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Model reference — Live feed

AI models for Live stream moderation / visual policy alerts

This service watches a live stream against your published policy and raises an alert when something breaks it — nudity, violence, weapons, prohibited symbols, banned products, or spoken abuse — fast enough for a moderator to intervene while it is happening.

Two constraints shape every deployment. The first is that the picture and the sound must both be watched, since a stream can be entirely acceptable visually and unacceptable in what is said. The second is the alert budget: moderators can only act on so many alerts an hour, so the thresholds are set to fit the moderation team you actually have, and the system is measured on what it lets through at that rate. Automatic cut-off is possible but is normally reserved for the narrow set of categories where a false positive is cheaper than a false negative.

Live stream moderation / visual policy alerts service AI models for live feed

Input type — Live feed

Models in this group take a live camera or stream as input and must keep pace with it in real time. Each specification table gives three hardware tiers — Minimum, the smallest setup on which the model runs correctly; Medium, the usual production configuration; and High, a configuration sized for peak volume. The rate is how many camera streams or feeds one server of that tier can keep up with in real time, not a per-hour count: live work must fit inside the interval between frames, and a server that cannot keep pace drops frames rather than falling behind. Use these rates for initial sizing. Before production, benchmark your own data to validate accuracy, latency, throughput and cost. The sample input here is one 1080p stream at 25 frames per second.

CLIP-based NSFW classifier

Vendor: LAION

What it does: scores frames for sexual content against a written description, so the definition can be tuned to your policy rather than a fixed notion. The usual visual first pass.

RequirementMinimumMediumHigh
GPU typeRTX 3060RTX 4090A100 80 GB
VRAM6 GB24 GB80 GB
vCPUs4824
RAM16 GB32 GB64 GB
Server1× RTX 3060 12 GB1× RTX 4090 24 GB1× A100 SXM 80 GB
Rate (camera streams handled at 25 frames per second)≈ 12 streams≈ 45 streams≈ 130 streams

NudeNet

Vendor: community-maintained open-source project

What it does: a very small classifier detecting explicit content cheaply, light enough to run on every frame of many streams at once.

RequirementMinimumMediumHigh
GPU typeRTX 3060RTX 4090A100 80 GB
VRAM4 GB24 GB80 GB
vCPUs4824
RAM8 GB32 GB64 GB
Server1× RTX 3060 12 GB1× RTX 4090 24 GB1× A100 SXM 80 GB
Rate (camera streams handled at 25 frames per second)≈ 40 streams≈ 150 streams≈ 450 streams

Falconsai NSFW image detection

Vendor: Falcons.ai

What it does: an alternative classifier used alongside the others, since agreement between two independent models is a far better basis for automatic action than either alone.

RequirementMinimumMediumHigh
GPU typeRTX 3060RTX 4090A100 80 GB
VRAM6 GB24 GB80 GB
vCPUs4824
RAM16 GB32 GB64 GB
Server1× RTX 3060 12 GB1× RTX 4090 24 GB1× A100 SXM 80 GB
Rate (camera streams handled at 25 frames per second)≈ 20 streams≈ 70 streams≈ 200 streams

YOLO11

Vendor: Ultralytics

What it does: detects specific prohibited objects — weapons, particular products, banned symbols — fitted to your own list. The precise component of the policy check.

RequirementMinimumMediumHigh
GPU typeRTX 3060RTX 4090A100 80 GB
VRAM6 GB24 GB80 GB
vCPUs4824
RAM16 GB32 GB64 GB
Server1× RTX 3060 12 GB1× RTX 4090 24 GB1× A100 SXM 80 GB
Rate (camera streams handled at 25 frames per second)≈ 10 streams≈ 36 streams≈ 100 streams

YOLO-World

Vendor: Tencent AI Lab

What it does: detects objects from a written list without being fitted first, which lets a new policy item be enforced the day it is added.

RequirementMinimumMediumHigh
GPU typeRTX 3060RTX 4090A100 80 GB
VRAM8 GB24 GB80 GB
vCPUs61224
RAM16 GB32 GB64 GB
Server1× RTX 3060 12 GB1× RTX 4090 24 GB1× A100 SXM 80 GB
Rate (camera streams handled at 25 frames per second)≈ 3 streams≈ 12 streams≈ 34 streams

Qwen2.5-VL 7B / 72B

Vendor: Alibaba Cloud

What it does: judges a flagged frame against your written policy in context — distinguishing a medical image from an explicit one — which is what reduces false alerts. Applied only to frames another model flagged.

RequirementMinimumMediumHigh
GPU typeRTX 4090 (7B, reduced precision)A100 80 GB (7B, full precision)2× H100 80 GB (72B model)
VRAM16 GB80 GB160 GB combined
vCPUs81632
RAM32 GB64 GB200 GB
Server1× RTX 4090 24 GB1× A100 SXM 80 GB2× H100 SXM 80 GB
Rate (camera streams handled at 25 frames per second)≈ 1 stream≈ 4 streams≈ 8 streams

Parakeet TDT

Vendor: NVIDIA

What it does: transcribes the stream live so what is said can be checked as well as what is shown.

RequirementMinimumMediumHigh
GPU typeRTX 3090RTX 4090A100 80 GB
VRAM12 GB24 GB80 GB
vCPUs81224
RAM32 GB48 GB96 GB
Server1× RTX 3090 24 GB1× RTX 4090 24 GB1× A100 SXM 80 GB
Rate (camera streams handled at 25 frames per second)≈ 8 streams≈ 30 streams≈ 80 streams

Llama Guard 3

Vendor: Meta

What it does: checks the live transcript against your policy and reports which category is broken, with the passage that broke it.

RequirementMinimumMediumHigh
GPU typeRTX 3090RTX 4090H100 80 GB
VRAM16 GB24 GB80 GB
vCPUs81224
RAM32 GB48 GB128 GB
Server1× RTX 3090 24 GB1× RTX 4090 24 GB1× H100 SXM 80 GB
Rate (camera streams handled at 25 frames per second)≈ 6 streams≈ 20 streams≈ 60 streams

Choosing between them

The configuration depends on your policy, your audience and the size of your moderation team. Our consultants review your policy and a sample of your streams, then recommend the models, the thresholds for alert and automatic action, and the human review the result requires.

At the start of a project we may run a short proof of concept on a sample of your own data, measuring the accuracy and the throughput the model actually achieves on your material. That replaces the estimates on this page with real figures, so the cost and the schedule for the full engagement are known before it is committed.

Live stream moderation / visual policy alerts service AI models for live feed Pricing

From benchmark to production

Share a representative sample, expected volume, latency target and deployment location for Live stream moderation / visual policy alerts. We benchmark the shortlisted models, recommend the lowest-cost GPU configuration that meets the target, and scale it from pilot capacity to a dedicated production cluster.