Simulating realistic RAG / search-augmented answers parameters (8,000 in / 500 out with 50% cache reuse). DeepSeek Coder V2.5 delivers a 98% cost reduction over Perplexity Sonar Pro.
| Traffic Volume Tier | DeepSeek Coder V2.5 Monthly | Perplexity Sonar Pro Monthly | Monthly Savings by picking DeepSeek Coder V2.5 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $0.756 | $31.50 | Save $30.744 / mo |
| 10,000 reqs/mo (Small App) | $7.56 | $315.00 | Save $307.44 / mo |
| 100,000 reqs/mo (Growth Production) | $75.60 | $3,150.00 | Save $3,074.40 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $756.00 | $31,500.00 | Save $30,744.00 / mo |
DeepSeek Coder V2.5 is 98% cheaper for RAG / search-augmented answers workloads. At standard RAG / search-augmented answers parameter ratios (8,000 input tokens, 500 output tokens, 50% cache hit), DeepSeek Coder V2.5 costs $0.000756 per request compared to $0.0315 on Perplexity Sonar Pro.
DeepSeek Coder V2.5 offers a context window of 128,000 tokens (max output: 8,192), while Perplexity Sonar Pro offers 200,000 tokens (max output: 8,192).
At 100,000 requests per month, using DeepSeek Coder V2.5 saves $3,074.40 every month (or $36,892.80 annually) compared to Perplexity Sonar Pro.
retrieved-context dominates cost — tune top-k and chunk size before switching models. Re-rank and drop marginal chunks; halving context roughly halves input cost. Deduplicate repeated chunks across queries to raise the cache hit rate.