Pricing
Agnify is pay-as-you-go. You’re billed only for the inference that actually runs — no seats, no subscriptions, no per-minute video tax. Every new account starts with $5 of free credit, and you top up from there whenever you want.
Estimate your cost
Section titled “Estimate your cost”Plug in a video length, how many frames per second you want analyzed, and which nodes your pipeline uses. The estimate updates as you type.
How billing works
Section titled “How billing works”Pricing is per successful inference call. One “call” is one priced node processing one analyzed frame. So the cost of a run is:
cost = Σ (rate for each node) × (frames analyzed by that node)A few consequences worth knowing:
- Only frames you analyze count. A 30 fps video analyzed at 1 fps is metered
as 1 frame per second, not 30. You set the sampling rate on the
FrameExtractornode. - Only successful calls are billed. Failed, mocked, or empty-input calls are never metered. A run that crashes on its first wave costs almost nothing.
- Unpriced nodes are free. Frame extraction, tracking, counting, redaction, and output nodes don’t call inference, so they add nothing to your bill.
- Detections returning zero objects still count. A successful inference that finds nothing is still a call that ran on a GPU.
- Pose estimation includes detection. Pose runs as a single fused detect-and-pose call, so a pose pipeline is billed at the pose rate alone — you aren’t charged separately for object detection on the same frames.
- Attribute extraction is billed per finished track, not per frame. It makes one VLM call for each tracked object as it leaves the scene — so its cost depends on how many distinct objects you see, not on frame count. That’s why it isn’t in the frame-based calculator above.
- The VLM nodes price by the model you choose. Frame description and attribute extraction can run on a small self-hosted model or the frontier Gemini API, and you’re charged the real cost of whichever you pick — a Gemini call costs roughly 30× a self-hosted 8B call.
Rate card
Section titled “Rate card”Rates are zero-margin — self-hosted rates reflect measured GPU cost, and the Gemini rates pass through Google’s API price, with no markup.
| Node | What it does | Billed | Rate |
|---|---|---|---|
| Object detection (D-FINE) | Bounding boxes for objects | per analyzed frame | $0.000001 |
| Segmentation (SAM3) | Pixel masks for objects | per analyzed frame | $0.000028 |
| Pose estimation | Body keypoints (detection included) | per analyzed frame | $0.000028 |
The VLM nodes — Frame description (per analyzed frame) and Attribute extraction (per finished track) — price by the selected model:
| Model | Hosting | Rate per VLM call |
|---|---|---|
| Qwen3.6 35B | self-hosted | $0.000056 |
| Qwen3.5 9B | self-hosted | $0.000028 |
| Gemini 3 Flash | Google API | $0.000380 |
| Gemini 3 Pro | Google API | $0.001550 |
For example, a 5-minute video analyzed at 1 fps (300 frames) with object
detection plus frame description on the Qwen3.5 9B model costs
300 × ($0.000001 + $0.000028) = $0.0087; switch frame description to Gemini 3
Pro and it’s 300 × ($0.000001 + $0.001550) = $0.4653. The same clip with
pose estimation (a fused detect-and-pose call) is 300 × $0.000028 = $0.0084.
Credits and top-ups
Section titled “Credits and top-ups”Your balance is a prepaid credit ledger, denominated in US dollars.
- Free signup credit: every new account gets $5 to start, automatically.
- Top up any time from the Top up menu in the app header or from Billing in organization settings. Preset amounts are $10, $25, $50, and $100, paid by card through Stripe’s hosted checkout.
- Runs start while you have a positive balance. When your balance hits zero, new runs are blocked until you top up — but an in-flight run is never killed mid-way, so your balance can dip slightly negative as the last charges settle.