u/gargetisha

Hey everyone, we are launching Cline Cloud Agents (Beta)

With Cloud Agents, you can now run Cline directly from your browser, without needing to keep your IDE or desktop app open.

Give it a task, and it works inside its own secure cloud sandbox, writing code, running commands, and making changes to your repository. Once it's done, it opens a pull request on GitHub for you to review.

Here's what you can do with Cloud Agents:

Run multiple Clines in parallel

Every agent gets its own independent, secure container in the cloud, so you can have several tasks running simultaneously.

For example, you could have one Cline fixing a bug, another refactoring an existing feature, and a third building something new. All three work independently, and you can review their PRs as they come in.

Start on your laptop, continue from your phone

Since everything runs in the cloud, your agents don't stop when you close your laptop. You can kick off a task before heading out, check its progress from your phone, and come back to review the changes later.

Choose your model

You can get started for free with models like DeepSeek V4.1 Flash. We also support ClinePass, which gives you access to open-weights models at ~5x discounted rates.

How to Get started:

1. Log in or create a Cline account.
2. Connect your GitHub account.
3. Head to the Agents tab, select a repository, and tell Cline what you want to build.

Try Cline Cloud Agents: https://cline.bot/cloud

Cline Cloud Agents is still in beta, and we'd love to hear your feedback as we continue improving the experience.

Hey everyone, Mistral Large 4 just dropped and we've added it to Cline.

One of the most interesting results so far is on the Artificial Analysis Cyber Index, where Mistral Large 4 scores 50, ahead of GPT-6 Astra at 33 and Opus 5.5 at 29.

But what makes this comparison interesting is the refusal rate.

GPT-6 Astra refused 38 of the cybersecurity tasks because of its safety filters, while Opus 5.5 refused 36. Mistral Large 4, meanwhile, completed 50 tasks without those safety blocks.

Mistral Large 4 comes with a 1M-token context window, native multimodal support, tool calling, and a Mixture-of-Experts architecture with 1.05T total parameters and 49B active parameters.

Mistral Large 4 is now available in Cline.

Try it in CLI:
npm i -g cline

Or in our new Desktop app (we have several free model promos to give it a spin!)

Give it a try and let us know how it performs for you.

Hey everyone, we just added Pareto 26.10 Preview to Cline.

Pareto takes a pretty different approach from a standard single-model endpoint. It’s a composite model designed for coding and agentic workloads, routing work across multiple models and selecting the strongest result while keeping costs low.

Pareto 26.10 Preview scored 69.9% on DeepSWE v1.1 at an average cost of $0.24/task. For comparison, Fable 5 sits at roughly the same DeepSWE score at $13.41/task.

That makes Pareto about 56x cheaper per task at essentially the same score in this comparison.

It comes with a 1M-token context window, supports text and image input along with tool calling, and is designed for coding, research, and longer agentic workflows. Pricing is $0.80 per 1M input tokens, $0.03 per 1M cached input tokens, and $3.20 per 1M output tokens.

One particularly interesting part for Cline workloads is caching. Pareto is designed to preserve prompt caching even while using its composite approach, which matters a lot once an agent starts repeatedly working with a large codebase and long context.

It is still a Preview, so the model and its benchmark numbers may continue to change as Unbiased iterates on it.

Pareto 26.10 Preview is available in Cline now.

Try it in CLI:
npm i -g cline

Or in our new Desktop app (we have several free model promos to give it a spin!)

If you try it on a real codebase, especially a longer agentic task, let us know how it compares with the models you normally use.

Hey everyone - Cline Desktop is now available on Linux, with auto-updates included. It's the same app as on macOS and Windows: parallel sessions, scheduled tasks, SSH remotes, local models, and every provider we support.

Every release now ships four Linux packages:

• Cline_x.y.z_amd64.deb
• Cline_x.y.z_arm64.deb
• Cline_x.y.z_x86_64.rpm
• Cline_x.y.z_aarch64.rpm

That covers Debian, Ubuntu, Mint, Pop!_OS, Fedora, RHEL, and openSUSE. The packages are built on Ubuntu 22.04, so anything with that glibc and WebKitGTK 4.1 works.

Local models: Cline Desktop is open source and built for open-weight models. Run Ollama, LM Studio, or llama.cpp on the same box, point Cline at it, and the whole loop stays on your machine. Or use the free models and ClinePass with no API key: https://cline.bot/pass

Homelab and server crowd: Settings -> Remote lets the app stay on your laptop while the agent runs on any Linux box you can SSH into. No root, no npm, no public port. It uploads a self-contained helper and tunnels only the authenticated Cline protocol. Docs: https://docs.cline.bot/usage/cline-desktop-ssh

Download: https://cline.bot/desktop

Hey everyone, another stealth model just dropped and we've added it to Cline for FREE.

It comes with a 262K context window and scored 90% on the Next.js Agent Evals, passing 28 of 31 practical web and mobile development tasks. That puts it tied with GPT 6 Astra and ahead of Kimi K3. With bundled Next.js docs, that score jumps to 97%, matching Claude Fable 5.1 at the top.

It runs at around 20–25 tokens/sec and seems particularly interesting for frontend and agentic coding tasks like refactoring, layouts, interactive components, and building web/mobile apps.

And right now, Pixel Canary is completely free in Cline while it's in stealth.

It's pretty fun trying it in the new Cline Desktop app alongside the other free models like DeepSeek V4.1 Flash and Gemini 3.8 Flash.

Try it in Cline Desktop

Give it a try and let us know how it performs on your projects.

Also, who do you think is behind Pixel Canary? 👀

Hey everyone, Gemini 3.8 Flash is now available in Cline for FREE.

Gemini 3.8 Flash is the most intelligent Flash model yet, built specifically for long horizon software engineering, autonomous agents, and complex multi step workflows.

And the speed is probably the most fun part.

It runs at roughly 291 output tokens/sec with a 1M-token context window, and supports text, images, audio, video, and PDFs as input, with up to 64K tokens of text output.

On the Artificial Analysis Intelligence Index, it scores 41 ahead of the similarly priced models in the comparison, including DeepSeek V4.1 Flash, GPT 5.6 Luna, Qwen3.8 27B, and MiniMax M3.

It’s especially fun to use in the new Cline Desktop app because you can really feel how fast the model is when Cline is working through a task and that too for FREE.

To try it:

1. Download Cline Desktop
2. Select Gemini 3.8 Flash as your free model

Do give it a try and let us know what you build with it.

Hey everyone - another stealth model just landed, and we've added it to Cline for FREE.

Space Bunny Alpha is a fast reasoning model built with coding and agentic workflows in mind. It comes with a massive 1M-token context window, native multimodal support for text, images, and video, tool calling, fast inference, and zero data retention.

There aren't reliable public coding benchmark numbers for it yet, and the team behind the model hasn't been disclosed, so for now, it's genuinely a stealth model.

You can try it for free in Cline right now:

1. Download Cline Desktop
2. Select Space Bunny Alpha as your free model

If you test it, drop what you built or your experience below. Especially curious how it does on larger existing codebases and longer agent runs.

Who do you think is behind it? 👀

Hey everyone - A new stealth model called Union Alpha just dropped yesterday and we've added it to Cline for FREE.

At 256K context window, it’s multimodal, supports tool calling, and is built for agentic coding workflows.

On DeepSWE, Union Alpha scored 73%, putting it right next to GPT-6 Astra and Opus 5 at 74%.

And the cost difference is pretty wild: its expected cost is around $0.65, compared to $6.50 for Astra and $11.80 for Opus 5 on the same benchmark.

The team behind the model hasn’t been disclosed yet, so for now, it’s genuinely a stealth model.

You can try it for free in Cline right now:

npm i -g cline

Then /model → Free → Union Alpha

If you test it, drop what you built/your experience below. Especially curious how it does on larger existing codebases and longer agent runs.

And yes, we also want to know who made it 👀

Hey everyone 👋

Today we’re launching Cline Desktop, a native interface for coding with open weight models.

You can use it with ClinePass and free models like DeepSeek-V4.1-Flash, or BYOK with the provider and model you want.

Cline started as a VS Code extension and is now used by more than 11 million developers.

With Desktop, we’re bringing the same best-in class open-weight agent harness into a dedicated workspace while keeping the things that have always mattered to us - open source software, open models, and giving you control over how you work with agents.

As we started delegating more work to agents ourselves, we found that keeping track of tasks and context gets difficult pretty quickly. The extension and CLI work great when you’re actively working alongside an agent, but we wanted a place for the work you’re increasingly handing off.

With Cline Desktop App, you can:

→ Choose from 300+ models through Cline, use open weight models with ClinePass, run local models, or bring your own API keys
→ Import tasks from Claude Code, Codex, and other supported agents and continue with the existing context
→ Start a task in the Cline CLI or VS Code extension and pick it up again on Desktop
→ Schedule recurring work like PR reviews, repo checks, and documentation updates
→ Discover and manage plugins, MCP servers, and skills through the Marketplace
→ Use web search and voice input for research, outside context, and longer instructions

Cline Desktop is now available in macOS and Windows(beta).

Learn more here: https://cline.bot/desktop

This is still early, and we’re continuously improving it. Do give Cline Desktop a try and share your feedback. If there’s something you’d like to see next, we’d love to hear what you want us to build.

Hey everyone - DeepSeek V4.1 Flash is now available in ClinePass.

This one is pretty interesting. DeepSeek released V4.1 Flash less than a month after V4 Pro 0813, and the new Flash model has already surpassed Pro across performance, cost, speed, and total task time.

On Terminal Bench 2.1, V4.1 Flash scores 90.6, ahead of Opus 5 at 89.1, GPT 5.6 Sol at 88.8, Kimi K3 at 88.3, and V4 Pro at 87.9.

And it's $0.30/$1.20 per 1M input/output. That's roughly:

- 1/20th cost of Opus 5
- 1/17th cost of GPT-5.6 Sol
- 1/12th cost of Kimi K3

It also comes with a 1M context window, native vision, and a new architecture designed to make long agentic workloads significantly more efficient.

You can now use DeepSeek V4.1 Flash directly with ClinePass.

ClinePass is our subscription for ~5x discounted access to open weight models including DeepSeek, Kimi, GLM, MiniMax, and others, for just $9.99/month.

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

Try it on a real coding task and let us know how it compares to V4 Pro or the previous V4 Flash model.

Hey everyone 👋

Meta’s Muse Spark 1.3 Contributor is now available for free in Cline.

It’s built for coding and agentic workflows, with a 1M token context window and stronger performance on long-running tasks that involve navigating codebases, using tools, and iterating across multiple steps.

Meta’s benchmarks also put it in a similar performance range to models like Opus 5, while being considerably more affordable.

This should be an interesting one to try on real repo-level work in Cline: larger features, bug fixes, refactors, or tasks that require understanding a lot of existing code.

Try it now:

1. npm i -g cline
2. /model
3. Select Muse Spark 1.3 Contributor under Free

Give it a try and let us know how it performs on your workflows.

Hey everyone - Solar Pro 4 by South Korean AI lab Upstage is now available for free in Cline.

It comes with a 512K context window and is built for agentic workloads, including coding, tool use, and reasoning across large amounts of context.

Solar Pro 4 also represents a significant jump in agent capability over Solar Pro 3, with a 57 score on Terminal Bench 2.1.

Beyond coding, it’s designed to handle long, structured documents like invoices, reports, and technical specs with hundreds of line items, which makes it interesting for workflows that need a lot of context.

To try it:

npm i -g cline

/model

Select Solar Pro 4 under Free Models.

Would love to hear how it performs on your coding workflows, especially longer agentic tasks.

Hey everyone - OpenAI just released GPT-6 Astra, and it’s now available in Cline.

The coding results are probably the most interesting part of the release for us.

It takes the top spot on Terminal-Bench 4.0 and scored 57.9%, ahead of Claude Fable 5.1 at 55.8% and GPT 5.6 Sol at 37.3%. It's 1.9% ahead of Claude Fable 5.1 which only came out a few days ago.

Beyond coding, OpenAI is positioning Astra as its most capable model for complex reasoning, computer use, research, and end to end professional work. It comes with a 1.05M token context window and supports up to 128K output tokens.

You can try it in Cline now:

1. npm i -g cline
2. /model
3. Select gpt-6-astra

We’d love to hear how it performs on actual repos, especially how it compares with Fable 5.1 and the open weight models you’ve been using in Cline.

Hey everyone - LongCat-2.0 just landed in Cline as a FREE model.

It’s a 1.6T open weights MoE model with ~48B active parameters and 1M context window from Meituan, and it’s putting up some pretty interesting coding numbers.

On Terminal Bench 2.1, it scores 70.8, in the same range as Claude Opus 4.7 at 71.7 and Gemini 3.1 Pro at 70.7.

You can try it for free in Cline right now:

npm i -g cline

Then run /models → Cline provider → Free → LongCat 2.0

It’s available in VS Code and JetBrains too.

Would love to hear how LongCat 2.0 holds up on your actual coding workflows.

Hey everyone, thought to share an interesting stat with you all.

47% of Qwen3.8 Max usage in Cline is now coming through ClinePass, compared to 53% through direct API access.

At $9.99/month, ClinePass is our subscription for roughly 5x discounted access to open weight models, including DeepSeek, Kimi, GLM, MiniMax, Qwen, and others.

Curious about the other half though.

If you’re not using ClinePass in Cline, what’s stopping you? Price, usage limits, model availability, or something else?

Would genuinely love to hear what would make it more useful for you.

Hey everyone - Tencent just released Hy4 Preview, and it’s now leading SWE bench Pro at 65.7%, putting it ahead of GPT 5.6 Sol, GLM 5.3, Kimi K3 and DeepSeek V4 Pro.

At 770B total parameters, 49B active parameters and 1M token context window, the model itself is pretty massive.

Tencent declares Hy4 Preview as their biggest generational leap measured so far, with the model specifically built around productivity and agentic workloads.

What’s especially exciting is seeing another open weights model competing this closely with frontier models on coding benchmarks. The open weights ecosystem keeps getting much more interesting.

You can try Hy4 Preview in Cline right now:

1. npm i -g cline
2. Run /model
3. Select Hy4 preview

It’s also available in Cline on VS Code and JetBrains.

Curious to see how it performs outside benchmarks. If you try it on a real coding task, share how it goes.

We wanted to know the cheapest possible way to win an IMO gold medal, so we ran eight models against all six IMO 2026 problems in Cline.

And, the cheapest answer turned out to be just 12 cents.

DeepSeek V4 Flash scored 30/42, clearing this year’s gold medal cutoff of 29 points. For comparison, Claude Fable 5 scored 41/42, but the run cost $17.20. DeepSeek’s gold scoring run cost just $0.1215.

What makes this more interesting is that DeepSeek V4 Flash isn’t specifically post trained for Olympiad problems. It’s a 284B parameter MoE model with roughly 13B parameters activated per token.

We had the proofs graded anonymously using the IMO 0 to 7 scoring system. Two independent model blind graders scored each solution, with disagreements resolved by a third model. Internet access was disabled, and the models only had access to the problem and a submit solution tool.

There are some obvious benchmark caveats. We ran multiple attempts and selected the best score for each problem, so this isn’t the same as measuring a single pass success rate. The $0.12 also represents the best scoring run, not the total cost of all the experimentation.

Still, how far open weight models have come is the most surprising part. DeepSeek V4 Flash reached a gold level score at a tiny fraction of the cost of the frontier models we tested.

Read more about it here: https://cline.bot/blog/deepseek-wins-imo-gold-on-12-cents

You can also try DeepSeek V4 Flash for FREE in Cline:

1. npm i -g cline
2. Open /settings → Cline provider → Free models
3. Select deepseek-v4-flash

Any interesting problems you think should be thrown at these models next?

Hey everyone - the mystery around Ox Alpha is over. Zai revealed that the stealth model was GLM-5.3-Flash, and we’re keeping it FREE to use in Cline.

It’s a 320B parameter MoE with only 18B active parameters per token, a 1M token context window, and it’s the first natively multimodal model in the GLM-5 series. Zai also redesigned the architecture around a mix of sparse + linear attention to make long-context workloads cheaper to serve.

The weights are also publicly available under an MIT license and the model is even beating frontier models on benchmarks.

Ox Alpha became the fastest-growing model in Cline history and is already driving 11%+ of all inference through Cline in less than a week.

You can try GLM-5.3-Flash for FREE right now:

npm i -g cline

Then run /models → Cline provider → Free → GLM-5.3-Flash

It’s available in VS Code and JetBrains too.

Curious to hear from people who were already using Ox Alpha before the reveal. What has it been particularly good or bad at for you?

We benchmarked Ox Alpha vs Fable on an actual bug from the Cline repo.

Both models found the root cause and fixed the bug correctly. The interesting difference was how they reasoned before making the edit.

Fable repeatedly re-verified the same conclusion. At one point, it effectively said “I found the root cause” 7 times before actually editing the code.

Ox Alpha did something very different. It identified the issue once, stated the conclusion, and moved straight to the fix.

For the same task, Ox Alpha used roughly 3x fewer output tokens.

A lot of reasoning models seem to be post-trained to improve reliability through repeated verification: reconsider the conclusion, validate it again, then validate it one more time before acting. Ox Alpha seems much more willing to trust its first solid conclusion and execute.

That feels less like just another efficiency improvement and more like a genuinely different approach to post-training reasoning models.

Aslo, Ox Alpha is currently FREE to use in Cline.

npm i -g cline

(Also available in VS Code and JetBrains.)

We recently added Ox Alpha, a new stealth model, to Cline for FREE.

There’s still no confirmed information about who built the model, but what we know so far is pretty interesting. Ox Alpha is a reasoning model geared toward coding and longer agentic workloads, with a 1M token context window and support for multimodal inputs.

Early results are looking promising too.

In a community DeepSWE run across 10 tasks:

Ox Alpha: 80%
Fable: 65%
GPT 5.6 Sol: 52%

What’s been even more surprising is the adoption. In just 48 hours, Ox Alpha is already driving 8% of all inference through Cline, making it the fastest growing model in Cline’s history.

You can try it for free:

npm i -g cline

Then use /models and look for Ox Alpha under the Free options.

Would be curious to hear from anyone who has already tried it on a real repo. How does it compare with the model you normally use?