Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Qwen3 Coder Flash (OpenRouter) delivers a 92% cost reduction over Perplexity Sonar Deep Research.
| Traffic Volume Tier | Perplexity Sonar Deep Research Monthly | Qwen3 Coder Flash (OpenRouter) Monthly | Monthly Savings by picking Qwen3 Coder Flash (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $40.00 | $3.167 | Save $36.833 / mo |
| 10,000 reqs/mo (Small App) | $400.00 | $31.668 | Save $368.332 / mo |
| 100,000 reqs/mo (Growth Production) | $4,000.00 | $316.68 | Save $3,683.32 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $40,000.00 | $3,166.80 | Save $36,833.20 / mo |
Qwen3 Coder Flash (OpenRouter) is 92% cheaper for AI coding assistant workloads. At standard AI coding assistant parameter ratios (12,000 input tokens, 2,000 output tokens, 60% cache hit), Qwen3 Coder Flash (OpenRouter) costs $0.003167 per request compared to $0.04 on Perplexity Sonar Deep Research.
Perplexity Sonar Deep Research offers a context window of 128,000 tokens (max output: 16,384), while Qwen3 Coder Flash (OpenRouter) offers 1,000,000 tokens (max output: 65,536).
At 100,000 requests per month, using Qwen3 Coder Flash (OpenRouter) saves $3,683.32 every month (or $44,199.84 annually) compared to Perplexity Sonar Deep Research.
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.