Unsloth AI

@UnslothAI

Run and train models locally with the Unsloth Desktop app. 🦥 github.com/unslothai/unsl…

San Francisco, CA

unsloth.ai

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Unsloth AI
@UnslothAI
Aug 11
Introducing Unsloth Desktop 🦥 The first desktop app to run and train models locally. • Open-source. Runs on Mac, Windows and Linux • Supports MLX, diffusion image/video, audio, GGUF • Connect Claude Code and Codex to local LLMs • 50% more accurate, self-healing tool calls +
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Unsloth AI
@UnslothAI
Sep 8
Qwen3.8-27B Unsloth GGUF is now the #1 most-liked GGUF of all time! The model hit 10M downloads and 3.7K likes in just 24 days on Hugging Face - all thanks to you. 🤗🦥 GGUF: huggingface.co/unsloth/Qwen3.… Guide: unsloth.ai/docs/models/qw…
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Unsloth AI
@UnslothAI
Sep 4
We made GLM-5.3-Flash run 3.3x faster locally! Local GGUF inference is now 1.6–3.4× faster with optimized decoding and bonus multi-token prediction. Run 3-bit on 128GB setups via Unsloth Desktop or llama.cpp. Guide: unsloth.ai/docs/models/gl… GGUF: huggingface.co/unsloth/GLM-5.…
Z.ai
@Zai_org
Aug 26
Introducing GLM-5.3-Flash - Leading capabilities at a highly competitive price - Natively multimodal with a 1M-token context window - A 320B-A18B model released under the MIT License - Previously previewed as Ox Alpha, running entirely on Chinese AI chips Blog:
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Unsloth AI
@UnslothAI
Sep 3
You can now run Unsloth GGUFs locally in one-click via Hermes! ✨ Qwen3.8-27B, Qwen3.8-Flash, DeepSeek-V4-Flash and more are all supported.
Nous Research
@NousResearch
Sep 3
00:17
Hermes Desktop now sets up local models in one click. It automatically reads your hardware, picks the best model for you, then downloads it and configures the runtime.
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Unsloth AI
@UnslothAI
Sep 2
Qwen3.8-Flash can now run 1.7× faster locally with MTP!⚡️ GGUFs can reach 170 tokens/s on a RTX PRO 6000. MTP enables Qwen3.8-Flash-Next ~1.3–1.7× faster inference with no accuracy change. GGUFs: huggingface.co/unsloth/Qwen3.… Guide: unsloth.ai/docs/models/qw…
Unsloth AI
@UnslothAI
Aug 26
Qwen3.8-Flash can now be run locally! 🔥 The 125B MoE model outperforms Claude-Opus-4.6 (Max). Run on 75GB RAM via Unsloth GGUFs. Qwen3.8-Flash-Next enables CPU RAM / unified mem setups to deliver near VRAM speeds. Guide: unsloth.ai/docs/models/qw… GGUF: huggingface.co/unsloth/Qwen3.…
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