Updates for developers building with @lmstudio 👾
Joined June 2025
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We made @lmstudio's MLX Engine a lot faster in the latest release.
Read the technical deep dive from @ostensiblyneil.
P.S. it's all open source!
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LM Studio with Multi Token Prediction (MTP) is now in beta.
1. Update to 0.4.14 3 in-app
2. Make sure your llama.cpp engine is 2.15.0
3. Turn on MTP when loading a model
Use a model that supports it, like Qwen3.6-35B-A3B-MTP-GGUF or Qwen3.6-27B-MTP-GGUF
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Batching for vision models is now available in Beta with our latest MLX engine update 👾
The updated engine also brings major improvements to caching for faster inference overall.
Turn on Developer Mode, choose the beta runtime channel, and select LM Studio MLX v1.8.1.
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Locally AI is joining LM Studio!
We are beyond excited to welcome @adrgrondin and @LocallyAIApp to the LM family.
Together we are doubling down on native AI experiences across your devices, anywhere you go.
Read our announcement lmstudio.ai/blog/locally-ai-…
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We worked with @NVIDIAAI to bring up support for DGX Station GB300 at launch!
✨ 748GB of coherent memory
👾 Install llmster and enable LM Link
🛰️ Load models and use them from other devices
Learn how to set it up: lmstudio.ai/blog/dgx-station
🚀⚡️🔥
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LM Studio 0.4.7 Beta (build 3) is now available.
This build contains many bug fixes:
🐛🔨 LaTeX ($ signs) rendering, extraneous <think> tags in coding agents, fixes for tool calling parsing, and more!
Update in-app or from lmstudio.ai/beta-releases
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Nemotron 3 Super by @nvidia is now live in LM Studio!
🦾 Open-weight 120B MoE, 12B active params
📜 Supports up to 1M tokens context window
Requires about ~83GB to run locally 🚀
lmstudio.ai/models/nemotron-…
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LM Studio Developers retweeted
Mar 6
One of the coolest uses of @lmstudio and @AIatAMD is using LM Link to have a Framework Desktop be a remote inference server for a laptop, including something little like Framework Laptop 12. It feels native on the laptop, but gets the desktop’s performance.
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|￣￣￣￣￣￣￣￣￣￣￣￣￣ |
| lms get qwen3.5-9b |
|＿＿＿＿＿＿＿＿＿＿＿＿＿ |
(\__/) ||
(•ㅅ•) ||
/ づ
Mar 2
🚀 Introducing the Qwen 3.5 Small Model Series
Qwen3.5-0.8B · Qwen3.5-2B · Qwen3.5-4B · Qwen3.5-9B
✨ More intelligence, less compute.
These small models are built on the same Qwen3.5 foundation — native multimodal, improved architecture, scaled RL:
• 0.8B / 2B → tiny, fast, great for edge device
• 4B → a surprisingly strong multimodal base for lightweight agents
• 9B → compact, but already closing the gap with much larger models
And yes — we’re also releasing the Base models as well.
We hope this better supports research, experimentation, and real-world industrial innovation.
Hugging Face: huggingface.co/collections/Q…
ModelScope: modelscope.cn/collections/Qw…
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Introducing LM Link ✨ Connect to remote instances of LM Studio, securely.
🔐 End-to-end encrypted
📡 Load models locally, use them on the go
🖥️ Use local devices, LLM rigs, or cloud VMs
Launching in partnership with @Tailscale
Try it now: link.lmstudio.ai
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Debugging tips 👇
For engine level logs, try:
> lms log stream -s runtime
To see input output to the model:
> lms log stream
Make sure to be on LM Studio 0.4.1
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lms get qwen/qwen3-coder-next
Feb 3
🚀 Introducing Qwen3-Coder-Next, an open-weight LM built for coding agents & local development.
What’s new:
🤖 Scaling agentic training: 800K verifiable tasks executable envs
📈 Efficiency–Performance Tradeoff: achieves strong results on SWE-Bench Pro with 80B total params and 3B active
✨ Supports OpenClaw, Qwen Code, Claude Code, web dev, browser use, Cline, etc
🤗 Hugging Face: huggingface.co/collections/Q…
🤖 ModelScope: modelscope.cn/collections/Qw…
📝 Blog: qwen.ai/blog?id=qwen3-coder-…
📄 Tech report: github.com/QwenLM/Qwen3-Code…
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See how to configure it 👇
lmstudio.ai/blog/claudecode
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LM Studio Developers retweeted
Jan 30
this is extremely epic. allows one to get a full-featured MCP client in LMStudio and integrate it w/ whatever pipeline you like. used to automate my @moltbook bot locally
Use your local MCP servers via API
LM Studio 0.4.0 introduces a new API endpoint
𝙿𝙾𝚂𝚃 /𝚊𝚙𝚒/𝚟𝟷/𝚌𝚑𝚊𝚝
It makes it possible to use your local models with MCP servers from your mcp.json
Check the docs for detailed code examples! lmstudio.ai/docs/developer/c…
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