Simulating realistic Document summarization parameters (25,000 in / 600 out with 10% cache reuse). Qwen3 Coder Flash (OpenRouter) delivers a 92% cost reduction over GPT-5.4 Workhorse.
| Traffic Volume Tier | GPT-5.4 Workhorse Monthly | Qwen3 Coder Flash (OpenRouter) Monthly | Monthly Savings by picking Qwen3 Coder Flash (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $65.875 | $5.07 | Save $60.805 / mo |
| 10,000 reqs/mo (Small App) | $658.75 | $50.70 | Save $608.05 / mo |
| 100,000 reqs/mo (Growth Production) | $6,587.50 | $507.00 | Save $6,080.50 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $65,875.00 | $5,070.00 | Save $60,805.00 / mo |
Qwen3 Coder Flash (OpenRouter) is 92% cheaper for Document summarization workloads. At standard Document summarization parameter ratios (25,000 input tokens, 600 output tokens, 10% cache hit), Qwen3 Coder Flash (OpenRouter) costs $0.00507 per request compared to $0.0659 on GPT-5.4 Workhorse.
GPT-5.4 Workhorse offers a context window of 256,000 tokens (max output: 32,768), while Qwen3 Coder Flash (OpenRouter) offers 1,000,000 tokens (max output: 65,536).
At 100,000 requests per month, using Qwen3 Coder Flash (OpenRouter) saves $6,080.50 every month (or $72,966.00 annually) compared to GPT-5.4 Workhorse.
Long-context models pay off here — compare price per 1M tokens at your true document size. Summarize once, store the result; don't re-summarize unchanged documents. For batch backfills, nightly jobs can use cache-friendly request ordering.