Simulating realistic AI coding assistant parameters (12,000 in / 2,000 out with 60% cache reuse). Qwen3 Coder Flash (OpenRouter) delivers a 75% cost reduction over GLM-5 (Z.ai).
| Traffic Volume Tier | GLM-5 (Z.ai) Monthly | Qwen3 Coder Flash (OpenRouter) Monthly | Monthly Savings by picking Qwen3 Coder Flash (OpenRouter) |
|---|---|---|---|
| 1,000 reqs/mo (Dev/Testing) | $12.64 | $3.167 | Save $9.473 / mo |
| 10,000 reqs/mo (Small App) | $126.40 | $31.668 | Save $94.732 / mo |
| 100,000 reqs/mo (Growth Production) | $1,264.00 | $316.68 | Save $947.32 / mo |
| 1,000,000 reqs/mo (Scale SaaS) | $12,640.00 | $3,166.80 | Save $9,473.20 / mo |
Qwen3 Coder Flash (OpenRouter) is 75% 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 $0.0126 on GLM-5 (Z.ai).
GLM-5 (Z.ai) offers a context window of 200,000 tokens (max output: 131,072), 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 $947.32 every month (or $11,367.84 annually) compared to GLM-5 (Z.ai).
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.