Glimpse-v1

A lightweight, open vision-language model built to understand and summarize home security camera events.

ollama run llmvision/glimpse-v1

Install Ollama, then paste the command above. See the project site for documentation.

Model summary

Developer	LLM Vision
Base model	google/gemma-3-4b-pt
Architecture	Gemma 3 (vision-language)
Parameters	~4B
Modality	Image + text → text
Training samples	5,000+ real-world home security camera events
Reported gain	1.9× accuracy improvement over the base model on the target task
License	Gemma Terms of Use

Intended use

Glimpse-v1 is purpose-built for summarizing and describing footage from home security cameras — for example, generating short natural-language descriptions of motion events, deliveries, visitors, pets, or vehicles, locally on consumer hardware.

Designed for

• Local, privacy-preserving smart-home automations
• Event summaries for camera notifications
• Integrations with home-automation platforms (e.g. Home Assistant via the LLM Vision project)
• Edge devices and machines with limited VRAM/RAM

Not designed for

• General-purpose visual question answering or document understanding
• Person identification, biometric recognition, or surveillance of identifiable individuals
• Safety-critical decisions (medical, legal, security response) without human review
• Use cases prohibited by the Gemma Prohibited Use Policy

Languages

English only for now.

Why a small model?

Glimpse-v1 is a compact 4B-parameter model deliberately sized to run on hardware with limited memory and compute. The goal is private, local AI for the home: your camera footage never has to leave your network, and you avoid recurring API costs.

Performance

Glimpse-v1 reports a 1.9× accuracy improvement over the base Gemma 3 4B model on home-security event summarization. See the project site for the latest benchmarks.

Training

• Base: Gemma 3 4B
• Data: ~5,000 curated real-world home security camera events spanning diverse scenes, lighting conditions, and event types
• Objective: Supervised fine-tuning for concise, factual event descriptions

Files in this repository have been modified from the original Gemma 3 release as part of this fine-tune.

How to use

Ollama (recommended)

ollama run llmvision/glimpse-v1

Transformers

from transformers import AutoProcessor, AutoModelForImageTextToText
import torch
model_id = "llmvision/glimpse-v1"
processor = AutoProcessor.from_pretrained(model_id)
model = AutoModelForImageTextToText.from_pretrained(
model_id, torch_dtype=torch.bfloat16, device_map="auto"
)

messages = [
{"role": "user", "content": [
{"type": "image", "url": "path/to/frame.jpg"},
{"type": "text", "text": "Summarize this camera event in one sentence."},
]},
]
inputs = processor.apply_chat_template(
messages, add_generation_prompt=True, tokenize=True,
return_dict=True, return_tensors="pt",
).to(model.device)
out = model.generate(inputs, max_new_tokens=128)
print(processor.decode(out[0], skip_special_tokens=True))

Limitations and risks

• Domain-specific. Outside of home-security framing, quality drops noticeably.
• Hallucination. Like all VLMs, it can invent details (people, objects, actions) not present in the image. Treat outputs as suggestions, not ground truth.
• Bias. Training data reflects the distribution of available home camera footage and may underperform on under-represented scenes, lighting, or demographics.
• Privacy. Although the model runs locally, you are responsible for handling footage of identifiable people in line with local laws (e.g. GDPR).
• Not a security system. Do not use Glimpse-v1 as the sole signal for emergency response.

License

This model is a Gemma Model Derivative and is distributed under the Gemma Terms of Use. Use, reproduction, modification, and redistribution are subject to those terms, including the Gemma Prohibited Use Policy.

By downloading or using Glimpse-v1 you agree to the Gemma Terms of Use. If you redistribute Glimpse-v1 or any derivative of it, you must:

1. Pass these terms through to your recipients as an enforceable provision.
2. Provide recipients a copy of the Gemma Terms of Use.
3. Mark any modified files with prominent notices that they have been modified.
4. Include a NOTICE file containing:

   Gemma is provided under and subject to the Gemma Terms of Use found at ai.google.dev/gemma/terms.

Citation

@misc{glimpse_v1,
title  = {Glimpse-v1: A compact vision-language model for home security event understanding},
author = {Valentin Fröhlich},
year   = {2026},
url    = {https://llmvision.org/glimpse/}
}

Acknowledgements

Built on Google Gemma 3. Distributed via Ollama and Hugging Face.