Primate Vision vs. Gemini (API + Live) (2026): 1fps Stills vs. Native Frame Rate
Let me start with the concession, because it’s a big one: Gemini is the strongest general-purpose video-understanding model you can rent, and at its default 1fps sampling it’s dramatically cheaper than us. If you want conversational answers about stored video — summaries, Q&A, world-knowledge reasoning — it’s excellent.
But for real-time video analysis, the spec sheet decides, not the marketing. Gemini Live’s video input is hard-capped at 1fps JPEG stills. Audio+video sessions last 2 minutes without context compression. And the meter re-bills the entire session context on every turn. Primate Vision watches live video at native frame rates over managed WebRTC (45ms p50 per-frame inference) and returns a deterministic verdict — yes / no / indeterminate — with calibrated confidence, timestamps, and an annotated evidence video, on a flat per-second meter.
A note on keeping Google straight: this post is about Gemini — Google’s modern multimodal surface. Google Video Intelligence, the 2017-era annotation API, is a different product with different criticisms; we cover it in the full landscape comparison. Don’t conflate them — we don’t.
Two different jobs
Gemini is a universal brain. Video is one input modality among many, decomposed into sampled frames plus audio tokens, answered with generated prose or JSON. Google’s own docs describe the capability well — “describe, segment, and extract information from videos, answer questions about video content” (video understanding docs).
Primate Vision is a measurement instrument. It watches video — live (managed WebRTC) or uploaded (up to 2 GiB, direct or URL ingest) — and answers one framed question with a deterministic verdict (yes / no / indeterminate), a calibrated 0–1 confidence score, timestamped evidence segments, and an annotated overlay evidence video. Verdicts are computed by similarity scoring against the video, not sampled from a language model, and you can pin the model version (darwin-1.3) so behavior changes only when you choose.
The head-to-head
| Capability | Primate Vision | Gemini (API + Live) |
|---|---|---|
| Live video input | ✅ managed WebRTC, native frame rate | ⚠️ Live API: “images (JPEG <= 1FPS)” — frame-push stills, WebRTC only via third parties (Live docs) |
| Live session length | ✅ up to 1 hour per session on top plans; API publishes your cap and warns before cutoff | ⚠️ audio+video capped at 2 minutes without compression; ~10-min connection lifetime (session docs) |
| Published latency | ✅ 45ms p50 / 316ms p95, 11.8 fps sustained, 6.6s setup | ❌ none — “low-latency” marketing language only |
| Verdict contract | ✅ deterministic yes/no/indeterminate + calibrated 0–1 confidence | ⚠️ JSON schema possible, but uncalibrated, no indeterminate semantics, nondeterministic LLM sample |
| Reproducibility | ✅ deterministic verdict path, model pinning, deterministic test mode | ❌ temperature/top_p/top_k deprecated on 3.x (2026-07-21) — you can’t even pin temperature=0 (changelog) |
| Evidence artifacts | ✅ annotated overlay evidence video + timestamped clips | ❌ text/JSON/audio out only |
| Fast-action fidelity | ✅ native frame rate | ⚠️ Google’s own docs: 1fps “might lose detail… Consider slowing down such clips” (docs) |
| Transcript / OCR / audio | ❌ visual only | ✅ native audio, transcription, OCR |
| Embeddings / search | ❌ none | ✅ multimodal embeddings GA |
| Webhooks | ✅ Standard Webhooks + Prefer: wait |
✅ launched 2026-05-04 for Batch + long-running ops |
That last row matters for honesty: earlier analyses called Google “polling-only.” That’s now wrong for Gemini — they shipped webhooks in May 2026. (It remains true for Google Video Intelligence, the other Google surface.)
The 1fps wall
This is the crux, and it’s Google’s spec, not our characterization. The Live API’s input modalities are listed as “Audio…, images (JPEG <= 1FPS), text.”
Think about what one frame per second means physically. A person falls in 0.7 seconds. A package is snatched between frames. At one still per second, fast events cannot be seen — not “detected less accurately,” not seen — which is why Google’s own video docs recommend “slowing down such clips” as the workaround for fast action. That’s a fine tip for stored files. It is not available advice for a live camera.
On the file path you can request a higher custom fps. Then the token meter answers. Which brings us to pricing.
Pricing: flat meter vs. compounding token curve
Gemini bills tokens. Each frame is 258 tokens at default resolution; ~300 tokens/second of video all-in. At the 1fps default on Flash-Lite, that’s roughly $0.28 per camera-hour input (estimate, input-only) — 100×+ cheaper than our metered rate. I’m not going to pretend otherwise. If 1fps is enough and prose is enough, Gemini is very cheap and you should use it.
But two curves bend the other way:
- Fidelity parity. At 12fps — what Primate Vision actually sustains — Gemini’s input tokens alone reach $0.28–$0.37/min on frontier models (3.6 Flash / 3.1 Pro): 46–62% of Primate’s all-in $0.60/min, before output tokens, before thinking tokens, and with no verdict layer, no calibration, and no evidence artifacts on top.
- The Live re-billing trap. Google’s own best-practices page: “Past tokens are re-processed and accounted for in each new turn… As a session lengthens, the cost per turn increases because the conversational history is re-processed” (best practices). Interactive live-video sessions get superlinearly expensive and CFO-unpredictable.
Primate Vision has two lanes, stated plainly:
- Metered — $0.01 per second of source video ($0.60/min), flat, fps-independent — 10 seconds at 60fps bills as 10 seconds. Queued time free; failed jobs free. A 30-second clip → verdict + confidence + timestamps + evidence video = $0.30.
- Enterprise — contact us for 24/7 continuous monitoring and camera fleets: dedicated capacity or on-site deployment at a small fraction of the metered rate, under highly discounted enterprise plans.
Normalized honestly: at 1fps Gemini is ~$0.28–$1.39/camera-hour (estimate, input-only) versus $36/camera-hour† at our metered rate. The metered lane isn’t priced for passive camera-hours — it’s priced per answered question with evidence. When the workload is camera-hours, that’s the enterprise lane.
† Metered rate normalized for comparison. Primate does not sell 24/7 continuous monitoring at the metered rate — continuous and fleet workloads use enterprise plans; contact us.
One more production consideration: model churn. Gemini 2.0 was shut down June 2026. Preview models are routinely retired on ~30-day notice. The Live model on the developer API is still -preview (GA only via Vertex). Every forced migration means re-validating your video pipeline — anyone who’s shipped on a fast-moving model API knows exactly what that costs. Primate Vision versions models as pinnable resources. Behavior changes when you choose.
Choose Gemini instead when…
These are its lanes, not ours:
- Conversational “what am I looking at?” experiences. Voice assistant over a screen share or camera where prose/audio is the product — Shopify’s Sidekick is built on Gemini Live via Vertex. We don’t do conversation.
- Low-fps, low-stakes monitoring at massive scale, where ~$0.30–$1.40/camera-hour beats everything and an occasional miss is tolerable.
- Rich Q&A and summarization over stored footage where world knowledge matters more than temporal precision — lectures, meetings, content libraries. And it can hear: transcription and audio understanding we simply don’t have.
- Semantic search over video via multimodal embeddings (GA) — we offer no embeddings.
- One-vendor GCP shops that want LLM + vision + audio + embeddings under Vertex SLAs.
Choose Primate Vision when…
- The event is faster than one second. Native frame rate vs. 1fps stills isn’t a tuning difference; it’s whether the event is visible at all.
- The output feeds an alert, a workflow, or a compliance record. A deterministic verdict with calibrated confidence and a watchable evidence video — versus a nondeterministic prose sample you can no longer even pin to temperature=0.
- You need sessions longer than 2 minutes on live audio+video, without context-compression gymnastics and resumption tokens.
- You need a predictable bill. Seconds × $0.01, flat — versus a token meter that compounds per turn.
- Latency is a requirement. We publish 45ms p50 / 316ms p95 / 11.8 fps / 6.6s setup on a public /performance page. Google publishes no latency numbers for video on either surface.
Try it
Try it for free — real processing, no card required to start.
Your AI agent can do it for you — right from Claude. Primate Vision ships an MCP server, llms.txt, markdown docs twins, and a sandbox key available in a single POST — your agent can get a key, upload a clip, and read back a verdict without a human touching a dashboard.
For 24/7 monitoring and camera fleets: see our enterprise plans.
Method note: every Gemini claim traces to ai.google.dev docs, pricing, and changelog pages accessed 2026-07-31. Estimates are labeled. Google’s own per-minute price equivalences are internally inconsistent with its documented tokenization (~8× gap) — we quote the documented token math.