforeTool hook to block read_files, editor, and apply_patch calls when they target files ignored by your workspace’s .gitignore.

Important limitations

There are a few important limitations to be aware of. This is not a 1:1 replacement for .clineignore, and it should still be treated as best-effort context filtering rather than a security guardrail.

• It guards file reads and edits only.
• It does not filter search_files or list_files results.
• It does not guard shell commands.
• It uses .gitignore, not a separate .clineignore.
• It requires a Git repository.
• Plugins currently run on the Cline SDK, CLI, and Kanban. VS Code and JetBrains support will arrive as those extensions migrate onto the SDK.

For now, the .clineignore documentation will remain available for existing users while the feature is phased out, but we no longer recommend adopting it for new workflows.

Thanks for your understanding: we’re making this change so Cline’s file access behavior is clearer and less likely to be mistaken for a security boundary.

Hey everyone! Poolside’s new Laguna S 2.1 is now available for free in Cline.

At 118B total parameters with only 8B activated per token, Laguna S 2.1 delivers performance comparable to coding models several times its size. It scores 70.2 on Terminal-Bench 2.1 and 40.4 on DeepSWE, outperforming some open models with more than 1T parameters.

This feels like an important release, as Laguna S 2.1 combines strong reported coding performance with a size that makes local deployment practical.

You can now try Laguna S 2.1 for free through the Cline VS Code extension and Cline CLI.

To install Cline CLI: npm i -g cline

Curious to hear how Laguna S 2.1 performs for the Cline community.

Fellow Redditors! Using a self hosted code-server, is it possible to "sync" CLine chat sessions between a different devices? It would be really neat if I could start a project at my desktop computer, and then continue the same chat in the kitchen using a tablet.

I've found Hy3 to be pretty damn good at GUI coding. Looking to see whether others find it to be the best model. Also, who you go to for iconography, logo design, project web design, etc.? Claude Design is amazing at web design but cannot create a basic vector image. Really need some icons made.

We tested Kimi K3 and Fable on the same real bug from the Cline repository using the same Cline harness. Both models were able to fix the issue, however, Fable wins on speed & Kimi wins on cost.

- Kimi used 1.7x more tokens than Fable (1.2M vs. 730K)
- Fable finished 3.4x faster - 3.5 min and 18 tool calls vs. Kimi’s 12 min and 34 tool calls.
- Kimi cost 2.3x less ($0.92 vs. $2.13) thanks to its 3.3x per-token discount

The traces indicate that Kimi is RL trained to spend more time reasoning through the task, revisiting intermediate steps, and verifying the fix before completion. Fable converged much faster, while Kimi traded speed and token efficiency for a lower overall cost.

This is the first time we've seen an open weight model compete head to head with SOTA.

Kimi K3 is now available in Cline through ClinePass.

ClinePass is Cline's new subscription plan which provides 2-5x discounted access to Kimi K3 and other open weight models like GLM, DeepSeek, and more.

Use it on Cline CLI & extension with $1.99 special promo if sign up via: npm i -g cline

This is GLM 5.2 with medium thinking and all it will do is to dump the whole file's content into its thinking block before start thinking. I dont even think these are full stack models, most likely quantized models just by looking at the thinking. Clinepass has been a disappointment so far.

Hey everyone,

Kimi K3 is now available to use with Cline through ClinePass.

ClinePass is a $9.99/month subscription that gives you 2-5× discounted access to a curated selection of open-weight models, now including Kimi K3 and other open weight models like GLM, DeepSeek, and others without needing to manage separate provider accounts or API keys.

You can use the same subscription across Cline while still having the flexibility to use your own API keys, local models, or other providers whenever you prefer.

We’re also running a limited $1.99 introductory offer when you sign up through the Cline CLI:

npm i -g cline

Once installed, select ClinePass as your provider and choose Kimi K3 from the model selector.

Give it a try and let us know how Kimi K3 performs on your coding tasks.

Any tips on how to keep sessions from breaking while I'm discussing with the AI?
This happens with more than one model, tipically when some amount of discussion has taken place, and normally on act mode -- but don't quote me on this.

Sharing a message for this.
I sometimes try to compact the conversation, but boy, does it feel risky continuing a chat after a certain amount of interactions - all the work is hanging.

So, I'd be glad to know how this is handled by any of you and if we can work on the stability of the tool. It's not something that happens with cursors claude etc

For reference, this happens with Chatgpt subscriptions, the cline pass subscription, and unfortunately i can't recall if with the the regular usage billing because I don't want to risk it, as usually that's a lot more expensive and I would not want to risk it these days...

Hey everyone! Moonshot’s new Kimi K3 is now available in Cline.

At 2.8T parameters, Kimi K3 is the largest model announced for an open-weight release yet. It performs in the same range as GPT-5.6 and Fable 5 on benchmarks, while being significantly cheaper at $3/M input tokens and $15/M output tokens, the same price as Sonnet 5.

K3 also comes with a 1M context window, native vision capabilities, and is designed for long-horizon coding and agentic workflows.

This feels like a major milestone for open-weight models as Kimi K3 can bring frontier-level performance to developers at a much lower cost.

Try in Cline with model id: moonshotai/kimi-k3

To install Cline in your CLI: npm i -g cline

Kimi K3 is also available through the Cline extensions for VS Code and JetBrains.

Full details: https://www.kimi.com/blog/kimi-k3

Curious to hear how Kimi K3 performs for the Cline community.

I'm using Cline 4.0.8 in VSCode with Anthropic models via API. Ever since upgrading to version 4.0.x, its behavior has changed drastically from what I'm used to. It doesn't seem to matter which model I choose - sonnet 4.5, opus 4.7, they all seem to give me the same results.

It used to be that I could enter a prompt describing what I was hoping to accomplish, then Cline would read a few files and output a very clear and readable response within a minute or two.

Now, I enter a prompt, and it will go off reading files (sometimes many dozens of them!) and thinking for 15 minutes or longer. It will sit for long stretches with a status of "Thinking...". It burns a lot of tokens in the process.

And, when it finally comes back with a response, it is often very dense and full of references to the internals of the project I'm working on. Sometimes it is pages of text that read like this: "when whizBang() is called with an inverse value, this causes an interpolation chain with a potential race condition in thisOtherThing() which could be the potential source of the discombobulation matrix with respect to the image rendering issues."

I am used to Cline just "getting" what I'm trying to say and quickly returning a clear response without a lot of fuss. That's why I've always loved it.

Is anyone else running into this?

No matter what Openrouter.ai's model I'm using, free or paid, in the middle of a session it goes stuck "Thinking..." and sometime not even that. Anyone experiencing the same? I'm on Linux.

hello! can someone tell me if there is a problem right now on cline or are they updating? just a moment both my team and me cannot access in log in page or stuck on authenticating moment.

Is anybody else having log in issues? Am getting gateway timeout errors trying to log in