RecursiveSI/flint-nvfp4-gguf
Text Generation • 40B • Updated • 2
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#1 opened about 7 hours ago
by 
PotatoSniffer
alexey-recursive
published 3
models about 7 hours ago
lvmopt
published a
model about 7 hours ago
alexey-recursive
updated 3
models about 8 hours ago
lvmopt
updated a
model about 9 hours ago
danielhanchen
posted an update 2 days ago
Post
4,268
Run DeepSeek V4.1-Flash-1017 locally! 🐳
We made 1-bit retain ~88.2% accuracy while shrinking size from 508GB to 250GB (−52%).
Run on a 128GB+ RAM device. V4.1 Flash 1017 is the strongest open model to date
Guide: https://unsloth.ai/docs/models/deepseek-v4.1-flash
GGUF: unsloth/DeepSeek-V4.1-Flash-1017-GGUF
We made 1-bit retain ~88.2% accuracy while shrinking size from 508GB to 250GB (−52%).
Run on a 128GB+ RAM device. V4.1 Flash 1017 is the strongest open model to date
Guide: https://unsloth.ai/docs/models/deepseek-v4.1-flash
GGUF: unsloth/DeepSeek-V4.1-Flash-1017-GGUF
danielhanchen
posted an update 13 days ago
Post
5,002
You can now train your own Decision model like Jev locally!
We increased Qwen3.5 0.8B’s aggregate accuracy from 20.7% to 74.3% across 3 decision benchmarks - on just 4GB VRAM.
Turn any LLM like Qwen3.8, Gemma 4 into decision models with our open-source Unsloth repo.
GitHub: https://github.com/unslothai/unsloth
Guide: https://unsloth.ai/docs/basics/train-your-own-decision-model-with-unsloth
We increased Qwen3.5 0.8B’s aggregate accuracy from 20.7% to 74.3% across 3 decision benchmarks - on just 4GB VRAM.
Turn any LLM like Qwen3.8, Gemma 4 into decision models with our open-source Unsloth repo.
GitHub: https://github.com/unslothai/unsloth
Guide: https://unsloth.ai/docs/basics/train-your-own-decision-model-with-unsloth
- 5 replies
danielhanchen
posted an update 15 days ago
Post
4,062
Google releases EmbeddingGemma 2, a new open embedding model that runs locally on 0.5GB RAM.
The 740M parameter Apache 2.0 model combines a 270M text model with vision (170M) + audio (300M).
Run & train the model via Unsloth.
GGUF: unsloth/embeddinggemma-2-GGUF
Guide: https://unsloth.ai/docs/models/embeddinggemma-2
The 740M parameter Apache 2.0 model combines a 270M text model with vision (170M) + audio (300M).
Run & train the model via Unsloth.
GGUF: unsloth/embeddinggemma-2-GGUF
Guide: https://unsloth.ai/docs/models/embeddinggemma-2
danielhanchen
posted an update 26 days ago
danielhanchen
posted an update 29 days ago
Post
3,728
Qwen-Image-2.1 can now run locally on 12GB VRAM with Unsloth GGUFs! 🖼️
The 7B model performs on par with Nano Banana 2.0.
For higher quality, you can also run Dynamic FP8 on just 6GB of VRAM via offloading.
GGUF: unsloth/Qwen-Image-2.1-GGUF
Guide: https://unsloth.ai/docs/models/qwen-image-2.1
The 7B model performs on par with Nano Banana 2.0.
For higher quality, you can also run Dynamic FP8 on just 6GB of VRAM via offloading.
GGUF: unsloth/Qwen-Image-2.1-GGUF
Guide: https://unsloth.ai/docs/models/qwen-image-2.1
danielhanchen
posted an update about 1 month ago
Post
6,905
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: unsloth/Qwen3.8-27B-GGUF
Guide: https://unsloth.ai/docs/models/qwen3.8
The model hit 10M downloads and 3.7K likes in just 24 days on Hugging Face - all thanks to you.
GGUF: unsloth/Qwen3.8-27B-GGUF
Guide: https://unsloth.ai/docs/models/qwen3.8
- 5 replies
cranial-xix
submitted a
paper to Daily Papers 2 months ago
danielhanchen
posted an update 2 months ago
Post
7,572
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 + sandboxed code exec
• Works for CPU + multiGPU setups - NVIDIA, AMD, Intel, Mac
• Train models 2× faster with 70% less VRAM
• Private web search, deep research, RAG, MCP and exports (NVFP4, GGUF)
• Use Unsloth’s OpenAI-compatible API and cloud models
• Securely deploy LLMs remotely and access anywhere
Unsloth Desktop is now available on http://unsloth.ai
and GitHub.
GitHub: https://github.com/unslothai/unsloth
Blog and Guide: https://unsloth.ai/docs/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 + sandboxed code exec
• Works for CPU + multiGPU setups - NVIDIA, AMD, Intel, Mac
• Train models 2× faster with 70% less VRAM
• Private web search, deep research, RAG, MCP and exports (NVFP4, GGUF)
• Use Unsloth’s OpenAI-compatible API and cloud models
• Securely deploy LLMs remotely and access anywhere
Unsloth Desktop is now available on http://unsloth.ai
and GitHub.
GitHub: https://github.com/unslothai/unsloth
Blog and Guide: https://unsloth.ai/docs/desktop
- 6 replies
danielhanchen
posted an update 3 months ago
Post
3,835
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.
GGUFs: unsloth/DeepSeek-V4-Flash-0731-GGUF
Guide: https://unsloth.ai/docs/models/deepseek-v4
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.
GGUFs: unsloth/DeepSeek-V4-Flash-0731-GGUF
Guide: https://unsloth.ai/docs/models/deepseek-v4
- 1 reply
danielhanchen
posted an update 3 months ago
Post
3,578
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
danielhanchen
posted an update 3 months ago
Post
5,774
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