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Tiny Aya: Bridging Scale and Multilingual Depth
EAGER: Entropy-Aware GEneRation for Adaptive Inference-Time Scaling
Articles
Update README.md
1
#47 opened 3 days ago
by 
tuffie
danielhanchen
posted an update 3 days ago
Post
799
We compared 1-bit Kimi K3 to Claude Opus 5 and GPT 5.6. 🤯
We gave 4 models the same prompt: Create a glass aquarium whose side panel develops a visible crack and then bursts...
1-bit Kimi K3 GGUF ran locally on 4x B200s at 36 tok/s.
GGUF: unsloth/Kimi-K3-GGUF
GitHub repo: https://github.com/unslothai/unsloth
We gave 4 models the same prompt: Create a glass aquarium whose side panel develops a visible crack and then bursts...
1-bit Kimi K3 GGUF ran locally on 4x B200s at 36 tok/s.
GGUF: unsloth/Kimi-K3-GGUF
GitHub repo: https://github.com/unslothai/unsloth
- 1 reply
Terrencez
updated a
model 4 days ago
danielhanchen
posted an update 5 days ago
Post
3636
Kimi K3 can now be run locally! ✨
The 1-bit model retains ~78.9% accuracy after we shrunk it from 1.56TB to 594GB (-62% size).
Run on a Mac Studio connected with 128GB RAM device. Kimi K3 is the strongest open model to date.
GGUF: unsloth/Kimi-K3-GGUF
Guide: https://unsloth.ai/docs/models/kimi-k3
The 1-bit model retains ~78.9% accuracy after we shrunk it from 1.56TB to 594GB (-62% size).
Run on a Mac Studio connected with 128GB RAM device. Kimi K3 is the strongest open model to date.
GGUF: unsloth/Kimi-K3-GGUF
Guide: https://unsloth.ai/docs/models/kimi-k3
- 5 replies
Terrencez
published a
model 6 days ago
danielhanchen
posted an update 14 days ago
Post
4723
Introducing Unsloth for AMD 🚀
You can now train & run LLMs on your AMD hardware
• We collaborated with AMD to enable you to train & run 500+ models on AMD GPUs
• Works on Windows, WSL, Linux
• Train Qwen, Gemma on just 3GB VRAM
GitHub: https://github.com/unslothai/unsloth
Blog + Guide: https://unsloth.ai/docs/basics/amd
You can now train & run LLMs on your AMD hardware
• We collaborated with AMD to enable you to train & run 500+ models on AMD GPUs
• Works on Windows, WSL, Linux
• Train Qwen, Gemma on just 3GB VRAM
GitHub: https://github.com/unslothai/unsloth
Blog + Guide: https://unsloth.ai/docs/basics/amd
- 3 replies
danielhanchen
posted an update 16 days ago
Post
5790
Gemma 4 is now faster and much more accurate! 🚀
Google made huge improvements to tool-calling and chat accuracy, reliability + speed.
To get fixes, re-download our updated GGUF, MLX, NVFP4 quants!
Unsloth quants: https://huggingface.co/collections/unsloth/gemma-4
Gemma 4 Guide: https://unsloth.ai/docs/models/gemma-4
Google made huge improvements to tool-calling and chat accuracy, reliability + speed.
To get fixes, re-download our updated GGUF, MLX, NVFP4 quants!
Unsloth quants: https://huggingface.co/collections/unsloth/gemma-4
Gemma 4 Guide: https://unsloth.ai/docs/models/gemma-4
- 8 replies
streaming support
1
#1 opened 27 days ago
by 
Dusk007
danielhanchen
posted an update 20 days ago
Post
4674
We’re releasing Gemma 4 NVFP4 quants that run 1.5× faster on your GPU.
Gemma-4-12B NVFP4 works on 11GB VRAM.
26B-A4B hits 13K tok/s (B200).
Unsloth NVFP4 enables faster, more accurate 4-bit Blackwell inference.
Blog: https://unsloth.ai/docs/basics/nvfp4
Gemma NVFP4: https://huggingface.co/collections/unsloth/nvfp4
Gemma-4-12B NVFP4 works on 11GB VRAM.
26B-A4B hits 13K tok/s (B200).
Unsloth NVFP4 enables faster, more accurate 4-bit Blackwell inference.
Blog: https://unsloth.ai/docs/basics/nvfp4
Gemma NVFP4: https://huggingface.co/collections/unsloth/nvfp4
- 3 replies
shaun-cassini-cohere
updated a
model 21 days ago
Update README.md
1
#44 opened 25 days ago
by 
SeongKweon
danielhanchen
posted an update 24 days ago
Post
4258
We’re releasing new Qwen3.6 quants that run 2.5× faster on your GPU. ⚡
Qwen3.6-27B NVFP4 runs on 24GB VRAM.
35B-A3B can hit 17,561 tok/s (B200).
We also improved accuracy, tool calling, agent use, and looping.
Qwen3.6 NVFP4: https://huggingface.co/collections/unsloth/nvfp4
Guide: https://unsloth.ai/docs/models/qwen3.6#nvfp4
Qwen3.6-27B NVFP4 runs on 24GB VRAM.
35B-A3B can hit 17,561 tok/s (B200).
We also improved accuracy, tool calling, agent use, and looping.
Qwen3.6 NVFP4: https://huggingface.co/collections/unsloth/nvfp4
Guide: https://unsloth.ai/docs/models/qwen3.6#nvfp4
- 1 reply
Add EvalEval community eval results
#11 opened about 2 months ago
by 
EvalEvalBot
danielhanchen
posted an update 27 days ago
Post
6201
DeepSeek-V4 can now run locally with Unsloth GGUFs! 🐳
Run lossless DeepSeek-V4-Flash on 168GB RAM or
3-bit works on 110GB Mac, RAM, VRAM setups.
Run via Unsloth Studio or llama.cpp.
GGUF: unsloth/DeepSeek-V4-Flash-GGUF
Guide: https://unsloth.ai/docs/models/deepseek-v4
Run lossless DeepSeek-V4-Flash on 168GB RAM or
3-bit works on 110GB Mac, RAM, VRAM setups.
Run via Unsloth Studio or llama.cpp.
GGUF: unsloth/DeepSeek-V4-Flash-GGUF
Guide: https://unsloth.ai/docs/models/deepseek-v4
stvincent-cohere
published an article 27 days ago
Article
Meet Cohere Transcribe Arabic
CohereLabs
• • 10 shaun-cassini-cohere
published a
Space 27 days ago
shaun-cassini-cohere
published a
model 27 days ago
shaun-cassini-cohere
updated a
Space 27 days ago
danielhanchen
posted an update about 1 month ago
Post
3367
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: unsloth/GLM-5.2-GGUF
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: unsloth/GLM-5.2-GGUF
- 3 replies
danielhanchen
posted an update about 2 months ago
Post
4611
Google's new 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: https://github.com/unslothai/unsloth
Guide: https://unsloth.ai/docs/models/diffusiongemma
We made local DiffusionGemma inference 1.8× faster.
Run it on 18GB RAM via Unsloth Studio.
GitHub: https://github.com/unslothai/unsloth
Guide: https://unsloth.ai/docs/models/diffusiongemma
- 4 replies