Batch and multimodal economics
GPU batch job cost calculator
Turn your measured cluster throughput into time, total cloud cost and cost per task. Compare the scenario with exact Qwen3-VL MLPerf Offline and Server results without pretending that those results transfer to your workload.
- No estimated TFLOPS conversion
- Explicit retry and checkpoint overhead
- Published samples/s and queries/s kept distinct
Your measured scenario
Estimate one complete batch
A task can be an image, request, render frame or document only if your throughput measurement uses that same unit.
Complete every field with measured or planned inputs.
Exact published system
Published Qwen3-VL batch reference economics
Every result below uses the same Nebius eight-GPU B300 system and is re-priced with the current official on demand $7.85 per-GPU-hour catalog rate, equal to $62.80 per hour for the exact eight-GPU reference system. This is a transparent reference calculation, not a promise for another workload.
batchOffline
qwen3-vl-235b-a22b
$0.2229 / 1K samples
- Published result
- 78.28 Samples/s
- Reference time
- 12.78 s / 1K samples
- System
- 8× NVIDIA B300
- Reference cluster rate
- $62.80 / h
- Reference yield @ $100 compute
- 448.72K samples
- Purchase model
- on demand
- Price observed
- 2026-08-13 02:40 UTC
- Capacity
- 8 GPUs available together: not verified
- Evidence
- 1 verified result
- Source revision
4d3916ac9cf4
F1_HIERARCHICAL: 0.7880721729948121
Inspect source evidence ↗batchServer
qwen3-vl-235b-a22b
$0.3864 / 1K queries
- Published result
- 45.15 Queries/s
- Reference time
- 22.15 s / 1K queries
- System
- 8× NVIDIA B300
- Reference cluster rate
- $62.80 / h
- Reference yield @ $100 compute
- 258.83K queries
- Purchase model
- on demand
- Price observed
- 2026-08-13 02:40 UTC
- Capacity
- 8 GPUs available together: not verified
- Evidence
- 1 verified result
- Source revision
4d3916ac9cf4
F1_HIERARCHICAL: 0.7865237675409595
Inspect source evidence ↗Calculation
Formula you can audit
Seconds = tasks ÷ measured cluster tasks/second × (1 + overhead). Total cost = seconds ÷ 3,600 × GPUs × price per GPU-hour. Unit cost = total cost ÷ tasks.