Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
12 KiB
MiniMax H3 serving plan — pools, pricing, capacity scenarios
Prepared 2026-08-06. Every generation time in this document is measured on
our pods (see docs/BENCHMARKS.md); derived numbers state their formula.
GPU prices are what we actually pay: B200 $6.94/hr, RTX 5090 $0.99/hr,
RTX 4090 $0.74/hr. All jobs are 20 steps, 24 fps, template sampler settings.
Two structural facts drive everything:
- One generation saturates one GPU (measured: co-scheduling is 13% slower). Throughput = number of workers; latency = service time + queue.
- bf16 is the fastest family wherever it fits — including, surprisingly, layer-streamed on the RTX 5090 (110 s vs 143 s pruned for the standard clip). Quantized families are for VRAM-constrained multi-model workers, not for speed or cost.
The product surface (what we can offer)
Modalities: text-to-video, keyframe-to-video (first and/or last frame), reference-to-video (1–9 images; also up to 3 ref videos + 3 audio clips, untested by us). All produce video + native stereo audio.
Resolutions (canvas must be multiples of 32, area ≤ ~1.03 MP):
| Tier | 16:9 | 9:16 | 1:1 | Notes |
|---|---|---|---|---|
| Draft (352p) | 608×352 | 352×608 | 448×448 | fastest, preview quality |
| SD (480p) | 864×480 | 480×864 | 640×640 | the sweet spot |
| HD (768p) | 1344×768 | 768×1344 | 992×992 | native max; ~3.3× cost |
Intermediate 16:9 rungs exist every 32 px (736×416, 960×544, 1056×608, 1152×640, 1216×672, 1280×736) — we recommend selling the three tiers above. Other aspects (4:3, 21:9, …) work too — anything multiple-of-32 under the area cap. 2K does not exist locally (hosted-API upscale only).
Durations: frame count must satisfy n ≡ 5 (mod 17); trained range 124–362 frames → ~5.2 s to ~15.1 s in ~0.7 s steps (5.2, 5.9, 6.6, 7.3, 8.0, 8.7, 9.4, 10.1, 10.8, 11.5, 12.2, 12.9, 13.7, 14.4, 15.1). Sell "5 / 10 / 15 seconds"; internally snap up to the grid. fps is fixed at 24.
Pool 1 — Paid (bf16, everything)
Worker type
B200 (180 GB) is the only worker class that runs the entire paid surface on bf16 — HD, 15 s, and heavy reference jobs all need its VRAM. However, 55–70 % of paid traffic (≤480p, ≤10 s) runs 4× cheaper on 5090-bf16 workers at identical weights/quality. Recommended deployment:
- 5090 bf16 pool — handles t2v/i2v/ref2v at ≤480p, ≤10 s (dedicated single-model workers; no model switching, so no cache-none tax).
- B200 bf16 pool (small) — handles HD, >10 s, and
max-sizing reference jobs; also absorbs overflow for latency.
Route by job shape. This hybrid cuts blended cost ~2.5–3× vs all-B200.
Cost per video (B200 bf16, measured/derived)
t2v baseline; keyframe (i2v) ≈ +5 %; reference adder below.
| Resolution | 5 s | 10 s | 15 s |
|---|---|---|---|
| Draft 352p | 26 s → $0.050 | 63 s → $0.122 | 111 s → $0.214 |
| SD 480p | 51 s → $0.098 | 125 s → $0.240 | 240 s → $0.463 |
| HD 768p | 169 s → $0.326 | 490 s → $0.945 | 965 s → $1.861 |
(10 s and 352p/HD-longer cells derived from measured duration/resolution scaling on identical hardware; 480p-5/15 s, HD-5 s are directly measured.)
Reference-to-video adder (match sizing): +$0.006 (1 ref) to +$0.054
(8–9 refs) at ≤480p; +$0.22 at HD with 8 refs. max reference sizing
multiplies job cost ~5–10× — if offered at all, price it as its own SKU at
~5× the base price, or restrict to ≤4 refs (+$0.08).
On the 5090-bf16 pool the same ≤480p jobs cost: 5 s $0.030 · 10 s $0.074 ·
1-ref +$0.01. Blend accordingly; the pricing below uses B200 costs as
the conservative basis, so hybrid routing only improves your real margin.
Pricing table (per video, 480p/SD baseline, t2v/i2v)
Margin means gross margin on price (price = cost ÷ (1 − margin)).
| Duration | Cost | 0% | 15% | 25% | 50% | 70% |
|---|---|---|---|---|---|---|
| 5 s | $0.098 | $0.098 | $0.116 | $0.131 | $0.197 | $0.328 |
| 10 s | $0.240 | $0.240 | $0.283 | $0.320 | $0.481 | $0.801 |
| 15 s | $0.463 | $0.463 | $0.545 | $0.617 | $0.926 | $1.543 |
| SKU modifiers | ×cost | example @25% margin, 10 s |
|---|---|---|
| Draft 352p | ×0.51 | $0.163 |
| HD 768p | ×3.6+ | $1.260 (5 s: $0.434, 15 s: $2.481) |
| + references (≤9, match) | +$0.01–0.06 | round: +$0.05 |
| + references at HD | +$0.22 | round: +$0.30 |
| keyframe (first/last frame) | +5 % | fold into base |
Simple public menu suggestion (at ~50 % blended margin, knowing hybrid routing makes true margin higher): Draft $0.10 · SD $0.20/5 s · HD $0.65/5 s; +$0.05 per clip with references; duration billed per 5 s block.
Pool 2 — Free (480p, 5 s, ≤3 cropped refs)
Constraint set: 864×480 (any of the three aspects), 5 s, up to 3 reference
images pre-cropped/downscaled (our --ref-downscale 0.2 path — measured to
also improve stability and speed).
Cost per 1,000 free generations (measured)
| Worker + weights | time/job | jobs/hr/worker | $/1k videos |
|---|---|---|---|
| 5090 bf16 (t2v/i2v only) | 110 s | 32.7 | $30 |
| 5090 pruned int8, t2v | 143 s | 25.2 | $39 |
| 5090 pruned int8, 3 refs | ~176 s | 20.5 | $48 |
| 4090 patched, 3 refs | ~400 s | 9.0 | $82 |
| B200 bf16, 3 refs | 60 s | 60.0 | $116 |
int8 (non-pruned) sits between pruned and bf16 in speed on every card and
fits nothing extra — it has no serving niche; skip it. Recommendation:
free pool = 5090s running pruned int8 with the ref2va model resident
(one model handles ref jobs; t2v works via 0-ref… no — t2v needs fl2va).
Practical split: ~⅓ of free workers hold fl2va (t2v/i2v jobs, $39/1k), ⅔
hold ref2va (ref jobs, $48/1k) — no model switching, no cache-none tax,
blended **$45 per 1,000 free videos**. bf16-on-5090 is competitive for
t2v-only but its ref2v carries the switch tax; revisit if free tier drops
references.
Quality note: pruned int8's output is strong (community: "near-lossless lineage"), and free users get 480p/5 s — the quality delta vs bf16 at this tier is minimal. If you want bf16 everywhere anyway, free costs rise ~25 %.
Capacity & demand scenarios
Model: workers sized so that peak-hour utilization ≤ 70 % (queueing knee). Peak hour assumed 3× the daily average rate. Wait ≈ service_time × ρ/(1−ρ) per M/M/1 worker; at 70 % that's ~2.3× service time queued ahead of you — the sizing keeps typical waits under ~1 job-length even at peak.
Wait-time intuition (176 s free ref job):
| Utilization | Avg queue wait |
|---|---|
| 50 % | ~3 min |
| 70 % | ~7 min |
| 85 % | ~17 min |
| 95 % | ~56 min |
Free pool (5090 pruned, blended 165 s/job, 21.8 jobs/hr/worker)
| Demand (videos/day) | Peak rate/hr | Workers (70 % peak) | $/day (24/7) | $/day (autoscaled*) | Mean-hour wait | Peak wait |
|---|---|---|---|---|---|---|
| 1,000 | 125 | 9 | $214 | ~$95 | <1 min | ~6 min |
| 5,000 | 625 | 41 | $974 | ~$430 | <1 min | ~6 min |
| 20,000 | 2,500 | 164 | $3,897 | ~$1,700 | <1 min | ~6 min |
| 100,000 | 12,500 | 820 | $19,483 | ~$8,600 | <1 min | ~6 min |
*Autoscaled ≈ 44 % of 24/7 (integrate a 3:1 peak:trough sinusoidal day at 70 % target util). Requires image-baked or volume-attached workers that cold start in ~4 min (measured: container rebuild ~4 min + first model load ~40 s on a warm volume).
Rule of thumb: free tier costs ~$45 per 1,000 videos served — the worker math above just determines how fast you serve them.
Paid pool (hybrid; blended job assumed 60 % SD-5s / 20 % SD-10s / 10 % HD-5s / 10 % ref-heavy)
Blended: $0.11 cost per job on hybrid routing ($0.16 all-B200), ~150 s
blended service time on the 5090 share, 84 s on the B200 share.
| Demand (jobs/day) | 5090 workers | B200 workers | $/day (24/7) | Revenue/day @25 % margin | @50 % |
|---|---|---|---|---|---|
| 500 | 3 | 1 | $238 | $73 rev / $55 cost* | $110 |
| 2,500 | 12 | 2 | $618 | $367 / $275 | $550 |
| 10,000 | 46 | 5 | $1,926 | $1,467 / $1,100 | $2,200 |
| 50,000 | 229 | 22 | $9,105 | $7,333 / $5,500 | $11,000 |
*Cost column is per-job cost × volume (what you actually burn on GPU-seconds); the $/day worker column is capacity cost at 24/7 — the gap is idle headroom, recovered by autoscaling (×0.44) or by letting free-tier jobs soak idle paid workers (recommended: one queue, two priorities — paid preempts free).
Break-even insight: at 25 % margin the paid pool only covers its 24/7 capacity above ~4,000 jobs/day; below that, either autoscale, raise margin, or (best) run paid and free as one fleet with priority scheduling so paid headroom serves free demand instead of idling.
Concrete deployment recommendation
- One fleet, two queues (paid priority, free backfill) on RTX 5090 workers in one region sharing a network volume: bf16-fl2va workers for paid t2v/i2v ≤480p/≤10 s, pruned-ref2va workers for all reference jobs and free tier.
- Small B200 pool (1–2 + burst) for HD / 15 s / max-sizing paid SKUs.
- Config per
docs/MITIGATIONS.md: 5090s need the #15316 patch +--reserve-vram 4; keep one model per worker (no switching) to avoid every RAM-cap failure mode we found. - Autoscale on queue depth; workers cold-start in ~5 min from a shared volume (bake the container image to cut pip-install; then ~1 min).
- Watch for ComfyUI merging #15316 and the KJNodes SageAttention patch (~2× potential speedup, currently broken for H3) — either would shift every number in this doc favorably.
Assumptions register (audit before betting real money)
- GPU prices: our current RunPod rates; community-cloud 5090s can be ~30 % cheaper, secure-cloud availability at scale unverified (provider/worker- availability research is a pending follow-up).
- 10 s and 352p/HD-long cells derived from measured scaling laws, not directly timed on bf16; ±15 % error bars.
- 3-ref free-tier time interpolated between measured 1-ref and 4-ref runs.
- Peak:average = 3:1 assumed; measure your real diurnal curve and re-run the sizing (formulas inline above).
- No egress/storage/queue-infra costs included (small: ~1–3 MB per video).
- Quality parity of pruned int8 for the free tier is a judgment call — A/B the actual outputs (they're all on the pods' volumes).