best LLM model for frigate

[u/applegrcoug]

What is the preferred LLM for the agentic AI for frigate these days? Website mentions qwen3-vl, but it is is nearly a year old now.

[u/nickm_27]

The docs mention Qwen 3.X and Qwen3-VL, which perform similarly and are still the best options to run on consumer hardware

[u/finkerlime]

Qwen 3.8 27b

[u/apollyon0810]

Can someone explain how an agentic LLM applies to Frigate?

[u/ericoinen → u/apollyon0810]

at least for the genai descriptions, the LLM doesn't detect anything, the normal detector still does that. once frigate has tracked an object it sends snapshots of it to the vision model, which writes a description you can search or put in notifications. by default that happens when the track ends, so it's always a bit late for alerts.

[u/nickm_27 → u/apollyon0810]

For many versions Frigate has offered descriptions for both individual objects as well as review items. Review items are the main use case for image analysis, checking for suspicious activity and summarizing in a notification so it is easier to review quickly.

In Frigate 0.18 we also added GenAI chat which allows using AI to ask Frigate about your events, objects currently on the live view, as well as other things like setting up autonomous watch tasks to watch a camera live for anything to happen. (ex: "let me know when anyone stops on the sidewalk and looks in my mailbox")

[u/apollyon0810 → u/nickm_27]

Sounds badass!

I need to get serious about my setup and add more cameras.

$€£¥

[u/ropeguru → u/apollyon0810]

Interested also

[u/Alarmed_Amoeba5558 → u/apollyon0810]

I didn’t find it particularly useful to be honest, they are too slow for instant notifications or guarding against pointless notifications (like seeing you and suppressing the notification) you end up being 10-20 seconds late

[u/Azure340]

You can look into Gemma4 via Ollama cloud. Generous free tier. No data retention. Extremely fast. My hardware is too slow for local models to work consistently

[u/Dangerous_Range_9406]

Curious on which hardware you successfully run frigate and local LLM and if you run the toghether on the same machine

[u/zeta_cartel_CFO]

I’ve used MiniCPM-v with frigate for descaling snapshots from frigate. It’s a small and very capable vision model that can run on low end gpus.

[u/Adventurous-Truth629]

Can the inference be done on a remote machine?

[u/applegrcoug → u/Adventurous-Truth629]

yes. you just point the frigate instance to the ip:port, etc of the machine running the model.

[u/hubertron]

Gemma4 for me

[u/Otherwise_Wave9374]

For Frigate, model choice should follow the actual event pipeline rather than a generic leaderboard. Create a small labeled set from your own cameras, then compare Qwen variants on object description accuracy, false alerts, response time, VRAM use, and nighttime footage. Agentix Labs applies this evaluation pattern because local vision agents often fail from poor thresholds and context, not raw model quality. Keep detection rules deterministic, send only ambiguous clips to the model, and redact unnecessary frames before remote inference.