Unsloth AI (@UnslothAI) / X

Unsloth AI

687 posts

Unsloth AI

@UnslothAI

Train and run models locally! 🦥 github.com/unslothai/unsl…

San Francisco, CA

Joined November 2023

Pinned
Unsloth AI
@UnslothAI
Mar 17
Introducing Unsloth Studio ✨ A new open-source web UI to train and run LLMs. • Run models locally on Mac, Windows, Linux • Train 500+ models 2x faster with 70% less VRAM • Supports GGUF, vision, audio, embedding models • Auto-create datasets from PDF, CSV, DOCX •
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Unsloth AI
@UnslothAI
19h
What’s your go-to local model right now?
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Unsloth AI
@UnslothAI
Jun 23
1-bit GLM-5.2 GGUF vs. Claude 4.8 Opus vs. GPT-5.5 We gave 3 models the same prompt and compared one-shot outputs. The 1-bit GLM-5.2 GGUF ran locally on a Mac Studio M3 Ultra with 256GB RAM at ~21.6 tok/s. Which output do you like best? GGUF: huggingface.co/unsloth/GLM-5.…
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Unsloth AI
@UnslothAI
Jun 18
GLM-5.2 can now be run locally!🔥 The 2-bit model retains ~82% accuracy after we shrunk it from 1.51TB to 238GB (-84% size). Run on a 256GB Mac or RAM/VRAM setups. GLM-5.2 is the strongest open model to date. Guide: unsloth.ai/docs/models/gl… GGUF: huggingface.co/unsloth/GLM-5.…
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Unsloth AI
@UnslothAI
Jun 18
GLM-5.2 can now be run locally!🔥 The 2-bit model retains ~82% accuracy after we shrunk it from 1.51TB to 238GB (-84% size). Run on a 256GB Mac or RAM/VRAM setups. GLM-5.2 is the strongest open model to date. Guide: unsloth.ai/docs/models/gl… GGUF: huggingface.co/unsloth/GLM-5.…
Z.ai
@Zai_org
Jun 16
Introducing GLM-5.2: Frontier Intelligence, Open Weights - Significant improvements in coding and agentic tasks - Strong long-horizon capabilities with a 1M context window - Two levels of reasoning effort: GLM-5.2 (max) pushes the limits, while GLM-5.2 (high) strikes a strong
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Unsloth AI
@UnslothAI
Jun 18
You can run GLM-5.2 and other models directly in Unsloth Studio:
GitHub - unslothai/unsloth: Unsloth Studio is a web UI for training and running open models like...
From github.com
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Unsloth AI
@UnslothAI
Jun 15
You can now run Kimi K2.7 Code locally! 🌘 We shrank the 1T model to 325GB (-48%) via Dynamic 2-bit where important layers are upcasted. Run at >40 tok/s on 330GB RAM/VRAM setups. Run full precision on 610 GB. Guide: unsloth.ai/docs/models/ki… GGUF: huggingface.co/unsloth/Kimi-K…
Kimi.ai
@Kimi_Moonshot
Jun 12
🌘 Kimi-K2.7-Code, our latest coding model, is now released and open-sourced! 🔷 Improved coding & agent performance over K2.6: +21.8% on Kimi Code Bench v2, +11.0% on Program Bench, and +31.5% on MLS Bench Lite. 🔷 Reasoning efficiency: Less overthinking, with 30% lower
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Unsloth AI reposted
Ivan Fioravanti ᯅ
@ivanfioravanti
Jun 12
Local AI in action! MiniMax M3 unning locally on a single M3 Ultra 512GB in Unsloth Studio! 🔥 Here UD-Q5_K_XL decoding at 32.5 toks/s!
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Unsloth AI
@UnslothAI
Jun 12
MiniMax M3 can now be run locally!🔥 MiniMax-M3 is a new 428B (23B active) open model with 1M context that performs on par with Gemini 3.1 Pro. Run Dynamic 2-bit GGUF on 138GB RAM/VRAM or 3-bit on 165GB. GGUF: huggingface.co/unsloth/MiniMa… Guide: unsloth.ai/docs/models/mi…
MiniMax (official)
@MiniMax_AI
Jun 12
MiniMax M3, Open-Weight, Now On Hugging Face , with only ~428B parameters and ~23B activated parameters Weights: huggingface.co/MiniMaxAI/Mini… MiniMax Sparse Attention: huggingface.co/papers/2606.13…
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Unsloth AI
@UnslothAI
Jun 12
DiffusionGemma can now run at 2000+ tokens/sec! ⚡ We made local DiffusionGemma inference 1.8× faster. Run it on 18GB RAM via Unsloth Studio. GitHub: github.com/unslothai/unsl… Guide: unsloth.ai/docs/models/di…
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Unsloth AI
@UnslothAI
Jun 10
Google releases DiffusionGemma.✨ The new 26B-A4B diffusion text model runs locally on 18GB RAM. It supports high-speed text generation, thinking, image, video and 256K context. Run and train via Unsloth Studio. GGUF: huggingface.co/unsloth/diffus… Guide: unsloth.ai/docs/models/di…
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Unsloth AI
@UnslothAI
Jun 11
Gemma 4 now runs 2x faster with MTP GGUFs! Run locally on just 6GB RAM. ⚡️ MTP enables Google Gemma 4 run ~1.4–2.2× faster with no accuracy loss. Gemma 4 12B MTP can run at 162 t/s vs. 52 t/s without MTP. 31B reaches 101 t/s. GGUFs + Guide: unsloth.ai/docs/models/mtp
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Unsloth AI
@UnslothAI
Jun 10
Google releases DiffusionGemma.✨ The new 26B-A4B diffusion text model runs locally on 18GB RAM. It supports high-speed text generation, thinking, image, video and 256K context. Run and train via Unsloth Studio. GGUF: huggingface.co/unsloth/diffus… Guide: unsloth.ai/docs/models/di…
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Google Gemma
@googlegemma
Jun 10
Meet DiffusionGemma! An experimental open model that explores a fast approach to text generation, released under an Apache 2.0 license. Moving beyond sequential, token-by-token processes to generate entire blocks of text simultaneously. Here’s what’s new with DiffusionGemma: 👇
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Unsloth AI
@UnslothAI
Jun 5
Google releases Gemma 4 QAT. ✨ You can now run Gemma 4 at 3x less memory with near original performance. Quantization-Aware Training (QAT) makes it possible to run Gemma 4 26B-A4B on 16GB RAM. GGUFs: huggingface.co/collections/un… QAT Guide: unsloth.ai/docs/models/ge…
Google Gemma
@googlegemma
Jun 5
We just dropped Gemma 4 Quantization-Aware Training (QAT) checkpoints on Hugging Face! All Gemma 4 model sizes and their drafters are now optimized with QAT to cut memory requirements and maximize on-device performance!
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Unsloth AI
@UnslothAI
Jun 4
You can now run NVIDIA Nemotron 3 Ultra, a new 550B open model. Nemotron-3-Ultra-550B-A55B is NVIDIA's largest LLM yet, with 1M context, frontier coding & chat. Run 2-bit on 200GB RAM, 3-bit on 256GB, 8-bit on 600GB. GGUF: huggingface.co/unsloth/NVIDIA… Guide: unsloth.ai/docs/models/ne…
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NVIDIA AI
@NVIDIAAI
Jun 4
Today we're shipping Nemotron 3 Ultra. A 550B MoE frontier-intelligence open model built for long-running agents. It delivers 5x faster inference and lowers the cost of complex agentic tasks by up to 30% versus other open frontier models.
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Unsloth AI
@UnslothAI
Jun 4
2-bit Gemma 4 12B GGUF, only 4.66 GB on disk, managed to cite 15 sites from a single prompt. Try this locally on >6GB RAM via Unsloth Studio. GitHub: github.com/unslothai/unsl…
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Unsloth AI
@UnslothAI
Jun 3
Gemma 4 12B can now run locally on just 8GB RAM via Dynamic GGUFs. Google's new model, Gemma 4 12B Unified supports image, audio and 256K context. You can run and train the model via Unsloth Studio. GGUF: huggingface.co/unsloth/gemma-… Guide: unsloth.ai/docs/models/ge…
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