Simulating realistic Data extraction & tagging parameters (2,000 in / 250 out with 20% cache reuse). DeepSeek Coder V2.5 delivers a 37% cost reduction over Qwen 2.5 Coder 32B.
| Traffic Volume Tier | DeepSeek Coder V2.5 Monthly | Qwen 2.5 Coder 32B Monthly | Monthly Savings by picking DeepSeek Coder V2.5 |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $0.2996 | $0.478 | Save $0.1784 / mo |
| 10,000 reqs/mo (Small App) | $2.996 | $4.78 | Save $1.784 / mo |
| 100,000 reqs/mo (Growth Production) | $29.96 | $47.80 | Save $17.84 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $299.60 | $478.00 | Save $178.40 / mo |
DeepSeek Coder V2.5 is 37% cheaper for Data extraction & tagging workloads. At standard Data extraction & tagging parameter ratios (2,000 input tokens, 250 output tokens, 20% cache hit), DeepSeek Coder V2.5 costs $0.0003 per request compared to $0.000478 on Qwen 2.5 Coder 32B.
DeepSeek Coder V2.5 offers a context window of 128,000 tokens (max output: 8,192), while Qwen 2.5 Coder 32B offers 128,000 tokens (max output: 8,192).
At 100,000 requests per month, using DeepSeek Coder V2.5 saves $17.84 every month (or $214.08 annually) compared to Qwen 2.5 Coder 32B.
Volume makes nano-tier models attractive — extraction rarely needs frontier reasoning. Constrain output with JSON schema modes to avoid retry loops on malformed responses. Cache shared schema instructions and few-shot examples across calls.