richardyoung/SmolVLM2-2.2B-Instruct-GGUF overview
SmolVLM2 2.2B Instruct GGUF GGUF quantizations of HuggingFaceTB/SmolVLM2 2.2B Instruct https://huggingface.co/HuggingFaceTB/SmolVLM2 2.2B Instruct for use with…
Runs locally from ~1.04 GB disk (4 GB VRAM class GPUs with llama.cpp / guIDE).
Repository Files & Downloads
Model Details
| Model ID | richardyoung/SmolVLM2-2.2B-Instruct-GGUF |
|---|---|
| Author | richardyoung |
| Pipeline | — |
| License | apache-2.0 |
| Base model | HuggingFaceTB/SmolVLM2-2.2B-Instruct |
| Last modified | 2026-09-26T19:09:47.000Z |
Model README
---
language:
- en
license: apache-2.0
library_name: transformers
base_model: HuggingFaceTB/SmolVLM2-2.2B-Instruct
tags:
- vision
- multimodal
- llama-cpp
- gguf
- quantized
---
SmolVLM2-2.2B-Instruct GGUF
GGUF quantizations of HuggingFaceTB/SmolVLM2-2.2B-Instruct for use with llama.cpp and Ollama.
Model Description
SmolVLM2 is a compact 2.2B parameter vision-language model from HuggingFace with video understanding capabilities. It's designed to be fast and efficient while maintaining strong performance on vision-language tasks.
Key Features
- Compact & Fast - Only 2.2B parameters, runs efficiently on consumer hardware
- Vision & Video - Understands both images and video frames
- Instruction-tuned - Optimized for following user instructions
- Apache 2.0 - Fully open source
Available Quantizations
| Filename | Quant | Size | Description |
|----------|-------|------|-------------|
| SmolVLM2-2.2B-Instruct-Q4_K_M.gguf | Q4_K_M | 1.0 GB | Best balance of quality and speed (recommended) |
| SmolVLM2-2.2B-Instruct-Q8_0.gguf | Q8_0 | 1.8 GB | Higher quality |
| SmolVLM2-2.2B-Instruct.gguf | F16 | 3.4 GB | Full precision |
Usage
With Ollama
# Pull and run (Q4_K_M by default)
ollama run richardyoung/smolvlm2-2.2b-instruct
# Or specific quantization
ollama run richardyoung/smolvlm2-2.2b-instruct:q8_0
ollama run richardyoung/smolvlm2-2.2b-instruct:f16
With llama.cpp
# Download a quantization
wget https://huggingface.co/richardyoung/SmolVLM2-2.2B-Instruct-GGUF/resolve/main/SmolVLM2-2.2B-Instruct-Q4_K_M.gguf
# Run with llama.cpp
./llama-cli -m SmolVLM2-2.2B-Instruct-Q4_K_M.gguf -p "Describe this image:" --image your_image.jpg
Technical Requirements
- Minimum: 4GB RAM, any modern CPU
- Recommended: 8GB RAM or Apple Silicon Mac
Chat Template
SmolVLM2 uses the ChatML format:
<|im_start|>system
{system_message}<|im_end|>
<|im_start|>user
{user_message}<|im_end|>
<|im_start|>assistant
{assistant_response}<|im_end|>
Links
- Original Model: HuggingFaceTB/SmolVLM2-2.2B-Instruct
- Ollama: richardyoung/smolvlm2-2.2b-instruct
Credits
- Original Model: HuggingFace
- Quantization: Richard Young (deepneuro.ai)
License
Apache 2.0
---
Built & maintained by Richard Young · DeepNeuro
Run richardyoung/SmolVLM2-2.2B-Instruct-GGUF with guIDE
Download guIDE — the AI-native code editor with local LLM inference and 69 built-in tools.
Source: Hugging Face · Compare models