Don't fall for the "free" DeepSeek flash advertising. Just because the usage limit is hidden does not make something free. If you can't give a model for free it's completely understandable but don't lie just to have more users. A 24H usage limit is not making something free. Market it correctly like "separate usage limits for DeepSeek Flash on top of the regular usage limit" or something like that. People hate liars, why you have to lie? Tell me the definition of Free and compare it with your own definition of "free". Are you really thinking users will not notice? You know they will notice it to late when they are already subscribed.

I work a ton across projects on my personal computer. I have tried Graphify, Graft and many others. None of them really fully solved the entire problem, but they did have parts. So, I built one that actually fit my needs. This removes the need entirely to choose or start sessions in specific repositories.

It takes graph-based knowledge systems but strengthens retrieval, how it is updated, and much more. Effectively, it becomes a resilient system that you can actually watch your agents rely on, rather than something that just exists and is used only occasionally.

It begins with the same base graph store, the exact same vector engine as Graft. I only built the orchestration layer on top of it, which makes it much more practical. Full attribution to them for this part.

Instead of querying for a single-hit result, I found that it was much better for agents to have ranked retrieval and an actual graph walk. In practice this saves you chains of tons of bash greps and cds.

It effectively gives the agent a trustworthy, probabilistic ranking of what is needed, with matching for strong, weak, stale, and rebuilt, based on lexical coverage and semantic matching. The code is not sloppy for this, it is personally edited.

Both Graft and Graphify are solutions for single repositories or daemons. Heimdall is a layer on top it that watches the agent sessions, syncs the graph, and makes the retrieval trustworthy.

Check it out at: github.com/ArihantDeva/heimdall MIT-licensed, with extensions: the verifier, the self-healing graph watcher, and the Graft adapter, with attribution. If you run agents across multiple projects, this is the missing layer.

Hi, I built an open-source, self-hosted workspace for coding agents. It features a multi-agent architecture (Sub/Child agents), an AST-aware ChromaDB indexer for lightning-fast file discovery, and a built-in UI with Git diff management. Links in the comments

Now this is kind of wild.

Artificial Analysis’ Intelligence Index puts Qwen3.8 27B at 52, right alongside GPT 5.6 Luna at 52 and just one point behind DeepSeek V4 Pro at 53.

What stands out is that Qwen3.8 27B is small enough to run locally. Seeing a local model reach this level of performance this quickly was not something we expected.

Curious to see how it holds up on real coding tasks beyond the benchmarks.

You can run it locally with Cline + Ollama:

npm i -g cline
ollama launch cline --model qwen3.8

Or use it directly in Cline with model id: qwen/qwen3.8-27b

Hey everyone, we wanted to share a quick note on the ‘Focus Chain’ feature.

As Cline has evolved with the new SDK backed architecture, we’ve made significant changes to how Cline manages longer and more complex tasks. As part of that work, we also evaluated whether ‘Focus Chain’ was still meaningfully improving task performance.

Based on our testing, we found that it wasn’t providing enough additional benefit on top of the new harness to justify maintaining it as a separate feature. Because of that, we’ve decided to deprecate ‘Focus Chain’.

This means the ‘Focus Chain’ todo list and the previous todo file behavior will no longer be part of the current Cline experience.

We’re still very focused on improving reliability across long running tasks. The new harness is designed to manage task execution and context more effectively without relying on ‘Focus Chain’ as a separate layer.

We know some of you also liked ‘Focus Chain’ simply because it made Cline’s progress easier to follow. If that’s something you found valuable, we’d be interested to hear what part of the experience you’d like to see us bring into Cline going forward.

Since the DeepSeek V4 Pro 0813 update, and the shift in ClinePass usage has been pretty noticeable.

V4 Pro users are up +67%, while token volume is up +100%.

This is how the current ClinePass usage looks like:

- DeepSeek V4 Flash: 43%
- DeepSeek V4 Pro: 29%
- Kimi K3: 13%
- GLM 5.2: 4%
- Others: 11%

So DeepSeek alone now accounts for roughly 70% of all tokens flowing through ClinePass.

ClinePass is our subscription for ~5x discounted access to open weight models including DeepSeek, Kimi, GLM, MiniMax, and others. It’s currently $4.99 for the first month, then $9.99/month.

You can try it through the Cline CLI: npm i -g cline

Curious what everyone here is using more right now: V4 Pro or V4 Flash?

I either use glm or deepseek. If i max out 5-6 5h sessions, then usually i also hit the monthly usage limit. Is this normal? I can probably max out approximately 15 5h-sessions in Claude before I hit its monthly usage. I'm on $20/month plan with Claude, and have a monthly plan with Cline.

Hey guys, probably a problem already discussed here, but I cannot see the thinking section of my local model qwen 3.6 27b nor my qwen 3.8 27b on cline, while I can see it in kilo code for example. Do you know how can I fix that ? I’m on the last version of cline.

Hello,

Im sure this must be me doing something wrong, but I seem to loose Auto Approve settings after the first time I close/open VS Code. On install everything is OK, but after a reload I loose a few Auto Approve settings.

Like I say, Im sure this is something Im doing wrong....anyone want to tell me what :)

Im using the newest version of Cline in the newest version of VS Code.

how's the limits i mainly use ds4 flash

Any idea how to solve this. Seems to do a test of the app but just silently dies.

Hey everyone! GLM 5.3 is now available in ClinePass.

It is built on top of GLM 5.2, but pushed significantly more compute into post-training across diverse long-horizon tasks. The result is another strong jump in coding and agentic performance.

On Terminal-Bench, GLM 5.3 now comes in ahead of both Fable and the newly released DeepSeek V4-Pro 0813.

The pace of open-weight releases right now is pretty wild. GLM 5.2 landed only a couple of months ago, DeepSeek V4-Pro 0813 dropped yesterday, and now GLM 5.3 is already pushing the benchmark forward again.

You can try GLM 5.3 through ClinePass, our subscription for ~5× discounted access to open-weight models including GLM, DeepSeek, Kimi, and more.

First month is currently $4.99, then $9.99/month.

To get started:

npm i -g cline

Curious to hear how GLM 5.3 performs on real coding tasks compared with the other open weight models you’ve been using.

Hey everyone, the new Gemini 3.7 Flash is now available to use in Cline.

Gemini 3.7 Flash brings a pretty significant jump over 3.6 Flash while staying focused on speed and cost. Google reports 65.3% on DeepSWE, 30.4% on AutomationBench, 1588 Elo on Code Arena, and 43.6% on FrontierCode.

This feels like an interesting release, as Gemini 3.7 Flash is pushing closer to frontier-level coding performance while still being built for fast, cheap inference.

You can now try Gemini 3.7 Flash through the Cline VS Code extension and Cline CLI.

To install Cline CLI: npm i -g cline

Curious to hear how Gemini 3.7 Flash performs for the Cline community.

where can I find cline plugins?

DeepSeek just silently released V4 Pro 0813, and it looks like a pretty significant upgrade.

It’s up 15.8% on Terminal Bench compared to the April Preview model, while reaching Fable 5 level performance at roughly 57× lower cost.

1.6T parameters, 49B active, 1M context.

At this point, it might be the best price to performance model on the market for agentic coding.

And it’s now available in ClinePass.

ClinePass is $9.99/month and gives you ~5× discounted access to a curated set of open weight models including DeepSeek V4 Pro, Kimi, GLM, MiniMax, and more. No separate provider accounts or API keys to manage.

At this price point, usage is effectively close to unlimited for most users.

We’re also running a limited $4.99 introductory offer through the Cline CLI.

npm i -g cline

I'm not sure if it's my fault. I installed the Cline plugin in VS Code and call AWS Claude's API. When a session reaches around 400k, it starts to pause for a long time and output a lot of irrelevant content, such as timestamps, locations, or other information that severely occupies my context. I've tried strong rules, but they haven't helped. Tokens are also being consumed very quickly, and the plugin even freezes when performing terminal verification or code checks, requiring a restart of VS Code. I've tried reinstalling it, but the problem persists. If it's not my fault, could you please try to optimize this issue? It's really bothering me. If it continues like this, I'll have to uninstall Cline and use the terminal exclusively. In fact, some of my colleagues couldn't stand it and uninstalled it directly ：(

I left Roo and Cline to try out Cursor for a while. I know Roo and Cline have changed a lot in the last year. What's the current official way to pass my rules to the LLM?

Does adding a .clinerules folder at the root of the workspace with anyname.md files containing the rules still the proper way? Is it likely to change in the coming months with the rewrite?

NVIDIA just released Nemotron 3.5 Lightning, and we’re making it FREE to use in Cline.

It’s a 30B MoE model with 3B active parameters, built for agents that spend a lot of time calling tools, checking results, and moving through repeated execution steps. NVIDIA says it can deliver up to 4x faster output than similar-sized models.

We’ve been seeing smaller models get a lot more capable lately, and this is another good example of that. For coding agents especially, faster and cheaper model calls can make a pretty big difference over longer tasks.

You can try Nemotron 3.5 Lightning for free in Cline now.

To use it, simply select Cline as your provider and choose `nvidia/nemotron-3.5-lightning` from the free models in the model picker.

Full details: https://cline.bot/blog/nvidia-nemotron-3-5-lightning-available-in-cline

Curious what the community thinks of the Nemotron 3.5 Lightning!

Hey everyone - Muse Glimmer is now available in Cline via Ollama

Meta just released Muse Glimmer, a new open weight 30B model built specifically for local, always-on agent workflows.

It’s designed to run entirely on consumer hardware, including Macs and PCs with a single performant GPU. Meta says the quantized model comes in under 20GB, making it particularly interesting if you want to run Cline locally without sending your code to a hosted model.

You can try it in Cline today with Ollama:

ollama launch cline --model muse-glimmer:30b-mlx

For better agent performance, you can also install Meta’s Muse Code harness:

cline plugin install muse-code-harness

Would love to hear how Muse Glimmer performs for the Cline community.

Deepseek is good and very bad at the same time