anthropic ·claude-sonnet-4-5Oct 16, 09:38 PM
Asset gIRjPqM
Score
1
Latency
1.7s
Cost
$0.0089
Workflow Eval Detail
Analyzes video frames to detect hardcoded captions baked into the visual content—useful for compliance checks and accessibility audits.
Burned-in Captions achieved a 0.991 average score with strong integrity and validation results, while gpt-5.1 is recommended for quality and latency and gpt-5.6-luna for lowest cost.
Each eval run captures efficacy, efficiency, and expense. We use this data to compare providers and track regressions over time.
We evaluate caption detection accuracy, confidence calibration, and response integrity alongside speed and cost thresholds.
| Provider | Model | Cases | Avg Score | Avg Latency | Avg Tokens | Avg Cost | Avg Cost / Min |
|---|---|---|---|---|---|---|---|
| anthropic | claude-sonnet-4-5 | 3 | 1 | 2.09s | 3,184 | $0.0099 | $0.0346/min |
| gemini-2.5-flash | 3 | 1 | 5.01s | 2,578 | $0.0026 | $0.009/min | |
| gemini-3-flash-preview | 3 | 1 | 4.54s | 3,346 | $0.0036 | $0.0125/min | |
| gemini-3.1-flash-lite | 3 | 1 | 1.98s | 2,624 | $0.0007 | $0.0024/min | |
| openai | gpt-5-mini | 3 | 0.94 | 10.57s | 3,816 | $0.0025 | $0.0088/min |
| openai | gpt-5.1 | 3 | 1 | 1.95s | 2,279 | $0.0022 | $0.0077/min |
| openai | gpt-5.6-luna | 3 | 1 | 5.09s | 2,902 | $0.0004 | $0.0013/min |