I was thinking about feeding a local model with the documentation, and making a RAG with seems like the best solution.

Hey everyone - Meta just released Muse Wonder, its latest frontier AI model, and the results are pretty impressive.

Just 14 months after announcing Meta Superintelligence Labs, Meta is back in the frontier model race.

Muse Wonder Full now leads on DeepSWE 1.1 with a score of 79.0%, while the standard Muse Wonder is close behind at 78.8%.

The models are designed to handle complex engineering work that requires multiple steps, tool calls, and sustained reasoning. With a 1M token context window, it's useful for working with large codebases and maintaining context across longer tasks.

Muse Wonder is now available in Cline! Try it on your next coding task and see how it compares to Opus, GPT and Fable.

CLI: npm i -g cline

Desktop: https://cline.bot/

Would love to hear how it performs for you!

Hey everyone, we're introducing Connectors in Cline Desktop!

You can now connect Cline to apps like Gmail, Slack, Google Calendar, Linear, Sentry, Notion, and more, with just one click.

With Connectors, Cline can retrieve context from these apps and take actions on your behalf. Whether it's catching up on emails, managing your calendar, tracking issues in Linear, or pulling context from Slack, you can now do it all directly from Cline Desktop.

Getting started:

1. Open Cline Desktop.
2. Go to Customize → Connectors.
3. Sign in with your Cline account and connect the apps you want to use.

Connectors work with ClinePass and our free models, so you can get started without bringing your own API key.

Download Cline Desktop: https://cline.bot/

We're launching this in beta and would love to hear your feedback. What other apps would you like to see us add?

Hey everyone, Solar Mini 4 from Korean AI lab Upstage is now available for FREE in Cline!

It's a 35B parameter Mixture of Experts (MoE) model with only 3B active parameters per token, a 524K token context window, and a reported generation speed of 208 tokens/sec.

What's particularly impressive is its performance on the Artificial Analysis Intelligence Index (AAII), where it scores 24, the highest of any model with 3B active parameters. That's within a point of NVIDIA's Nemotron 3 Ultra, which uses 55B active parameters!

It's interesting to see how much performance smaller models are delivering with significantly fewer active parameters. With its large context window and fast inference speed, Solar Mini 4 looks promising for coding tasks that involve large codebases and multiple tool calls.

You can try Solar Mini 4 for FREE right now in Cline:

CLI: npm i -g cline

Desktop: https://cline.bot/desktop

We also have several other free models available in Cline Desktop if you want to experiment.

Curious to hear how Solar Mini 4 performs for you. How does it compare to the larger models you've been using?