Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Qwen 2.5 Coder 32B delivers a 93% cost reduction over Claude Sonnet 5.
| Traffic Volume Tier | Claude Sonnet 5 Monthly | Qwen 2.5 Coder 32B Monthly | Monthly Savings by picking Qwen 2.5 Coder 32B |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $31.04 | $2.304 | Save $28.736 / mo |
| 10,000 reqs/mo (Small App) | $310.40 | $23.04 | Save $287.36 / mo |
| 100,000 reqs/mo (Growth Production) | $3,104.00 | $230.40 | Save $2,873.60 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $31,040.00 | $2,304.00 | Save $28,736.00 / mo |
Qwen 2.5 Coder 32B is 93% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Qwen 2.5 Coder 32B costs $0.002304 per request compared to $0.031 on Claude Sonnet 5.
Claude Sonnet 5 offers a context window of 1,000,000 tokens (max output: 128,000), while Qwen 2.5 Coder 32B offers 128,000 tokens (max output: 8,192).
At 100,000 requests per month, using Qwen 2.5 Coder 32B saves $2,873.60 every month (or $34,483.20 annually) compared to Claude Sonnet 5.
Output is the expensive side — prefer models with cheap output for autocomplete-style calls. Cache repository context between keystrokes; diffs change far less than the full file. Measure acceptance rate: paying for output users delete is pure waste.