Simulating realistic Document summarization parameters (25,000 in / 600 out with 10% cache reuse). Fireworks AI — DeepSeek R1 delivers a 48% cost reduction over o3-mini.
| Traffic Volume Tier | o3-mini Monthly | Fireworks AI — DeepSeek R1 Monthly | Monthly Savings by picking Fireworks AI — DeepSeek R1 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $28.765 | $15.064 | Save $13.701 / mo |
| 10,000 reqs/mo (Small App) | $287.65 | $150.64 | Save $137.01 / mo |
| 100,000 reqs/mo (Growth Production) | $2,876.50 | $1,506.40 | Save $1,370.10 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $28,765.00 | $15,064.00 | Save $13,701.00 / mo |
Fireworks AI — DeepSeek R1 is 48% cheaper for Document summarization workloads. At standard Document summarization parameter ratios (25,000 input tokens, 600 output tokens, 10% cache hit), Fireworks AI — DeepSeek R1 costs $0.0151 per request compared to $0.0288 on o3-mini.
o3-mini offers a context window of 200,000 tokens (max output: 100,000), while Fireworks AI — DeepSeek R1 offers 128,000 tokens (max output: 16,384).
At 100,000 requests per month, using Fireworks AI — DeepSeek R1 saves $1,370.10 every month (or $16,441.20 annually) compared to o3-mini.
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.