Simulating realistic Document summarization parameters (25,000 in / 600 out with 10% cache reuse). Fireworks AI — DeepSeek R1 delivers a 69% cost reduction over Pixtral Large.
| Traffic Volume Tier | Pixtral Large Monthly | Fireworks AI — DeepSeek R1 Monthly | Monthly Savings by picking Fireworks AI — DeepSeek R1 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $49.10 | $15.064 | Save $34.036 / mo |
| 10,000 reqs/mo (Small App) | $491.00 | $150.64 | Save $340.36 / mo |
| 100,000 reqs/mo (Growth Production) | $4,910.00 | $1,506.40 | Save $3,403.60 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $49,100.00 | $15,064.00 | Save $34,036.00 / mo |
Fireworks AI — DeepSeek R1 is 69% 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 $0.0491 on Pixtral Large.
Pixtral Large offers a context window of 128,000 tokens (max output: 8,192), 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 $3,403.60 every month (or $40,843.20 annually) compared to Pixtral Large.
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.