We’re releasing new Qwen3.8-27B GGUFs with 10% higher accuracy.
Unsloth Dynamic V3 outperforms others by >10% on Div-300, KLD & more benchmarks.
We also release 1-bit quants that retain 77% accuracy. Run on 8GB RAM.
Thanks to you guys, Qwen3.8-27B Unsloth GGUF is now the #2 trending model on Hugging Face with 2.7M downloads! 💗
Unsloth also reached #3 trending on GitHub!
Thanks so much for the love! Announcement coming tomorrow morning :)
It's still a WIP but after 2 years of our website, we never had a darkmode except for our docs. Well after lots and lots of feedback, we finally have a darkmode. I can't believe it took this long but hey, it's here and hope you don't avoid going to our website anymore 😅
We'll also be doing a whole rebrand and also redesign of website in like a month or two or so, so what you're seeing is temporary :)
Thanks so much and if you have any feedback, be my guest!
Website: https://unsloth.ai/
Hey guys just yesterday we were trending at #5 and now #3. Thanks so much guys! We couldn't believe it and it's literally all thanks to you guys! 🙏😭
We're currently adding many features and improvements especially regarding speed for UI/UX since some of y'all said it was laggy and also many extra new features including auto compaction etc
Feel free to star us on GitHub: https://github.com/unslothai/unsloth
Hey guys thanks so much for the support for Unsloth Desktop, we're currently trending at #5 overall on GitHub and the #2 overall package for Python! ❤️🦥
Feel free to Star us on GitHub: https://github.com/unslothai/unsloth
We are also adding a lot of new updates. If you have any feature requests or feedback, it would be best to make a GitHub issue, but also feel free to make a comment here.
Thanks so much once again for your support!
Here's 4-bit Qwen3.8-27B GGUF generating an interactive volcano simulation with geology, thermodynamics, fluid flow, buoyancy/drag, projectiles, cooling, groundwater interaction, and environmental effects in Unsloth Desktop.
What’s your favorite prompt to test a new model with? Full prompt in comment.
Hey guys, we got some updates since we last updated Unsloth Desktop.
First of all we wanted to thank you for the support for our launch. It really means the world to us and it was amazing seeing you enjoy it as much as we loved making it.
Secondly, we took your feedback seriously. We dmed and messaged some of you individually for feedback and took it in. Currently we have 60+ new PRs which havent been merged yet but for now, we've addressed the most critical issues:
llama-server flags.You can view the full release here: https://github.com/unslothai/unsloth/releases/tag/v0.1.800-beta
Qwen3.8-27B can now be run locally! ✨ Run on 17GB RAM via Unsloth Dynamic GGUFs and Unsloth Desktop. Qwen3.8-27B is by far the strongest model for its size.
Guide: https://unsloth.ai/docs/models/qwen3.8
We uploaded NVFP4 quants! GGUF: https://huggingface.co/unsloth/Qwen3.8-27B-GGUF
We also did a new release for Unsloth Desktop with many new features and performance increases!
Unsloth Desktop Highlights:
Unsloth Desktop Performance Improvements:
llama-server flags.Thank you!
Processing img az99qopcg8jh1...
So same as my prior post 1bit test... although this 1bit is a bit interesting you can read on unlsoth blog https://unsloth.ai/docs/models/qwen3.8 508 gigs being used I am using unsloth studio on the mac ultra 512. Im getting ~50pp and ~9.6 tgen drop to 5 at 50k tokens
Yes My computer i screaming at me. The things Im putting it through :'D
Flight Sim: the code for its is kind cool it is rendering gravity and physics rather then just a vector controls and force based dynamics which is more complex but doesn't show in the gameplay. I really like it even comparing to GLM 5.2 Not because of visuals because that we can just add later but because the controls feel kinda nice. (might be just the new toy bias). There is a bug with the water that its not rendering but Im just keeping whatever it output without telling it to fix it. I did run out of token head room 3 times, 1st i set 32k limit that didnt even finish the though process. then 65k it output the game and half output it. 96k it finished and tested to make sure it ran fixed a gravity bug where upward force was higher than gravity and accelerated upward. this is on Medium reasoning effort not xhigh. I dont have the token space for xhigh.
SVG Tests: All Medium Reasoning
Basic >_>' I know its dumb to test a 2.4T model. But Ill do the 3d renders later. just remember its almost like 1.5bit average
Panda: " generate an svg of a panda sitting having a picnic in Japan, make it beautiful"
PS4 Controller: It obviously isn't fully right but its very coherent and things are in the right places. This is a difficult test for models
Capybara: "generate a capybara having a yuzu in an onsen as beautiful as possible" this is some other world drawing... it used python to generate the noise and other things like snow and textures and then generated the svg in the same tool call
Pelican : "generate an svg of a pelican riding a bike" (This might have been on low thinking it only thought for 22 seconds I also didnt ask for it to be beautiful). But no missing parts, everything in the right place except the legs are on the same side of the bike.
You can now fine-tune Meta Muse Glimmer 30B for free! 🔥
Our free notebook also supports GRPO RL training.
Unsloth trains Muse Glimmer 1.5× faster with 50% less VRAM vs FA2 setups. Train locally with 24GB VRAM.
Guide: https://unsloth.ai/docs/models/muse-glimmer/train
Notebooks: https://unsloth.ai/docs/models/muse-glimmer/train#free-fine-tuning-notebooks
You can ofcourse also train the model in unsloth desktop
Hey guys, thanks so much for all the support for Unsloth Desktop yesterday and today, we appreciate every single of you and hope you are enjoying it as much as we made it.
Someone launched Unsloth Desktop on Product Hunt today,, so feel free to give us an upvote if you have any spare time: https://www.producthunt.com/products/unsloth/launches/unsloth-desktop
Also if you have any extra feedback or feature requests feel free to ask on GitHub or here!!
Thanks so much again guys! ❤️🦥
2-bit Nemotron 3.5 GGUF cited 80+ websites, executed code & searched for 10 real-world locations. Interestingly it never failed which is pretty impressive
The video was sped up by 6x.
Run and train via Unsloth Desktop.
GGUF: https://huggingface.co/unsloth/NVIDIA-Nemotron-3.5-Lightning-30B-A3B-GGUF
Qwen3.8 can now be run locally! 🔥
We shrank Qwen3.8-2.4T-A95B from 4.9TB to 397GB (-91% size) via Dynamic 1-bit by selectively quantizing layers
Run on 410GB+ RAM/VRAM via Unsloth Desktop or llama.cpp
Qwen3.8 rivals GPT-5.6 Sol on many benchmarks
Guide: https://unsloth.ai/docs/models/qwen3.8
GGUF: https://huggingface.co/unsloth/Qwen3.8-2.4T-A95B-GGUF
Currently the super small GGUFs only work via Unsloth.
Thanks!!
Hey guys thanks so much for all the love for Unsloth Desktop. Here's a breakdown of our 'main' features:
- Code execution: Unsloth improves tool calling with: 30–80% higher tool-call accuracy across models, more reliable call termination to reduce loops, better healing and deduplication to prevent XML leakage. Get 50% more accurate, self-healing tool calls and sandboxed code execution.
- Generate Images and Videos: For MiniMax-H3 on an NVIDIA B200, a 960×544, 124-frame, 8-step generation dropped from 70+ seconds to 13 seconds. Works with FLUX, Z-Image, LTX, Wan and fine-tuned LoRA adapters. Transform, inpaint, extend, upscale, reference and edit existing images.
- Serve and access your models anywhere: Serve your local or over HTTPS through Unsloth's free Cloudflare tunnel. Check a run from your phone, your laptop, or anywhere else you happen to be. Bind the app to your network with -H 0.0.0.0, or open a free Cloudflare tunnel for HTTPS:
- Connect your agent: Unsloth lets you connect Claude Code, Codex, Hermes, OpenCode, and other coding agents to a local model via the unsloth start command. The entire workflow can run offline on your own hardware. Unsloth Studio automatically configures the endpoint, API key, provider, model, and context length for each launch, so you can use your preferred agent without modifying them.
You can view details in our blog: https://unsloth.ai/docs/desktop
Available now on GitHub: https://github.com/unslothai/unsloth
Thanks so much!
Hi guys, we're super excited to announce Unsloth Desktop today,
The first desktop app to run and train models locally.
Unsloth Desktop is now available on unsloth.ai and GitHub.
Thank you and we're here to answer any questions!
What a powerful model even at 2-bit! Muse Glimmer did a complete repo bug hunt for 5 mins nonstop with: evidence, repro, fix, tests and a PR writeup.
You can now run and train it in Unsloth.
GitHub repo: https://github.com/unslothai/unsloth
Meta releases Muse Glimmer, a new 30B open model that runs on 18GB RAM.
Released under Apache 2.0, Muse Glimmer is designed for agentic and coding workloads and supports 128K+ context. It is the strongest agentic model for its size.
Run and train via Unsloth Desktop.
Hey guys, DeepSeek-V4-Flash can now run 2× faster locally with DSpark! ⚡️
DSpark enables V4-Flash-0731 GGUFs to generate ~1.4–2× faster with no accuracy change.
DeepSeek-V4-Flash-0731 can reach at 120 tokens/s. DSpark is automatically enabled in Unsloth Studio!
GGUFs: https://huggingface.co/unsloth/DeepSeek-V4-Flash-0731-GGUF
Guide: https://unsloth.ai/docs/models/deepseek-v4
Thank you!
Qwen just announced Qwen3.8-27B along with Qwen3.8-Max! 🔥
Qwen3.8-27B will run locally on 17GB RAM/VRAM setups and is expected to be the best performing model for its size.
We can't wait to support it at Unsloth AI. Qwen3.8-27B benchmarks are yet to be revealed, only Qwen3.8 -Max for now.
